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Volume 8
Issue 4
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Machines, Volume 8, Issue 4 (December 2020) – 31 articles

Cover Story (view full-size image): Automatic ball balancing is a technique adopted in rotordynamics to automatically reduce unknown rotor unbalance. This technique is appealing as it can ease a panoply of balancing issues considerably. The presence of stiction, however, scatters consistent qualitative balancing, which has led to limited implementation in the industry. Temporary speed reduction, a recent technique, could be used as a countermeasure for the stiction-induced scattering. This paper presents an in-depth study detailing how the technique should be implemented to guarantee effective balancing. The main findings of the study are that the adverse effects of stiction can be contained considerably using the speed reduction technique, especially in the under-excited range where a ball balancer behaves poorly when adopting a standard run-up profile. View this paper
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15 pages, 37237 KiB  
Article
Surface Finishing of Zirconium Dioxide with Abrasive Brushing Tools
by Eckart Uhlmann and Anton Hoyer
Machines 2020, 8(4), 89; https://doi.org/10.3390/machines8040089 - 21 Dec 2020
Cited by 10 | Viewed by 2762
Abstract
Brushing with bonded abrasives is a finishing process which can be used for the surface improvement of various materials. Since the machining mechanisms of abrasive brushing processes are still largely unknown and little predating research was done on brushing ceramic workpieces, within the [...] Read more.
Brushing with bonded abrasives is a finishing process which can be used for the surface improvement of various materials. Since the machining mechanisms of abrasive brushing processes are still largely unknown and little predating research was done on brushing ceramic workpieces, within the scope of this work technological investigations were carried out on planar workpieces of MgO-PSZ (zirconium dioxide, ZrO2) using brushing tools with bonded grains of polycrystalline diamond. The primary goal was the reduction of grinding-related surface defects under the preservation of surface roughness valleys and workpiece form. Based on microscopy and topography measurements, the grain size sg and the brushing velocity vb were found to have a considerable influence on the processing result. Furthermore, excessive tool wear was observed while brushing ceramics. Full article
(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Layout of a circular abrasive brush tool [<a href="#B9-machines-08-00089" class="html-bibr">9</a>].</p> Full article ">Figure 2
<p>Workpiece properties.</p> Full article ">Figure 3
<p>Experimental equipment: (<b>a</b>) profile grinding machine; (<b>b</b>) tactile surface measurement device; (<b>c</b>) tactile roughness measurement device; (<b>d</b>) exemplary circular brush used during technological investigations; (<b>e</b>) scanning electron microscope; (<b>f</b>) light microscope.</p> Full article ">Figure 4
<p>SEM images of the plane ground ZrO<sub>2</sub> surface.</p> Full article ">Figure 5
<p>Light microscopy images of ZrO<sub>2</sub> with characteristic surface defects: (<b>a</b>) ground surface; (<b>b</b>) brushed with abrasive filaments with a filament diameter of d<sub>f</sub> = 0.6 mm.</p> Full article ">Figure 6
<p>Light microscopy images of ZrO<sub>2</sub> under the variation of the grain size s<sub>g</sub>: (<b>a</b>) ground surface; (<b>b</b>) brushed with a grain size of s<sub>g</sub> = 320 mesh; (<b>c</b>) brushed with a grain size of s<sub>g</sub> = 240 mesh; (<b>d</b>) brushed with a grain size of s<sub>g</sub> = 80 mesh.</p> Full article ">Figure 7
<p>Topography of ZrO<sub>2</sub>, brushed with a grain size of s<sub>g</sub> = 320 mesh.</p> Full article ">Figure 8
<p>Topography of ZrO<sub>2</sub>, brushed with a grain size of s<sub>g</sub> = 80 mesh.</p> Full article ">Figure 9
<p>Light microscopy images of ZrO<sub>2</sub> under the variation of the brushing velocity v<sub>b</sub>: (<b>a</b>) ground surface; (<b>b</b>) brushed with a brushing velocity of v<sub>b</sub> = 10 m/s; (<b>c</b>) brushed with a brushing velocity of v<sub>b</sub> = 20 m/s; (<b>d</b>) brushed with a brushing velocity of v<sub>b</sub> = 30 m/s.</p> Full article ">Figure 10
<p>SEM images of ZrO<sub>2</sub> surface, brushed with a brushing velocity of v<sub>b</sub> = 30 m/s.</p> Full article ">Figure 11
<p>Topography of ZrO<sub>2</sub>, brushed with a brushing velocity of v<sub>b</sub> = 30 m/s.</p> Full article ">Figure 12
<p>Topography of ZrO<sub>2</sub>, brushed with a brushing velocity of v<sub>b</sub> = 10 m/s.</p> Full article ">Figure 13
<p>Topography of ZrO<sub>2</sub>, measured across the width of an overbrushed profile.</p> Full article ">Figure 14
<p>Material removal depth h<sub>r</sub>, measured across the width of an overbrushed profile.</p> Full article ">Figure 15
<p>Deviating roughness reduction caused by the wear of the brushing tool.</p> Full article ">
15 pages, 15920 KiB  
Article
MARMA: A Mobile Augmented Reality Maintenance Assistant for Fast-Track Repair Procedures in the Context of Industry 4.0
by Fotios K. Konstantinidis, Ioannis Kansizoglou, Nicholas Santavas, Spyridon G. Mouroutsos and Antonios Gasteratos
Machines 2020, 8(4), 88; https://doi.org/10.3390/machines8040088 - 20 Dec 2020
Cited by 65 | Viewed by 6328
Abstract
The integration of exponential technologies in the traditional manufacturing processes constitutes a noteworthy trend of the past two decades, aiming to reshape the industrial environment. This kind of digital transformation, which is driven by the Industry 4.0 initiative, not only affects the individual [...] Read more.
The integration of exponential technologies in the traditional manufacturing processes constitutes a noteworthy trend of the past two decades, aiming to reshape the industrial environment. This kind of digital transformation, which is driven by the Industry 4.0 initiative, not only affects the individual manufacturing assets, but the involved human workforce, as well. Since human operators should be placed in the centre of this revolution, they ought to be endowed with new tools and through-engineering solutions that improve their efficiency. In addition, vivid visualization techniques must be utilized, in order to support them during their daily operations in an auxiliary and comprehensive way. Towards this end, we describe a user-centered methodology, which utilizes augmented reality (AR) and computer vision (CV) techniques, supporting low-skilled operators in the maintenance procedures. The described mobile augmented reality maintenance assistant (MARMA) makes use of the handheld’s camera and locates the asset on the shop floor and generates AR maintenance instructions. We evaluate the performance of MARMA in a real use case scenario, using an automotive industrial asset provided by a collaborative manufacturer. During the evaluation procedure, manufacturer experts confirmed its contribution as an application that can effectively support the maintenance engineers. Full article
(This article belongs to the Section Advanced Manufacturing)
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Figure 1

Figure 1
<p>In the Industry 4.0, maintenance operators are supported by augmented reality (AR)-enabled handhelds.</p> Full article ">Figure 2
<p>Flowchart of the proposed augmented reality method for fast track maintenance procedures.</p> Full article ">Figure 3
<p>Main maintenance interface that includes the layout of the buttons and the progress bar.</p> Full article ">Figure 4
<p>The investigated compressor and its location within the topology of an air-conditioning system of a car.</p> Full article ">Figure 5
<p>Traditional paper-based technical drawing, presenting the correlations among the assembly parts of the compressor.</p> Full article ">Figure 6
<p>Exploded view diagram generated by MARS. The illustration contains the designed subparts of the compressor in the explosion option.</p> Full article ">Figure 7
<p>Demonstration of the maintenance steps of an A/C compressor using MARMA in a mobile device.</p> Full article ">
34 pages, 19929 KiB  
Article
Maintainability of a Gearbox Using Design for Disassembly and Augmented Reality
by Martina Marruganti and Leonardo Frizziero
Machines 2020, 8(4), 87; https://doi.org/10.3390/machines8040087 - 18 Dec 2020
Cited by 3 | Viewed by 3044
Abstract
Environmental impact and recycling have been increasingly frequent topics in recent years. At the same time, the life cycle of products has increasingly become shorter, as the escalating competitive market requires new products in smaller pieces. From this perspective, the recovery of parts [...] Read more.
Environmental impact and recycling have been increasingly frequent topics in recent years. At the same time, the life cycle of products has increasingly become shorter, as the escalating competitive market requires new products in smaller pieces. From this perspective, the recovery of parts and products that are produced in this market system for subsequent reuse when they reach the end of their life cycle is essential. For these reasons, it has become critical that companies re-evaluate their product design with a view to the possible recovery of the parts that comprise their products and to create new products for the market. The following discussion was based on the study of design for disassembly (DfD), which is the analysis of industrial products aimed at optimizing disassembly in terms of time and costs. The application of the DfD to a case study of a gearbox has, among its main objectives, the search for the best disassembly sequence in terms of time and money. During the course of the study, augmented reality (AR) was used. Through the use of the Unity software and Vuforia package, it was possible to bring the gearbox back to AR and then simulate the disassembly sequence in AR. Full article
(This article belongs to the Section Automation and Control Systems)
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Figure 1
<p>Structure of the paper.</p> Full article ">Figure 2
<p>Cost–Benefit–Disassembly Depth Curve.</p> Full article ">Figure 3
<p>Gearbox designed in Solidworks.</p> Full article ">Figure 4
<p>Exploded view.</p> Full article ">Figure 5
<p>Flow chart for the generation of a partial/parallel disassembly sequence.</p> Full article ">Figure 6
<p>Five possible Removal Movements.</p> Full article ">Figure 7
<p>Constraints and Directions: (<b>a</b>) Component E removal ranges respect to component A and B; (<b>b</b>) Limits in the directions between E and A and E and B.</p> Full article ">Figure 8
<p>Diagram for generating geometric product disassembly chart (DGCG).</p> Full article ">Figure 9
<p>DGCG Graph.</p> Full article ">Figure 10
<p>Task Type.</p> Full article ">Figure 11
<p>Instruments Type.</p> Full article ">Figure 12
<p>Image Target: (<b>a</b>) Image Target used for the application of augmented reality (AR); (<b>b</b>) Tracking points recognized on the Image Target used.</p> Full article ">Figure 13
<p>Gearbox in Unity.</p> Full article ">Figure 14
<p>Gearbox in AR.</p> Full article ">Figure 15
<p>Animation of the Game Object.</p> Full article ">Figure 16
<p>Animation of the Gearbox in AR.</p> Full article ">Figure 17
<p>Virtual Button in AR.</p> Full article ">
18 pages, 12659 KiB  
Article
Development of Mechanisms for Automatic Correction of Industrial Complex Tools in the Preprocessing of Laser Welding for Small-Scale and Piece Production Using Computer Vision
by Rodionov Dmitry, Lyukhter Alexander and Prokoshev Valery
Machines 2020, 8(4), 86; https://doi.org/10.3390/machines8040086 - 17 Dec 2020
Cited by 1 | Viewed by 2550
Abstract
This paper is devoted to the development and improvement of mechanisms for the functioning of an automated system for correcting the points of the planned trajectory of the tool of a laser robotic welding complex in the pre-process. Correction of the points of [...] Read more.
This paper is devoted to the development and improvement of mechanisms for the functioning of an automated system for correcting the points of the planned trajectory of the tool of a laser robotic welding complex in the pre-process. Correction of the points of the planned trajectory is carried out in two stages: in the first stage, the focal laser radiation is corrected; in the second stage, the position of the tool is corrected. Correction of the focal laser radiation is carried out in conjunction with the automated focusing of the camera by moving the tool of the industrial complex along its own axis. The functioning of position correction mechanisms is based on methods for recognizing the edges of the gap line to be welded from the image obtained from the charge-coupled device (CCD) camera. The edges of the gap to be welded in the image are segmented using threshold selection. The boundaries of the threshold selection segment are the extreme values of the pixel distribution of the entire image in brightness. For unambiguous recognition of the desired edges based on the segmentation result, the features defining them as a pair of continuous, conditionally parallel lines are formalized. Relative to the recognized pair of edges, the correct position of the planned trajectory point relative to the current position of the welding head is determined. To transfer the correct position, we formalized the calculation model and chose an arbitrary point in the flat image in the workspace laser robotic welding complex, considering the orientation of the tool and the position of the camera. The results obtained made it possible to develop a correction system and successfully test it in the industrial complex. Full article
(This article belongs to the Special Issue Selected Papers from the ICIEAM 2020 Conference)
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Figure 1
<p>Positioning of the LRC-W tool in the process of planning a laser tack with an inaccurately located point of the trajectory relative to the gap between workpieces.</p> Full article ">Figure 2
<p>Scheme of the LRC-W tool.</p> Full article ">Figure 3
<p>Scheme for determining the focal length of laser radiation and CCD camera.</p> Full article ">Figure 4
<p>Scheme of the sequence of operations of the system for correcting the points of the planned trajectory in the preprocessing of laser welding using computer vision systems.</p> Full article ">Figure 5
<p>The structural scheme of a laser robotic welding complex (© 2020 IEEE [<a href="#B30-machines-08-00086" class="html-bibr">30</a>]).</p> Full article ">Figure 6
<p>The authors’ system for the technological preparation of a laser robotic complex.</p> Full article ">Figure 7
<p>Scheme of the process of transferring the project from CAM to the LRC-W industrial complex using the trajectory correction system.</p> Full article ">Figure 8
<p>Scheme of tool movement in the process of automated detection of the focused position of the CCD camera.</p> Full article ">Figure 9
<p>Images captured from a CCD camera during autofocus.</p> Full article ">Figure 10
<p>Result of image blur estimation.</p> Full article ">Figure 11
<p>Images of gap lines between welded workpieces with the LRC-W complex obtained from a CCD camera of HD resolution.</p> Full article ">Figure 12
<p>Histograms of the brightness distribution of pixels in the HSV space of the images in <a href="#machines-08-00086-f011" class="html-fig">Figure 11</a> respectively.</p> Full article ">Figure 12 Cont.
<p>Histograms of the brightness distribution of pixels in the HSV space of the images in <a href="#machines-08-00086-f011" class="html-fig">Figure 11</a> respectively.</p> Full article ">Figure 13
<p>The result of brightness segmentation of the gap of the welded workpieces.</p> Full article ">Figure 13 Cont.
<p>The result of brightness segmentation of the gap of the welded workpieces.</p> Full article ">Figure 14
<p>Result of recognition of the gap based on segmentation results.</p> Full article ">Figure 15
<p>Scheme for determining the segments that belong to the edges of the joint and the parts to be welded (© 2020 IEEE [<a href="#B5-machines-08-00086" class="html-bibr">5</a>]).</p> Full article ">Figure 16
<p>The result of recognition of the gap of welded workpieces in the image obtained from the CCD camera LRC-W with used value parameter recognition: (<b>a</b>) w = 65 <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math>; (<b>b</b>) w = 55 <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>3.5</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>; (<b>c</b>) w = 30 <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo>=</mo> <mn>11</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math>.</p> Full article ">Figure 17
<p>The result of determining the correction point in the case: (<b>a</b>) part gap along the frame; (<b>b</b>) full gap in the frame; (<b>c</b>) arc-shaped gap in the frame.</p> Full article ">Figure 18
<p>Image coordinate system.</p> Full article ">Figure 19
<p>Location of the image base <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">{</mo> <mrow> <msup> <mover accent="true"> <mi>i</mi> <mo>¯</mo> </mover> <mo>′</mo> </msup> <mo>,</mo> <mo> </mo> <msup> <mover accent="true"> <mi>j</mi> <mo>¯</mo> </mover> <mo>′</mo> </msup> <mo>,</mo> <msup> <mover accent="true"> <mi>k</mi> <mo>¯</mo> </mover> <mo>′</mo> </msup> </mrow> <mo stretchy="false">}</mo> </mrow> </mrow> </semantics></math> relative to the base of the LRC-W workspace.</p> Full article ">
19 pages, 6461 KiB  
Article
Neural Network-Based Automated Assessment of Fatigue Damage in Mechanical Structures
by Hassan Alqahtani and Asok Ray
Machines 2020, 8(4), 85; https://doi.org/10.3390/machines8040085 - 16 Dec 2020
Cited by 7 | Viewed by 2208
Abstract
This paper proposes a methodology for automated assessment of fatigue damage, which has been tested and validated with polycrystalline-alloy (Aℓ7075-T6) specimens on an experimental apparatus. Based on an ensemble of time series of ultrasonic test (UT) data, the proposed procedure is [...] Read more.
This paper proposes a methodology for automated assessment of fatigue damage, which has been tested and validated with polycrystalline-alloy (Aℓ7075-T6) specimens on an experimental apparatus. Based on an ensemble of time series of ultrasonic test (UT) data, the proposed procedure is found to be capable of detecting fatigue-damage (at an early stage) in mechanical structures, which is followed by online evaluation of the associated risk. The underlying concept is built upon two neural network (NN)-based models, where the first NN model identifies the feature of the UT data belonging to one of the two classes: undamaged structure and damaged structure, and the second NN model further classifies an identified damaged structure into three classes: low-risk, medium-risk, and high-risk. The input information to the second NN model is the crack tip opening displacement (CTOD), which is computed by the first NN model via linear regression from an ensemble of optical data, acquired from the experiments. Both NN models have been trained by using scaled conjugate gradient algorithms. The results show that the first NN model classifies the energy of UT signals with (up to) 98.5% accuracy, and that the accuracy of the second NN model is 94.6%. Full article
(This article belongs to the Section Automation and Control Systems)
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Figure 1

Figure 1
<p>The fatigue testing apparatus and ancillaries; in (<b>b</b>), all dimensions are in mm.</p> Full article ">Figure 2
<p>Three different types of neural network architecture.</p> Full article ">Figure 3
<p>An artificial neuron.</p> Full article ">Figure 4
<p>The sigmoid function.</p> Full article ">Figure 5
<p>The classification hierarchy.</p> Full article ">Figure 6
<p>The UT signals energy for one experiment, where the <math display="inline"><semantics> <mi mathvariant="bold-italic">x</mi> </semantics></math>-axis presents 19,029 UT energy measurements during each experiment; and the <math display="inline"><semantics> <mi mathvariant="bold-italic">y</mi> </semantics></math>-axis shows the value of measured signal energy.</p> Full article ">Figure 7
<p>The The classification of the first stage, the damage initiation.</p> Full article ">Figure 8
<p>Determining the high-risk region using the crack length and CTOD.</p> Full article ">Figure 9
<p>The average surface roughness, <math display="inline"><semantics> <msub> <mi mathvariant="bold-italic">S</mi> <mi mathvariant="bold-italic">a</mi> </msub> </semantics></math>, measurements of one experiment.</p> Full article ">Figure 10
<p>Illustration of fatigue-damage evolution in a typical test specimen.</p> Full article ">Figure 11
<p>The neural network analysis procedure.</p> Full article ">Figure 12
<p>The linear regression model of the crack length and the crack tip opening displacement.</p> Full article ">Figure 13
<p>Performance of the first and second neural network models for all experiments.</p> Full article ">Figure 13 Cont.
<p>Performance of the first and second neural network models for all experiments.</p> Full article ">Figure 14
<p>Best validation performance for all experiments.</p> Full article ">Figure 14 Cont.
<p>Best validation performance for all experiments.</p> Full article ">Figure 15
<p>Error histogram for all experiments.</p> Full article ">Figure 16
<p>Receiver operating characteristics (ROC) for all experiments.</p> Full article ">
34 pages, 10221 KiB  
Article
Possible Applications of Additive Manufacturing Technologies in Shipbuilding: A Review
by Marcin Ziółkowski and Tomasz Dyl
Machines 2020, 8(4), 84; https://doi.org/10.3390/machines8040084 - 12 Dec 2020
Cited by 68 | Viewed by 10757
Abstract
3D printing conquers new branches of production due to becoming a more reliable and professional method of manufacturing. The benefits of additive manufacturing such as part optimization, weight reduction, and ease of prototyping were factors accelerating the popularity of 3D printing. Additive manufacturing [...] Read more.
3D printing conquers new branches of production due to becoming a more reliable and professional method of manufacturing. The benefits of additive manufacturing such as part optimization, weight reduction, and ease of prototyping were factors accelerating the popularity of 3D printing. Additive manufacturing has found its niches, inter alia, in automotive, aerospace and dentistry. Although further research in those branches is still required, in some specific applications, additive manufacturing (AM) can be beneficial. It has been proven that additively manufactured parts have the potential to out perform the conventionally manufactured parts due to their mechanical properties; however, they must be designed for specific 3D printing technology, taking into account its limitations. The maritime industry has a long-standing tradition and is based on old, reliable techniques; therefore it implements new solutions very carefully. Besides, shipbuilding has to face very high classification requirements that force the use of technologies that guarantee repeatability and high quality. This paper provides information about current R&D works in the field of implementing AM in shipbuilding, possible benefits, opportunities and threats of implementation. Full article
(This article belongs to the Section Advanced Manufacturing)
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Figure 1
<p>Presentation of cross-sections of composite prints using various reinforcing materials, from the left: carbon fiber, glass fiber, high-strength high-temperature glass fiber and Kevlar [<a href="#B16-machines-08-00084" class="html-bibr">16</a>].</p> Full article ">Figure 2
<p>Bending stress as a function of deformation. On the left, material not continuously reinforced; on the right, with the continuous reinforcement [<a href="#B16-machines-08-00084" class="html-bibr">16</a>].</p> Full article ">Figure 3
<p>Marine supply demand per trade [<a href="#B25-machines-08-00084" class="html-bibr">25</a>].</p> Full article ">Figure 4
<p>Number of companies in top 20 countries [<a href="#B25-machines-08-00084" class="html-bibr">25</a>].</p> Full article ">Figure 5
<p>Number of publications related to searched phrase: “Additive Manufacturing in shipbuilding”, by lens.org (26 November 2020).</p> Full article ">Figure 6
<p>Experience of additive manufacturing (AM) technologies per industry [<a href="#B33-machines-08-00084" class="html-bibr">33</a>].</p> Full article ">Figure 7
<p>Awareness about AM technologies [<a href="#B33-machines-08-00084" class="html-bibr">33</a>].</p> Full article ">Figure 8
<p>Welding robot as the main element of wire arc additive manufacturing (WAAM) printing.</p> Full article ">Figure 9
<p>WAAM prototype.</p> Full article ">Figure 10
<p>Crane hook during the 3D printing process.</p> Full article ">Figure 11
<p>Components made by onboard 3D printing [<a href="#B36-machines-08-00084" class="html-bibr">36</a>].</p> Full article ">Figure 12
<p>Submarine hull made incremental techniques for the US Navy [<a href="#B41-machines-08-00084" class="html-bibr">41</a>].</p> Full article ">Figure 13
<p>Mounting previously used by Wärtsilä personnel [<a href="#B42-machines-08-00084" class="html-bibr">42</a>].</p> Full article ">Figure 14
<p>Strength tests of the new mounting [<a href="#B42-machines-08-00084" class="html-bibr">42</a>].</p> Full article ">Figure 15
<p>The mounting after successful certification was put into operation in Wärtsila workshops [<a href="#B42-machines-08-00084" class="html-bibr">42</a>].</p> Full article ">Figure 16
<p>Models of the designed name plate and the mounting. From the top: name plates, view from the back and front, the mounting and the assembly of all components.</p> Full article ">Figure 17
<p>Photos of the plate and mounting produced in fused deposition modeling (FDM) technology.</p> Full article ">Figure 18
<p>From the left: a 1/4-section view and a full view of assembly showing the essence of the protective cap. Photo of an FDM-printed cap mounted on a bolt.</p> Full article ">Figure 19
<p>Nozzle manufactured by Wärtsilä [<a href="#B56-machines-08-00084" class="html-bibr">56</a>].</p> Full article ">Figure 20
<p>Graphic representation of the benefits of using 3D printing in shipbuilding.</p> Full article ">
20 pages, 7506 KiB  
Article
Inter-Stage Dynamic Performance of an Axial Compressor of a Twin-Shaft Industrial Gas Turbine
by Samuel Cruz-Manzo, Senthil Krishnababu, Vili Panov and Chris Bingham
Machines 2020, 8(4), 83; https://doi.org/10.3390/machines8040083 - 9 Dec 2020
Cited by 3 | Viewed by 3637
Abstract
In this study, the inter-stage dynamic performance of a multistage axial compressor is simulated through a semi-empirical model constructed in the Matlab Simulink environment. A semi-empirical 1-D compressor model developed in a previous study has been integrated with a 0-D twin-shaft gas turbine [...] Read more.
In this study, the inter-stage dynamic performance of a multistage axial compressor is simulated through a semi-empirical model constructed in the Matlab Simulink environment. A semi-empirical 1-D compressor model developed in a previous study has been integrated with a 0-D twin-shaft gas turbine model developed in the Simulink environment. Inter-stage performance data generated through a high-fidelity design tool and based on throughflow analysis are considered for the development of the inter-stage modeling framework. Inter-stage performance data comprise pressure ratio at various speeds with nominal variable stator guide vane (VGV) positions and with hypothetical offsets to them with respect to the gas generator speed (GGS). Compressor discharge pressure, fuel flow demand, GGS and power turbine speed measured during the operation of a twin-shaft industrial gas turbine are considered for the dynamic model validation. The dynamic performance of the axial-compressor, simulated by the developed modeling framework, is represented on the overall compressor map and individual stage characteristic maps. The effect of extracting air through the bleed port in the engine center-casing on transient performance represented on overall compressor map and stage performance maps is also presented. In addition, the dynamic performance of the axial-compressor with an offset in VGV position is represented on the overall compressor map and individual stage characteristic maps. The study couples the fundamental principles of axial compressors and a semi-empirical modeling architecture in a complementary manner. The developed modeling framework can provide a deeper understanding of the factors that affect the dynamic performance of axial compressors. Full article
(This article belongs to the Section Automation and Control Systems)
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Figure 1
<p>Pressure ratio estimated by high-fidelity design tool (HFDT) in overall compressor performance map.</p> Full article ">Figure 2
<p>Estimation of parameter λ from HFDT at design point and 100% ω<sub>max</sub>.</p> Full article ">Figure 3
<p>Comparison between stagewise pressure ratio from the 1-D model and HFDT at design point and 100% ω<sub>max</sub>.</p> Full article ">Figure 4
<p>Comparison between stagewise temperature ratio from the 1-D model and HFDT at design point and 100% ω<sub>max</sub>.</p> Full article ">Figure 5
<p>Representation of 0-D engine model developed in the Simulink environment.</p> Full article ">Figure 6
<p>Interface between 0-D and 1-D compressor models in the Simulink environment.</p> Full article ">Figure 7
<p>Overall modeling architecture for dynamic simulation of compressor performance.</p> Full article ">Figure 8
<p>Normalized gas generator speed (GGS) considered as input in the engine model.</p> Full article ">Figure 9
<p>Compressor discharge pressure with increasing load from 13% to 40% of the maximum load and with no bleed.</p> Full article ">Figure 10
<p>Compressor discharge pressure with increasing load from 26% to 53% of the maximum load and considering bleed.</p> Full article ">Figure 11
<p>Representation of transient compressor response on compressor performance map for 13–40% load with/without bleed air.</p> Full article ">Figure 12
<p>Representation of transient compressor response on compressor performance map for 13–40% load and 26–53% load with bleed air.</p> Full article ">Figure 13
<p>Simulink model for simulation of engine performance with inlet guide vane (IGV) offset position.</p> Full article ">Figure 14
<p>Simulated GGS response for 26–53% load and considering a positive and negative IGV offset of 3 degrees at 53% load.</p> Full article ">Figure 15
<p>Engine model considering a GGS change during offset in IGV position.</p> Full article ">Figure 16
<p>Simulated compressor dynamic response for 26–53% load and considering positive and negative IGV offset of 3 degrees at 53% load.</p> Full article ">Figure 17
<p>Representation of stage performance map.</p> Full article ">Figure 18
<p>Comparison between stage-performance map (stage 8) predicted by HFDT and predicted by 1-D compressor model from 70–100% speed.</p> Full article ">Figure 19
<p>Compressor transient response on the stage characteristic map @ 13–40% load and with/without bleed air, (<b>a</b>) stage 11, (<b>b</b>) stage 2.</p> Full article ">Figure 20
<p>Transient compressor response on the stage characteristic map @ 13–40% load and 26–53% load with bleed air, (<b>a</b>) stage 11, (<b>b</b>) stage 2.</p> Full article ">Figure 21
<p>Simulated compressor dynamic response on stage performance map for 26–53% load and considering positive and negative IGV offset of 3 degrees at 53% load, (<b>a</b>) stage 11, (<b>b</b>) stage 2.</p> Full article ">
16 pages, 6174 KiB  
Article
Design, Simulation, and Preliminary Validation of a Four-Legged Robot
by Stefano Rodinò, Elio Matteo Curcio, Antonio di Bella, Mattia Persampieri, Michele Funaro and Giuseppe Carbone
Machines 2020, 8(4), 82; https://doi.org/10.3390/machines8040082 - 4 Dec 2020
Cited by 13 | Viewed by 5321
Abstract
This paper outlines the design process for achieving a novel four-legged robot for exploration and rescue tasks. This application is also intended as an educational mean for masters’ students aiming at gaining skills in designing and operating a complex mechatronic system. The design [...] Read more.
This paper outlines the design process for achieving a novel four-legged robot for exploration and rescue tasks. This application is also intended as an educational mean for masters’ students aiming at gaining skills in designing and operating a complex mechatronic system. The design process starts with an analysis of the desired locomotion and definition of the main requirements and constraints. Then, the paper focuses on the key design challenges, including analytical/numerical modeling and simulations of kinematic and dynamic performances. Specific attention is addressed to the manufacturing of a proof-of-concept prototype, including mechanical and control hardware, as well as the development of the needed software for an autonomous operation. Preliminary tests were carried out, to validate the main features required by the final prototype, to prove its feasibility and user-friendliness, as well as the effectiveness of this complex mechatronic design task for successfully engaging students towards learning complex theoretical, numerical, and practical skills. Full article
(This article belongs to the Special Issue Latest Trends of Autonomous Aerial and Terrestrial Vehicles for Service Robotics Applications)
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<p>A flowchart of the proposed design procedure.</p> Full article ">Figure 2
<p>Schemes of a leg: (<b>a</b>) kinematic model based on a four-bar linkage (a dotted line shows a feasible motion path of the foot) and (<b>b</b>) main design parameters.</p> Full article ">Figure 3
<p>Comparison of results between direct kinematic model and SimMechanics model.</p> Full article ">Figure 4
<p>Schemes of the proposed leg design: (<b>a</b>) first link mass center, (<b>b</b>) mass centers of links two and three, (<b>c</b>) closing polygon scheme, and (<b>d</b>) mass center of link four.</p> Full article ">Figure 5
<p>A scheme of the external forces acting on a leg.</p> Full article ">Figure 6
<p>Calculated kinetic energies and potential energies for each of the four bodies in the kinematic model of <a href="#machines-08-00082-f004" class="html-fig">Figure 4</a>: (<b>a</b>) kinetic energies for bodies one to four, and (<b>b</b>) potential energies for bodies one to four.</p> Full article ">Figure 7
<p>A plot of a set of input q<sub>1</sub> and q<sub>2</sub> joints’ trajectory used to evaluate the dynamical model: (<b>a</b>) q<sub>1</sub> versus time; (<b>b</b>) q<sub>2</sub> versus time.</p> Full article ">Figure 8
<p>A path described by a point attached to the foot end point, as obtained by the model in <a href="#machines-08-00082-f005" class="html-fig">Figure 5</a>, when using the input variables given in <a href="#machines-08-00082-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 9
<p>Plots of simulation results: (<b>a</b>) actuation force for q<sub>2</sub> joint variable and (<b>b</b>) actuation torque for q<sub>1</sub> joint variable.</p> Full article ">Figure 10
<p>Pictures of the built prototype: (<b>a</b>) full robot and (<b>b</b>) a detail of the built full leg actuation mechanism.</p> Full article ">Figure 11
<p>(<b>a</b>) Inertial measurement unit (IMU) sensor, (<b>b</b>) temperature and humidity sensor, and (<b>c</b>) proximity sensor.</p> Full article ">Figure 12
<p>Prototype of manufacturing phases.</p> Full article ">Figure 13
<p>A logical scheme for the control hardware, motors, and sensors.</p> Full article ">Figure 14
<p>Master–slave communication between the Arduino MEGA and Arduino NANO controllers.</p> Full article ">Figure 15
<p>GUI (Graphical User Interface) for controlling robot and acquiring data.</p> Full article ">Figure 16
<p>A footfall scheme of trotting gait, [<a href="#B8-machines-08-00082" class="html-bibr">8</a>].</p> Full article ">Figure 17
<p>Experimental data during a trotting experiment.</p> Full article ">
15 pages, 4044 KiB  
Article
A Smart Stent for Monitoring Eventual Restenosis: Computational Fluid Dynamic and Finite Element Analysis in Descending Thoracic Aorta
by Betsy D. M. Chaparro-Rico, Fabio Sebastiano and Daniele Cafolla
Machines 2020, 8(4), 81; https://doi.org/10.3390/machines8040081 - 24 Nov 2020
Cited by 9 | Viewed by 4323
Abstract
Even though scientific studies of smart stents are extensive, current smart stents focus on pressure sensors. This paper presents a novel implantable biocompatible smart stent for monitoring eventual restenosis. The device is comprised of a metal mesh structure, a biocompatible and adaptable envelope, [...] Read more.
Even though scientific studies of smart stents are extensive, current smart stents focus on pressure sensors. This paper presents a novel implantable biocompatible smart stent for monitoring eventual restenosis. The device is comprised of a metal mesh structure, a biocompatible and adaptable envelope, and pair-operated ultrasonic sensors for restenosis monitoring through flow velocity. Aside from continuous monitoring of restenosis post-implantation, it is also important to evaluate whether the stent design itself causes complications such as restenosis or thrombosis. Therefore, computational fluid dynamic (CFD) analysis before and after stent implantation were carried out as well as finite element analysis (FEA). The proposed smart stent was put in the descending thoracic section of a virtually reconstructed aorta that comes from a computed tomography (CT) scan. Blood flow velocity showed that after stent implantation, there is not liquid retention or vortex generation. In addition, blood pressures after stent implantation were within the normal blood pressure values. The stress and the factor of safety (FOS) analysis showed that the stress values reached by the stent are very far from the yield strength limit of the materials and that the stent is stiff enough to support the applied loads exported from the CFD results. Full article
(This article belongs to the Special Issue Italian Advances on MMS)
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<p>Proposed smart stent details.</p> Full article ">Figure 2
<p>Proposed smart stent implanted in an aorta artery: (<b>a</b>) full view; (<b>b</b>) zoomed in image of the stent into the aorta.</p> Full article ">Figure 3
<p>Scheme of two ultrasonic sensors that operate in pairs for calculating velocity of the blood flow based on time transit time.</p> Full article ">Figure 4
<p>Computed flow trajectories and velocities for the aorta before stent implantation: (<b>a</b>) full view; (<b>b</b>) zoomed-in image of the place where the stent will be implanted.</p> Full article ">Figure 5
<p>Computed flow trajectories and velocities after stent implantation: (<b>a</b>) full view; (<b>b</b>) zoomed-in image ofthe implanted stent.</p> Full article ">Figure 6
<p>Cross-section velocities: (<b>a</b>) before stent implantation; (<b>b</b>) after stent implantation.</p> Full article ">Figure 7
<p>Blood pressures: (<b>a</b>) Before stent implantation; (<b>b</b>) After stent implantation.</p> Full article ">Figure 8
<p>Computed results from stress analysis.</p> Full article ">Figure 9
<p>Static nodal stress: (<b>a</b>) Nodes position, (<b>b</b>) Nodal stress plot.</p> Full article ">Figure 10
<p>Computed factor of safety (FOS).</p> Full article ">
12 pages, 1727 KiB  
Communication
Combined Optimization Prediction Model of Regional Wind Power Based on Convolution Neural Network and Similar Days
by Yalong Li, Fan Yang, Wenting Zha and Licheng Yan
Machines 2020, 8(4), 80; https://doi.org/10.3390/machines8040080 - 20 Nov 2020
Cited by 13 | Viewed by 2125
Abstract
With the continuous optimization of energy structures, wind power generation has become the dominant new energy source. The strong random fluctuation of natural wind will bring challenges to power system dispatching, so it is necessary to predict wind power. In order to improve [...] Read more.
With the continuous optimization of energy structures, wind power generation has become the dominant new energy source. The strong random fluctuation of natural wind will bring challenges to power system dispatching, so it is necessary to predict wind power. In order to improve the short-term prediction accuracy of regional wind power, this paper proposes a new combination prediction model based on convolutional neural network (CNN) and similar days analysis. Firstly, the least square fitting and batch normalization (BN) are used to preprocess the data, and then the recent historical wind power data set for CNN is established. Secondly, the Pearson correlation coefficient and cosine similarity combination method are utilized to find similar days in the long-term data set, and the prediction model based on similar days is constructed by the weighting method. Finally, based on the particle swarm optimization (PSO) method, a combined forecasting model is established. The results show that the combined model can accurately predict the future short-term wind power curve, and the prediction accuracy is improved to different extents compared to a single method. Full article
(This article belongs to the Section Machines Testing and Maintenance)
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<p>CNN structure diagram.</p> Full article ">Figure 2
<p>Trend comparison of similar days.</p> Full article ">Figure 3
<p>Model structure diagram.</p> Full article ">Figure 4
<p>CNN data set division diagram.</p> Full article ">Figure 5
<p>CNN prediction result at 0:00–4:00 on 6 November 2019.</p> Full article ">Figure 6
<p>Similar day result at 0:00–4:00 on 6 November 2019.</p> Full article ">Figure 7
<p>Predicted results of multiple models at 0:00–4:00 on 6 November 2019.</p> Full article ">
14 pages, 6955 KiB  
Article
Effect of the Ti6Al4V Alloy Track Trajectories on Mechanical Properties in Direct Metal Deposition
by Ivan Erdakov, Lev Glebov, Kirill Pashkeev, Vitaly Bykov, Anastasia Bryk, Vyacheslav Lezin and Liudmila Radionova
Machines 2020, 8(4), 79; https://doi.org/10.3390/machines8040079 - 19 Nov 2020
Cited by 19 | Viewed by 2618
Abstract
The TiAl6V4 alloy is widely used in selective laser melting and direct laser melting. In turn, works devoted to the issue of how the track stacking scheme affects the value of mechanical properties is not enough. The influence of the Ti6Al4V alloy track [...] Read more.
The TiAl6V4 alloy is widely used in selective laser melting and direct laser melting. In turn, works devoted to the issue of how the track stacking scheme affects the value of mechanical properties is not enough. The influence of the Ti6Al4V alloy track trajectories on the microstructure and mechanical properties during direct laser deposition is studied in this article for the first time. The results were obtained on the influence of «parallel» and «perpendicular» technique of laying tracks in direct laser synthesis. All studied samples have a microstructure typical of the hardened two-phase condition titanium. Here, it is shown that the method of laying tracks and the direction of load application during compression testing relative to the location of the tracks leads to a change in the ultimate strength of the Ti-6Al-4V alloy from 1794 to 1910 MPa. The plasticity of the Ti-6Al-4V alloy obtained by direct laser alloying can vary from 21.3 to 33.0% depending on the direction of laying the tracks and the direction of the compression test. The hardness of alloys varies in the range from 409 to 511 HV and depends on the method of laying the tracks and the direction of hardness measurements. Full article
(This article belongs to the Special Issue Selected Papers from the ICIEAM 2020 Conference)
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<p>Laser complex FL-Clad-R-4.</p> Full article ">Figure 2
<p>Determination of powder particle size with a scanning electron microscope.</p> Full article ">Figure 3
<p>Motion tracks of the laser head during powder melting: (<b>a</b>) Sample no. 1, the “parallel” technique; (<b>b</b>) sample no. 2, the “perpendicular” technique.</p> Full article ">Figure 4
<p>Samples obtained by the direct metal deposition (DMD) technology: (<b>a</b>) Sample no. 1, the “parallel” technique; (<b>b</b>) sample no. 2, the “perpendicular” technique.</p> Full article ">Figure 5
<p>Cut-up sketch for the electric discharge sawing to determine mechanical properties (<b>a</b>), obtaining samples for compression testing in mutually perpendicular directions of track formation; (<b>b</b>) obtaining samples for measuring hardness in planes 1, 2, and 3.</p> Full article ">Figure 6
<p>Layout of the tracks in samples for compression tests: (<b>a</b>) “Parallel”; (<b>b</b>) “perpendicular”; (<b>c</b>) “vertical”; (<b>d</b>) “mixed”.</p> Full article ">Figure 7
<p>Microstructure of sample no. 1, the «parallel» technique: (<b>a</b>,<b>b</b>) Direction 1 according to <a href="#machines-08-00079-f005" class="html-fig">Figure 5</a>b; (<b>c</b>,<b>d</b>) direction 2; (<b>e</b>,<b>f</b>) direction 3.</p> Full article ">Figure 8
<p>Microstructure of sample no. 2, the «perpendicular» technique: (<b>a</b>,<b>b</b>) Direction 1 according to <a href="#machines-08-00079-f005" class="html-fig">Figure 5</a>b; (<b>c</b>,<b>d</b>) direction 2; (<b>e</b>,<b>f</b>) direction 3.</p> Full article ">Figure 9
<p>Energy-dispersive X-ray spectroscopy (EDS) mapping of the Ti-6Al-4V alloy samples: (<b>a</b>) Sample no. 1, the “parallel” technique; (<b>b</b>) sample no. 1, the “parallel” technique without pores; (<b>c</b>) sample no. 2, the “perpendicular” technique at times; (<b>d</b>) sample no. 2, the “perpendicular” technique without pores.</p> Full article ">Figure 10
<p>Compression diagrams of samples with different track layouts: (<b>a</b>) “Parallel”; (<b>b</b>) 6—“perpendicular”; (<b>c</b>) “vertical”; (<b>d</b>) “mixed”; 1,2,3—sample test number.</p> Full article ">
14 pages, 6740 KiB  
Article
Investigation of Finishing Aluminum Alloy A5052 Using the Magnetic Abrasive Finishing Combined with Electrolytic Process
by Baijun Xing and Yanhua Zou
Machines 2020, 8(4), 78; https://doi.org/10.3390/machines8040078 - 19 Nov 2020
Cited by 14 | Viewed by 3098
Abstract
The magnetic abrasive finishing combined with electrolytic (EMAF) process was proposed to improve the finishing efficiency of the traditional magnetic abrasive finishing (MAF) process. Since the EMAF process contains electrolysis reactions, the machining mechanism of processing different metal is different. In this paper, [...] Read more.
The magnetic abrasive finishing combined with electrolytic (EMAF) process was proposed to improve the finishing efficiency of the traditional magnetic abrasive finishing (MAF) process. Since the EMAF process contains electrolysis reactions, the machining mechanism of processing different metal is different. In this paper, a series of experiments were conducted to explore the feasibility of using the compound processing tool to finish aluminum alloy A5052, and to preliminary explore the machining mechanism. Surface roughness and material removal are used to evaluate the finishing effect and the finishing efficiency, respectively. The EMAF processing current curve is used to evaluate and analyze the EMAF process. The feasibility of the EMAF processing is proved by the analysis of simulations and the experimental results. Finally, through a series of exploration experiments and parameter optimization experiments, the main conclusions are as follows: (1) Compared with the traditional MAF process, when finishing the surface of aluminum alloy A5052 by the same compound processing tool and at the same experimental conditions (except the electrolysis conditions), the EMAF process, which includes electrolysis reactions, can achieve higher finishing efficiency. (2) In this study, when the working gap is 1 mm and the concentration of NaNO3 solution is 15%, the recommended processing voltage is about 3.4 V. Full article
(This article belongs to the Special Issue Advanced Autonomous Machines and Designs)
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<p>Schematic of magnetic abrasive finishing combined with electrolytic process (EMAF) processing principle.</p> Full article ">Figure 2
<p>Schematic of electrolysis reactions during the EMAF process.</p> Full article ">Figure 3
<p>External view of experimental setup.</p> Full article ">Figure 4
<p>Schematic of current measuring and recording set up.</p> Full article ">Figure 5
<p>Simulation of magnetic induction. (<b>a</b>) magnetic induction on the surface of processing tools and (<b>b</b>) magnetic induction on the surface of the workpiece (working gap 1 mm).</p> Full article ">Figure 6
<p>Experimental results of electrolysis in EMAF process. (<b>a</b>) Changes of surface roughness during processing and (<b>b</b>) changes of material removal during processing.</p> Full article ">Figure 7
<p>MAF process experimental results (330 μm electrolytic iron powder).</p> Full article ">Figure 8
<p>MAF process experimental results (149 μm electrolytic iron powder).</p> Full article ">Figure 9
<p>EMAF process experimental results.</p> Full article ">Figure 10
<p>Observed surface by microscope after finishing. (<b>a</b>) Finished surface after EMAF processing; (<b>b</b>) finished surface after Stage 1; and (<b>c</b>) finished surface after Stage 2.</p> Full article ">Figure 11
<p>Optimization experiment of EMAF processing parameters.</p> Full article ">Figure 12
<p>Processing current curves of electrolysis reactions in EMAF process. (<b>a</b>) The current curve when processing voltage is 4 V; (<b>b</b>) the current curve when processing voltage is 5 V; and (<b>c</b>) the current curve when processing voltage is 6 V.</p> Full article ">Figure 12 Cont.
<p>Processing current curves of electrolysis reactions in EMAF process. (<b>a</b>) The current curve when processing voltage is 4 V; (<b>b</b>) the current curve when processing voltage is 5 V; and (<b>c</b>) the current curve when processing voltage is 6 V.</p> Full article ">Figure 13
<p>Processing current curves of EMAF process. (<b>a</b>) the current curve when processing voltage is 3.4 V; (<b>b</b>) the current curve when processing voltage is 3.6 V; (<b>c</b>) the current curve when processing voltage is 3.8 V; and (<b>d</b>) the current curve when processing voltage is 4.0 V.</p> Full article ">Figure 14
<p>3D topography of finished surfaces. (<b>a</b>) the 3D topography when processing voltage is 4.0 V; (<b>b</b>) the 3D topography when processing voltage is 3.8 V; (<b>c</b>) the 3D topography when processing voltage is 3.6 V; and (<b>d</b>) the 3D topography when processing voltage is 3.4 V.</p> Full article ">
14 pages, 6025 KiB  
Article
Analysis of Overturning and Vibration during Field Operation of a Tractor-Mounted 4-Row Radish Collector toward Ensuring User Safety
by Milon Chowdhury, Md Nafiul Islam, Md Zafar Iqbal, Sumaiya Islam, Dae-Hyun Lee, Dae-Geon Kim, Hyeon-Jong Jun and Sun-Ok Chung
Machines 2020, 8(4), 77; https://doi.org/10.3390/machines8040077 - 19 Nov 2020
Cited by 23 | Viewed by 3458
Abstract
The overturning stability and vibration of upland crop machinery under development are important issues for analysis because farms for upland crops are usually uneven, which may cause work-related fatalities, and vibration affects user comfort and reduces the durability of components. In this study, [...] Read more.
The overturning stability and vibration of upland crop machinery under development are important issues for analysis because farms for upland crops are usually uneven, which may cause work-related fatalities, and vibration affects user comfort and reduces the durability of components. In this study, the overturning stability and vibration of a tractor-mounted radish collector were investigated to ensure safety during radish collection. To analyze lateral stability, the center of gravity (CG) of the tractor-mounted radish collector system was calculated mathematically. Then, a simulation was performed to determine the lateral overturning angles at different folding positions of the radish conveyor belt and load conditions, and the results were validated through tests. Vibration sensors were used to measure the vibration levels and the power spectrum density (PSD) was obtained to check the cyclic apparatuses of the major frequencies. The load conditions, different conveyor speeds, and locations were considered as factors affecting the vibration levels. Considering the physical parameters of the tractor–collector system, the analytical overturning angle was 30.5°. The average overturning angle difference between the simulation and validation was 5°, and the difference between loaded and unloaded conditions was 2°. For 0, 45, and 90° folding positions of the conveyor belt, overturning angles increased and varied from 0.5 to 1°. The vibration level was greater under the unloaded conditions and increased with an increase in the conveyor speed. Vibrations under the loaded condition (0.37~0.48 ms−2) satisfied the ISO (International Organization for Standardization) standard (except the first conveyor belt). According to the PSD analysis, high magnitude peaks (>25 dB) appeared frequently in all directions, which indicates a high possibility of damage to the first conveyor belt. This study provides useful information for improving the safety and durability of agricultural machinery for uneven and sloped field conditions. Full article
(This article belongs to the Section Machines Testing and Maintenance)
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<p>3-dimensional model of the tractor-mounted radish collector system showing the major components: (<b>a</b>) tractor, (<b>b</b>) second conveyor motor, (<b>c</b>) second conveyor belt, (<b>d</b>) stem cutter (<b>e</b>) radish, (<b>f</b>) rubber bit, (<b>g</b>) first conveyor belt, (<b>h</b>) furrow guide, (<b>i</b>) collector-base, (<b>j</b>) first conveyor motor, (<b>k</b>) safety frame, and (<b>l</b>) hanging rods of the radish collecting bag.</p> Full article ">Figure 2
<p>Schematic diagram for center of gravity (CG) determination of the tractor–collector system under normal and inclined conditions.</p> Full article ">Figure 3
<p>Lateral overturning stability: (<b>a</b>) simulation and (<b>b</b>) validation of the tractor–collector system at 0° folding position of the conveyor belt and without load.</p> Full article ">Figure 4
<p>Positions of the vibration sensors in the radish collector during the field test.</p> Full article ">Figure 5
<p>Results of the transverse lateral overturning with 10° increment of the deflection angle.</p> Full article ">Figure 6
<p>Lateral overturning angles of the tractor–collector system: (<b>a</b>) simulated overturning angles under unloaded and loaded conditions, and (<b>b</b>) angle difference between simulation and validation.</p> Full article ">Figure 7
<p>Maximum vibration levels in different positions of the radish collector and speeds of the conveyor belts during (<b>a</b>) unloaded condition and (<b>b</b>) loaded condition.</p> Full article ">Figure 8
<p>Power spectrum density (PSD) analysis of the measured vibration on the first conveyor belt for 0.10, 0.16, and 0.20 ms<sup>−1</sup> conveyor speeds and loaded condition.</p> Full article ">
24 pages, 7389 KiB  
Article
Multibody-Based Piano Action: Validation of a Haptic Key
by Sébastien Timmermans, Bruno Dehez and Paul Fisette
Machines 2020, 8(4), 76; https://doi.org/10.3390/machines8040076 - 17 Nov 2020
Cited by 6 | Viewed by 4324
Abstract
A piano key prototype actuated by a custom-made linear actuator is proposed to enhance the touch of digital pianos by reproducing the force feedback of an acoustic piano action. This paper presents the design and the validation of the haptic device. The approach [...] Read more.
A piano key prototype actuated by a custom-made linear actuator is proposed to enhance the touch of digital pianos by reproducing the force feedback of an acoustic piano action. This paper presents the design and the validation of the haptic device. The approach exploits a multibody model to compute the action dynamics and the corresponding force on the key in real time. More specifically, a grand piano model that includes the five action bodies, its geometry and the specific force laws, is computed in the haptic device. A presizing step along with Finite Element Method (FEM) analysis produced an especially made actuator satisfying the design requirements, in particular the highly dynamic nature of the force to be transmitted. Force peaks, up to 50 (N) in less than 20 (ms), are reachable with low power consumption. Compared to previous solutions: (i) the key physical characteristics are preserved; (ii) the feedback is based on a real-time multibody model that is easily configurable and interchangeable; (iii) an experimental validation of the actuator within the prototype is developed and demonstrates its feasibility. The results confirm that the voice coil can produce suitable haptic feedback. In particular, rendering a grand piano action within the device shows promising haptic force profiles. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Grand piano action and its Computer Aided Design (CAD) replica.</p> Full article ">Figure 2
<p>Haptic force feedback principle.</p> Full article ">Figure 3
<p>View of the haptic key prototype.</p> Full article ">Figure 4
<p>Detailed view of the prototype elements: (1) Actuator; (2) Key; (3) Coil support; (4) Coil; (5) Spacers; (6) Magnets on steel walls.</p> Full article ">Figure 5
<p>Multibody model elements for a double escapement piano action: bodies, joints, stops, springs.</p> Full article ">Figure 6
<p>Position sensor measurements: one slow movement.</p> Full article ">Figure 7
<p>Position sensor measurements: several fast up-and-down movements.</p> Full article ">Figure 8
<p>Components of the actuator: (1) Coil; (2) Superior PMs; (3) Inferior PMs; (4) Iron pieces; (5) Air gap. Red and blue colors on the magnets correspond to opposite magnetization direction.</p> Full article ">Figure 9
<p>Actuator side and front views: parameters used during optimisation.</p> Full article ">Figure 10
<p>Force profiles <math display="inline"><semantics> <msub> <mi>F</mi> <mi mathvariant="italic">mod</mi> </msub> </semantics></math> considered for the presizing.</p> Full article ">Figure 11
<p>Magnetic field amplitude (T) for different iron pieces thicknesses, 3D view.</p> Full article ">Figure 12
<p>Voltage decomposition according to (<a href="#FD4-machines-08-00076" class="html-disp-formula">4</a>) for the <span class="html-italic">soft</span> force profile.</p> Full article ">Figure 13
<p>Results for the two considered force profiles using FEM simulations.</p> Full article ">Figure 14
<p>Coil current density during the two profiles. RMS value is computed over the duration considered.</p> Full article ">Figure 15
<p>Force-current relation: the slope corresponds to <math display="inline"><semantics> <msub> <mi>K</mi> <mi>f</mi> </msub> </semantics></math>.</p> Full article ">Figure 16
<p>Force-position relation, for a constant input current.</p> Full article ">Figure 17
<p>Key position applied for actuator validation.</p> Full article ">Figure 18
<p>Measured actuator coil force compared to the target.</p> Full article ">Figure 19
<p>Key position applied for the validation with piano action model.</p> Full article ">Figure 20
<p>Vertical key velocity and acceleration during the validation.</p> Full article ">Figure 21
<p>Measured and targeted forces during validation with the piano action model.</p> Full article ">Figure 22
<p>Measurements of the force felt by the pianist <math display="inline"><semantics> <msub> <mi>F</mi> <mrow> <mi>h</mi> <mi>a</mi> <mi>p</mi> <mi>t</mi> <mi>i</mi> <mi>c</mi> </mrow> </msub> </semantics></math> through an external linear actuator for the Renner<sup>®</sup> demonstrator (<b>up</b>) and the haptic prototype (<b>bottom</b>).</p> Full article ">Figure 23
<p>Haptic force measured on the Renner<sup>®</sup> demonstrator of <a href="#machines-08-00076-f001" class="html-fig">Figure 1</a> and on the prototype of <a href="#machines-08-00076-f003" class="html-fig">Figure 3</a>.</p> Full article ">
17 pages, 26223 KiB  
Article
Investigation on Finishing Characteristics of Magnetic Abrasive Finishing Process Using an Alternating Magnetic Field
by Huijun Xie and Yanhua Zou
Machines 2020, 8(4), 75; https://doi.org/10.3390/machines8040075 - 16 Nov 2020
Cited by 12 | Viewed by 4067
Abstract
The magnetic abrasive finishing (MAF) process is an ultra-precision surface finishing process. In order to further improve the finishing efficiency and surface quality, the MAF process using an alternating magnetic field was proposed in the previous research, and it was proven that the [...] Read more.
The magnetic abrasive finishing (MAF) process is an ultra-precision surface finishing process. In order to further improve the finishing efficiency and surface quality, the MAF process using an alternating magnetic field was proposed in the previous research, and it was proven that the alternating magnetic field has advantages compared with the static magnetic field. In order to further develop the process, this study investigated the effect on finishing characteristics when the alternating current waveform is a square wave. The difference between the fluctuation behavior of the magnetic cluster in two alternating magnetic fields (sine wave and square wave) is observed and analyzed. Through analysis, it can be concluded that the use of a square wave can make the magnetic cluster fluctuate faster, and as the size of the magnetic particles decreases, the difference between the magnetic cluster fluctuation speed of the two waveforms is greater. The experimental results show that the surface roughness of SUS304 stainless steel plate improves from 328 nm Ra to 14 nm Ra within 40 min. Full article
(This article belongs to the Special Issue Advanced Autonomous Machines and Designs)
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Figure 1

Figure 1
<p>Schematic of processing principle.</p> Full article ">Figure 2
<p>External view of the experimental setup.</p> Full article ">Figure 3
<p>Magnetic flux density measurement.</p> Full article ">Figure 4
<p>Schematic diagram of magnetic cluster fluctuation. (<b>a</b>) The highest position; (<b>b</b>) The lowest position.</p> Full article ">Figure 5
<p>The lowest position and the highest position in the fluctuation period of the magnetic cluster. (<b>a</b>) Sin-AC, 330 μm; (<b>b</b>) S-AC, 330 μm; (<b>c</b>) Sin-AC, 149 μm; (<b>d</b>) S-AC, 149 μm; (<b>e</b>) Sin-AC, 75 μm; (<b>f</b>) S-AC, 75 μm.</p> Full article ">Figure 6
<p>Current waveform diagram. (<b>a</b>) sin-AC, 1Hz; (<b>b</b>) S-AC, 1Hz; (<b>c</b>) DC.</p> Full article ">Figure 7
<p>The effect of current waveform on surface roughness and material removal. (Magnetic particles: 149 μm, frequency: 1 Hz, abrasive particles: WA#8000, rotational speed: 350 rpm).</p> Full article ">Figure 8
<p>The change curve of magnetic flux density with time. (<b>a</b>) Sin-AC; (<b>b</b>) S-AC.</p> Full article ">Figure 9
<p>The effect of magnetic particles size on surface roughness and material removal. (Current waveform: S-AC, frequency: 1 Hz, abrasive particles: WA#8000, rotational speed: 350 rpm).</p> Full article ">Figure 10
<p>Photos of the workpieces. (<b>a</b>) Magnetic particles: 75 μm; (<b>b</b>) Magnetic particles: 149 μm; (<b>c</b>) Magnetic particles: 330 μm.</p> Full article ">Figure 10 Cont.
<p>Photos of the workpieces. (<b>a</b>) Magnetic particles: 75 μm; (<b>b</b>) Magnetic particles: 149 μm; (<b>c</b>) Magnetic particles: 330 μm.</p> Full article ">Figure 11
<p>The amount of material removal per unit area (Q).</p> Full article ">Figure 12
<p>The effect of current frequency on surface roughness and material removal. (Magnetic particles: 149 μm, current waveform: S-AC, abrasive particles: WA#8000, rotational speed: 350 rpm).</p> Full article ">Figure 13
<p>The effect of abrasive particles size on surface roughness and material removal. (Magnetic particles: 149 μm, current waveform: S-AC, frequency: 1 Hz, rotational speed: 350 rpm).</p> Full article ">Figure 14
<p>SEM images of the workpiece surface and abrasive particles. (<b>a</b>) Workpiece surface; (<b>b</b>) Abrasive particles.</p> Full article ">Figure 14 Cont.
<p>SEM images of the workpiece surface and abrasive particles. (<b>a</b>) Workpiece surface; (<b>b</b>) Abrasive particles.</p> Full article ">Figure 15
<p>The Photographs of the workpiece surface after finishing (White Light Interferometers). (<b>a</b>) WA#6000; (<b>b</b>) WA#8000; (<b>c</b>) WA#20000.</p> Full article ">Figure 16
<p>The effect of rotational speed on surface roughness and material removal. (Magnetic particles: 149 μm, current waveform: S-AC, frequency: 1 Hz, abrasive particles: WA#8000).</p> Full article ">Figure 17
<p>3D photographs of the workpiece surface before and after finishing. (<b>a</b>) 350 rpm; (<b>b</b>) 450 rpm; (<b>c</b>) 550 rpm.</p> Full article ">Figure 17 Cont.
<p>3D photographs of the workpiece surface before and after finishing. (<b>a</b>) 350 rpm; (<b>b</b>) 450 rpm; (<b>c</b>) 550 rpm.</p> Full article ">
19 pages, 1239 KiB  
Article
Let’s Make Ball Balancing Great Again: Why You Should Use Temporary Speed Reduction
by Gabriël Van De Velde, Björn Verrelst, Dirk Lefeber and Patrick Guillaume
Machines 2020, 8(4), 74; https://doi.org/10.3390/machines8040074 - 15 Nov 2020
Viewed by 2305
Abstract
Automatic ball balancing is a technique adopted in rotordynamics to reduce unknown rotor unbalance automatically. This technique sounds appealing as it can ease a panoply of balancing issues considerably. The presence of stiction, however, scatters consistent qualitative balancing and led to a limited [...] Read more.
Automatic ball balancing is a technique adopted in rotordynamics to reduce unknown rotor unbalance automatically. This technique sounds appealing as it can ease a panoply of balancing issues considerably. The presence of stiction, however, scatters consistent qualitative balancing and led to a limited implementation in the industry. Temporary speed reduction, a recent technique, could be used as a countermeasure for the stiction-induced scattering. Presented in this paper is an in-depth study detailing how the technique should be implemented to guarantee effective balancing. By analysing a rotordynamic model of the Jeffcott kind, the influence of a multitude of parameters is studied such as the initial mass positions, the initial unbalance, the adopted speed profile, shaft damping, stiction and the speed reduction plateau of the adopted speed reduction strategy. The main findings of the study are that the adverse effects of stiction can be contained considerably using the speed reduction technique, especially in the under-excited range where a ball balancer behaves poorly when adopting a standard run-up profile. Finally, the speed plateau of the speed reduction technique should be selected carefully, preferably accounting for stiction, shaft damping and even more so the initial unbalance. Full article
(This article belongs to the Section Automation and Control Systems)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Fundamental sketch of a one-ball balancer with emphasis on forces acting on balancing mass I.</p> Full article ">Figure 2
<p>Coordinate definition for the Jeffcott rotor with a concentrically mounted ball balancer.</p> Full article ">Figure 3
<p>Standardized speed profile, nominal speed = 167 Hz. Total simulation time is 90 s.</p> Full article ">Figure 4
<p>A single run-up following the aforementioned speed profile illustrating the temporal speed reduction (TSR) technique.</p> Full article ">Figure 5
<p>Probability density function of the residual unbalance for an initial unbalance <span class="html-italic">G</span>20 (dashed line), standard (grey) and TSR (black) procedure.</p> Full article ">Figure 6
<p>Comparison of the balancing outcome of the standard (STD) and TSR procedure.</p> Full article ">Figure 7
<p>Lines: Influence of initial unbalance on residual unbalance following the standard configuration of <a href="#machines-08-00074-t001" class="html-table">Table 1</a> and afore-stated speed profile. Area: Valid initial unbalance range for a given tolerance class.</p> Full article ">Figure 8
<p>Immobility in function of rotational speed for an initial unbalance of <math display="inline"><semantics> <mrow> <mi>G</mi> <mn>20</mn> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>Influence of the speed profile on balancing range. A slower speed profile tends to mimic TSR. Intermittent vibrations when crossing resonance however annihilate this improvement.</p> Full article ">Figure 10
<p>Influence of damping and rolling friction on balance immobility for a nominal initial unbalance of <math display="inline"><semantics> <mrow> <mi>G</mi> <mn>20</mn> </mrow> </semantics></math>. Damping <math display="inline"><semantics> <mrow> <msub> <mi>c</mi> <mi>r</mi> </msub> <mo>=</mo> <mrow> <mo>{</mo> <mn>0.5</mn> <mo>;</mo> <mn>0.6</mn> <mo>;</mo> <mn>1</mn> <mo>;</mo> <mn>1.4</mn> <mo>}</mo> </mrow> </mrow> </semantics></math>. Friction <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mi>r</mi> </msub> <mo>=</mo> <mrow> <mo>{</mo> <mn>0.25</mn> <mo>;</mo> <mn>0.5</mn> <mo>;</mo> <mn>1</mn> <mo>;</mo> <mn>2</mn> <mo>;</mo> <mn>5</mn> <mo>}</mo> </mrow> </mrow> </semantics></math>.</p> Full article ">Figure 11
<p>An increase of friction leads to a global deterioration of balancing capabilities for the STD and TSR technique. (<b>a</b>) STD, (<b>b</b>) TSR. Sweep-up and haziness of the balancing outcomes occur respectively for STD and TSR as stability is only guaranteed in a narrow upper part of the adopted speed profile for a low initial unbalance range.</p> Full article ">Figure 12
<p>An increase of damping leads to a global deterioration of balancing capabilities for the STD and TSR technique. (<b>a</b>) STD, (<b>b</b>) TSR.</p> Full article ">Figure 13
<p>Effect of the lower speed plateau on the global balancing outcomes for <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mrow> <mi>i</mi> <mi>n</mi> <mi>i</mi> </mrow> </msub> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mi>r</mi> </msub> <mo>=</mo> <msub> <mi>c</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.</p> Full article ">Figure 14
<p>Effect of the initial unbalance on the valid lower speed plateau range, <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mi>r</mi> </msub> <mo>=</mo> <msub> <mi>c</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. The ideal speed plateau is <math display="inline"><semantics> <mrow> <mn>1.02</mn> </mrow> </semantics></math>.</p> Full article ">Figure 15
<p>Effect of the initial unbalance on the valid lower speed plateau range, <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>1</mn> <mo>,</mo> <msub> <mi>c</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math>. The ideal speed plateau is <math display="inline"><semantics> <mrow> <mn>1.03</mn> </mrow> </semantics></math>.</p> Full article ">Figure 16
<p>The balancing outcomes for <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>1</mn> <mo>,</mo> <msub> <mi>c</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math> whereby the lower speed plateau was altered from <math display="inline"><semantics> <mrow> <mn>1.06</mn> </mrow> </semantics></math> (standard) to <math display="inline"><semantics> <mrow> <mn>1.03</mn> </mrow> </semantics></math> (ideal). The STD balancing outcome is presented as well for illustration purposes.</p> Full article ">
22 pages, 3138 KiB  
Article
Calculating Power Parameters of Rolling Mill Based on Model of Deformation Zone with Four-Roll Passes
by Marina N. Samodurova, Olga I. Karandaeva, Vadim R. Khramshin and Ivan V. Liubimov
Machines 2020, 8(4), 73; https://doi.org/10.3390/machines8040073 - 13 Nov 2020
Cited by 8 | Viewed by 10006
Abstract
Making “digital twins” for rolling processes and mill equipment should begin with the development of mathematical models of the deformation zone. The deformation zone of two-high flat mill rolling have been studied in detail, relevant models are available in many academic papers. However, [...] Read more.
Making “digital twins” for rolling processes and mill equipment should begin with the development of mathematical models of the deformation zone. The deformation zone of two-high flat mill rolling have been studied in detail, relevant models are available in many academic papers. However, the same cannot be said about the most complex deformation zones in stands with multi-roll gauge. Therefore, the task of their reliable mathematical description is of immediate interest. The development of mathematical models is necessary for the design of new wire mills and rolling-drawing units. The combination of rolling in stands with multi-roll gauge and drawing is a promising direction in the production of wire from difficult-to-form steels and alloys. Digital models for pressure-based metal treatment are also necessary for calculating the rolling-mill power parameters during the development of new assortments at the operating mills. The models of deformation zones present the basis for developing the multivariable control systems of process conditions of continuous mills. This research is devoted to the study of the deformation zone and the development of a procedure for calculating the power parameters of rolling in a stand with four-roll passes. The solution of these challenges is given using the example of an operating five-stand wire mill. The authors analysed the known analytical dependencies for calculating the rolling mill force and torque. A mathematical model of the deformation zone and a program for calculating the power parameters have been developed. The paper compares the results obtained from calculations based on analytical dependence and on modelling. A comparison with the experimental parameters obtained at the mill is given. The authors assess the feasibility of using the known formulas and analyse the impact of the front and rear tensions on the power parameters of rolling mill. The problem of developing an automatic tension control system for continuous mills with multi-roll groove is substantiated. Full article
(This article belongs to the Special Issue Selected Papers from the ICIEAM 2020 Conference)
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Figure 1

Figure 1
<p>Layout for rolling a square-shaped stock material: (<b>a</b>) in four-roll pass; (<b>b</b>) in a stand with two three-roll passes.</p> Full article ">Figure 2
<p>Production equipment layout diagram: 1, 2—Decoilers (reel or coil); 3—Stretcher/Feeder; 4—Welding Unit; 5—Accumulator; 6—Inductor; 7—Mill Stands; 8—Actuating Units; 9—Cooling Sections; 10—Winder.</p> Full article ">Figure 3
<p>Diagram of forces acting on the elementary volume in the backward slip zone.</p> Full article ">Figure 4
<p>Explanations for the derivation of equations for <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mi>x</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>t</mi> <mi>g</mi> <msub> <mi>α</mi> <mi>x</mi> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 5
<p>Explanations for the derivation of equations for <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mi>x</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>t</mi> <mi>g</mi> <msub> <mi>α</mi> <mi>x</mi> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 6
<p>Structural diagram of a mathematical model of a continuous five-stand mill with four-roll passes.</p> Full article ">Figure 7
<p>Experimental research at four-roll pass rolling: dependence of rolling pressure on the rolls as a function of the friction coefficient (<b>a</b>), rolling rate (<b>b</b>), drawing down (<b>c</b>), temperature (<b>d</b>); curve 1—steel rolling 70; curve 2—steel R6M5 rolling; curve 3—steel KhI8N9T rolling</p> Full article ">Figure 8
<p>Calculated and experimental dependencies of pressure (<b>a</b>), flow (<b>b</b>) and torque (<b>c</b>) from the draw-down operation when rolling a wire rod with 11 mm diameter.</p> Full article ">Figure 9
<p>Calculated and experimental dependences of pressure (<b>a</b>), torque (<b>b</b>) and flow (<b>c</b>) from the front tension.</p> Full article ">Figure 10
<p>Dependencies similar to <a href="#machines-08-00073-f009" class="html-fig">Figure 9</a>, (<b>a</b>), torque (<b>b</b>) and flow (<b>c</b>) from rear tension.</p> Full article ">
11 pages, 1126 KiB  
Letter
Limited-Position Set Model-Reference Adaptive Observer for Control of DFIGs without Mechanical Sensors
by Mohamed Abdelrahem, Christoph M. Hackl and Ralph Kennel
Machines 2020, 8(4), 72; https://doi.org/10.3390/machines8040072 - 12 Nov 2020
Cited by 13 | Viewed by 2103
Abstract
Operations of the doubly-fed induction generators (DFIGs) without mechanical sensors are highly desirable in order to enhance the reliability of the wind generation systems. This article proposes a limited-position set model-reference adaptive observer (LPS-MRAO) for control of DFIGs in wind turbine systems (WTSs) [...] Read more.
Operations of the doubly-fed induction generators (DFIGs) without mechanical sensors are highly desirable in order to enhance the reliability of the wind generation systems. This article proposes a limited-position set model-reference adaptive observer (LPS-MRAO) for control of DFIGs in wind turbine systems (WTSs) without mechanical sensors, i.e., without incremental encoders or speed transducers. The concept of of the developed LPS-MRAO is obtained from the finite-set model predictive control (FS-MPC). In the proposed LPS-MRAO, an algorithm is presented in order to give a constant number of angles for the rotor position of the DFIG. By using these angles, a certain number of rotor currents can be predicted. Then, a new quality function is defined to find the best angle of the rotor. In the proposed LPS-MRAO, there are not any gains to tune like the classical MRAO, where a proportional-integral is used and must be tuned. Finally, the proposed LPS-MRAO and classical one are experimentally implemented in the laboratory and compared at various operation scenarios and under mismatches in the parameters of the DFIG. The experimental results illustrated that the estimation performance and robustness of the proposed LPS-MRAO are better than those of the classical one. Full article
(This article belongs to the Special Issue Design and Control of Rotating Electrical Machines)
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Figure 1

Figure 1
<p>Schematic-diagram of the VOC technique for doubly-fed induction generators (DFIGs) with model-reference adaptive observer (MRAO) in wind turbine systems.</p> Full article ">Figure 2
<p>Block diagram of the traditional MRAO for control of DFIGs without incremental encoders.</p> Full article ">Figure 3
<p>Block diagram of the proposed limited-position set (LPS)-MRAO for control of DFIGs without mechanical sensors.</p> Full article ">Figure 4
<p>The used test bench to validate the proposed LPS-MRAO.</p> Full article ">Figure 5
<p>Experimental results at changes of the rotation speed of the rotor: (<b>a</b>) LPS-MRAO, and (<b>b</b>) traditional MRAO.</p> Full article ">Figure 6
<p>Experimental results at variations of the electro-magnetic torque of the DFIG <math display="inline"><semantics> <msubsup> <mi>T</mi> <mi>e</mi> <mo>∗</mo> </msubsup> </semantics></math>: (<b>a</b>) LPS-MRAO, and (<b>b</b>) traditional MRAO.</p> Full article ">Figure 7
<p>Experimental results at variations of the DFIG stator resistance <math display="inline"><semantics> <msub> <mi>R</mi> <mi>s</mi> </msub> </semantics></math>: (<b>a</b>) LPS-MRAO, and (<b>b</b>) traditional MRAO.</p> Full article ">Figure 8
<p>Experimental results at variations of the DFIG stator inductance <math display="inline"><semantics> <msub> <mi>L</mi> <mi>s</mi> </msub> </semantics></math>: (<b>a</b>) LPS-MRAO, and (<b>b</b>) traditional MRAO.</p> Full article ">
14 pages, 7481 KiB  
Article
Synchronization of Auxiliary Mechanisms and Main Electric Drive of the Pipe Cold-Rolling Mill. Complete Solution
by Vsevolod Ostrouhov, Dmitry Sychev and Maxim Grigorev
Machines 2020, 8(4), 71; https://doi.org/10.3390/machines8040071 - 5 Nov 2020
Cited by 24 | Viewed by 2950
Abstract
This article deals with installations with complex and nonstandard executive instrument movement. Having analyzed the technical implementation and operational features of cold-rolling pipe mills, the research team formulated the problem of synthesizing electric drives of auxiliary mechanisms. It is shown that the conditions [...] Read more.
This article deals with installations with complex and nonstandard executive instrument movement. Having analyzed the technical implementation and operational features of cold-rolling pipe mills, the research team formulated the problem of synthesizing electric drives of auxiliary mechanisms. It is shown that the conditions for choosing a mechanical converter are associated with the oscillation of the processes of the electric drive system. The finite element method and the gradient descent method are used for structural analysis of solids and electromagnetic calculations. The data of the specific cost of semiconductor converters were analyzed using a linear least-squares regression technique. The advantages of a synchronous reluctance motor of independent excitation for the electric drives of auxiliary mechanisms are given and substantiated. The optimization of the geometrical parameters of the electromechanical converter was carried out according to the maximum developed electromagnetic torque. Modern semiconductor technology in the design of special-purpose electric drives leads to a revision of the principles for determining the optimal number of phases and the structure of the motor power supply. The rationale for the use of multilevel frequency converters is given. Taking into account an in-depth preliminary analysis and an integrated approach, these tasks were successfully completed, which was confirmed experimentally at the implementation of the developed system. Full article
(This article belongs to the Special Issue Selected Papers from the ICIEAM 2020 Conference)
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Figure 1

Figure 1
<p>Pipe cold-rolling mill: 1—crank mechanism; 2—rolling stand motor; 3—rolling stand; 4—pipe billet; 5—auxiliary pipe feeding and turning mechanisms.</p> Full article ">Figure 2
<p>Dependency of the rms torque on the gear ratio of the mechanical converter and the amplitude of the resonant maximum of the frequency response.</p> Full article ">Figure 3
<p>Pattern of distribution of mechanical stresses under the action of centrifugal forces.</p> Full article ">Figure 4
<p>The distribution of mechanical stresses under torque.</p> Full article ">Figure 5
<p>Pattern of distribution of mechanical stresses under the action of centrifugal forces.</p> Full article ">Figure 6
<p>The surface of optimization of weight and dimensions of the machine.</p> Full article ">Figure 7
<p>Functions of the specific cost of semiconductor converters from the current load</p> Full article ">Figure 8
<p>Dependency of the unit cost of the frequency converter on the number of phases <span class="html-italic">f</span> and the nominal torque of the operating mechanism T.</p> Full article ">Figure 9
<p>Dependency of the permissible torque M<sub>perm</sub> on the total number of phases of the power circuit diagram <span class="html-italic">f</span> and on the number of failed phases <span class="html-italic">f</span>’.</p> Full article ">Figure 10
<p>Oscillograms of transient processes of the electric drive of rotation of the HPT-250 mill.</p> Full article ">
29 pages, 12135 KiB  
Article
The Proposition of an Automated Honing Cell with Advanced Monitoring
by Adam Barylski and Piotr Sender
Machines 2020, 8(4), 70; https://doi.org/10.3390/machines8040070 - 28 Oct 2020
Cited by 5 | Viewed by 4012
Abstract
Honing of holes allows for small shape deviation and a low value of a roughness profile parameter, e.g., Ra parameter. The honing process heats the workpiece and raises its temperature. The increase in temperature causes thermal deformations of the honed holes. The article [...] Read more.
Honing of holes allows for small shape deviation and a low value of a roughness profile parameter, e.g., Ra parameter. The honing process heats the workpiece and raises its temperature. The increase in temperature causes thermal deformations of the honed holes. The article proposes the construction of a honing cell, containing in addition to CNC honing machine: thermographic camera, sound intensity meter, and software for collecting and analyzing data received during machining. It was proposed that the level of sound intensity obtained during honing could be monitored continuously and that the images from a thermographic camera could be analyzed on-line. These analyses would be aimed at supervising honing along with the on-line correction of machining parameters. In addition to the oil cooler, the machining cell may have an automatic selection of the grain trajectory shape, with specified value of the radii of curvature of the abrasive grain trajectories, according to the wall thickness of the honed workpiece, which will result in reducing the temperature generated during honing. Automated honing cell can mostly increase honing process efficiency. Simulations in FlexSim showed the possibility of increasing the efficiency of the honing process more than 20 times. Full article
(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining)
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Figure 1

Figure 1
<p>Honing head with main honing speeds; 1—honed cylinder liner, 2—abrasive whetstone, 3—expanding mandrel, 4—pressure and machined diameter measurement, 5—temperature measurement, 6—vision system.</p> Full article ">Figure 2
<p>Possible directions of movement of honing head in honing of cylindrical holes: 1—abrasive grain trajectories, 2—expanding of honed surface, 3—honed cylinder liners with honing head, 4—additional honing head oscillation motion in vertical direction, 5—additional honing head oscillation motion in horizontal direction, 6—additional oscillation motion of honing head rotation direction.</p> Full article ">Figure 3
<p>Traditional kinematics of honing process, (<b>a</b>) constant value of honing speed, (<b>b</b>) constant linear speed of honing head, (<b>c</b>) linear value of honing head, (<b>d</b>) length of abrasive grain path in traditional honing process; 1—an example of abrasive grain path.</p> Full article ">Figure 4
<p>Variable kinematics of honing process—an example of abrasive grain trajectory obtained during honing with variable linear and tangential speed. Components of the cylindrical honing process: 1—an example of abrasive grain path received in variable kinematics of honing, 2—comparative abrasive grain path obtained in traditional honing.</p> Full article ">Figure 5
<p>Haas VF-3SS milling machine with honing equipment: 1—thermal imaging camera, 2—software of thermal imaging camera, 3—Mitutoyo SJ-210 roughness meter, 4—software of Mitutoyo SJ-210 roughness meter, 5—sound intensity meter, 6—vibration meter, 7—air nozzle.</p> Full article ">Figure 6
<p>Image from computer simulation of honing process—heat flux flow; 1—the thickest machined cross–section, 2—the thinnest honed cross-section, 3—maximum value of the measured heat flux.</p> Full article ">Figure 7
<p>Deformation of the honed workpieces—different value in different places. (<b>a</b>)view of the window from the simulator with the effect of the deformations obtained, (<b>b</b>) view of the window from the simulator with the presentation of non-linear deformation results of the honed workpiece.</p> Full article ">Figure 8
<p>Examples of different grain trajectory shapes, shown on the developed surface of machined hole, with different oscillation frequency, with different path length for the same length on horizontal direction of the treated surface. The function marked with digit 1 has one change of the head movement direction in the lower and upper turning point. The function marked with digit 2 has one change in the head movement direction in the lower turning point and two changes in the direction of the upper turning point.</p> Full article ">Figure 9
<p>Programming in non-conventional way by adding oscillation frequency and amplitude’s high to circular path generated in CAD/CAM system; 1—entering parameters, 2—circular path, 3—the resulting sinusoidal trajectory.</p> Full article ">Figure 10
<p>The method of modifying the shape of the machining path in CAD/CAM system Alphacam.</p> Full article ">Figure 11
<p>Idea of honing process with abilities to control the abrasive whetstone and honing head movements in both direction: 1—honing head body; 2—expanding pin for abrasive whetstones; 3—abrasive whetstone; 4—possible TWO-WAY direction of movement control; 5—automatic vision system.</p> Full article ">Figure 12
<p>Machining tool: 1—new whetstone; 2—damaged whetstone; 3—worn whetstone.</p> Full article ">Figure 13
<p>Obtained texture of the honed surface for variable stroke speed of honing head in the range of 1000–3000 mm/min—average value of tangent angle to the grain trajectory of 14°; 1—sample abrasive grain path; 2—tangent line to the abrasive grain path.</p> Full article ">Figure 14
<p>Example of a honed surface without texture defects, 1—probe tip.</p> Full article ">Figure 15
<p>An example of a honed surface with texture defects: 1—scratch; 2—point flaw.</p> Full article ">Figure 16
<p>Verification of the shape and it’s continuity of oil channels using a neural network. The numbers indicate the stages of the subsequent stages of surface texture verification.</p> Full article ">Figure 17
<p>Cone showing the color description method named HSV.</p> Full article ">Figure 18
<p>Schematic diagram of honing algorithm: (<b>a</b>) FEM mesh overlay and working pressure setting, (<b>b</b>) determination of thermal conditions, (<b>c</b>) deformation, sound level and image analysis, (<b>d</b>) determination of honing parameters, (<b>e</b>) honing with variable kinematics setting with <span class="html-italic">CCR</span> module, (<b>f</b>) receiving variable shape of abrasive grain trajectories optimized to manufacturing conditions.</p> Full article ">Figure 19
<p>Schematic diagram of automated honing process.</p> Full article ">Figure 20
<p>Results of numerical analysis of honing process of cylinder linear with different thickness of cross-section; (<b>a</b>) simulation result of the entire assembly, (<b>b</b>) assembly simulation result without cylinder linear, (<b>c</b>) assembly simulation result without cylinder linear and without honing head body, (<b>d</b>) simulation of stresses obtained during honing process.</p> Full article ">Figure 21
<p>Numerical simulation—deformation of a cylinder with a variable wall thickness: 1—the greatest cylindrical deformation value of honed workpiece; 2—the smallest cylindrical deformation value of honed workpiece.</p> Full article ">Figure 22
<p>Matlab Audio Labeler—analysis of sound level vs honing process time conducted on CNC vertical milling machine Haas VF-3SS. Honing with variable kinematics condition, with different value of honing head stroke speed; 1—shorter honing cycle time, 2—longer honing cycle time, 3—honed workpiece, 4—honing equipment.</p> Full article ">Figure 23
<p>Test stand: 1 equipment for measuring of the sound intensity level.</p> Full article ">Figure 24
<p>Sound intensity level depending on the average value of the variable head feed, obtained during honing with variable kinematics.</p> Full article ">Figure 25
<p>Matlab Image Colour Thresholder—analysis of thermogram of honed workpiece on CNC vertical milling machine Haas VF-3SS (earlier stage of honing (than on <a href="#machines-08-00070-f026" class="html-fig">Figure 26</a>). H—hue, S—Saturation, and V—Value (HSV).</p> Full article ">Figure 26
<p>Matlab Image Colour Thresholder—analysis of thermogram of honed part on CNC vertical milling machines Haas VF-3SS (later stage of honing process than shown on <a href="#machines-08-00070-f025" class="html-fig">Figure 25</a>). H—hue, S—Saturation, and V—Value (HSV).</p> Full article ">Figure 27
<p>Window from the FlexSim 2020 simulator—comparison of production on a conventional station and on an automatic cell; 1—automated honing cell (efficiency of automated honing cell: 11.6 workpieces/h), 2—conventional honing cell (efficiency of traditional honing: 0.5 workpiece/h). 3 and 4—FlexSim 2020 simulation’s algorithms of honing process in Process Flow.</p> Full article ">
28 pages, 8192 KiB  
Review
Wire Electrical Discharge Machining—A Review
by Laurenţiu Slătineanu, Oana Dodun, Margareta Coteaţă, Gheorghe Nagîţ, Irina Beşliu Băncescu and Adelina Hriţuc
Machines 2020, 8(4), 69; https://doi.org/10.3390/machines8040069 - 28 Oct 2020
Cited by 35 | Viewed by 9015
Abstract
Wire electrical discharge machining has appeared mainly in response to the need for detachment with sufficiently high accuracy of parts of plate-type workpieces. The improvements introduced later allowed the extension of this machining technology to obtain more complex ruled surfaces with increasingly high [...] Read more.
Wire electrical discharge machining has appeared mainly in response to the need for detachment with sufficiently high accuracy of parts of plate-type workpieces. The improvements introduced later allowed the extension of this machining technology to obtain more complex ruled surfaces with increasingly high requirements regarding the quality of the machined surfaces and the productivity of the wire electrical discharge machining process. Therefore, it was normal for researchers to be interested in developing more and more in-depth investigations into the various aspects of wire electrical discharge machining. These studies focused first on improving the machining equipment, wire electrodes, and the devices used to position the clamping of a wire electrode and workpiece. A second objective pursued was determining the most suitable conditions for developing the machining process for certain proper situations. As output parameters, the machining productivity, the accuracy, and roughness of the machined surfaces, the wear of the wire electrode, and the changes generated in the surface layer obtained by machining were taken into account. There is a large number of scientific papers that have addressed issues related to wire electrical discharge machining. The authors aimed to reveal the aspects that characterize the process, phenomena, performances, and evolution trends specific to the wire electrical discharge machining processes, as they result from scientific works published mainly in the last two decades. Full article
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Figure 1
<p>Schematic representation of the machining zone and the machining equipment in the case of the wire electrical discharge machining (WEDM) process.</p> Full article ">Figure 2
<p>Evolution of knowledge about WEDM processes and equipment.</p> Full article ">Figure 3
<p>Redrawn figure of the schematic representations of different WEDG processes: (<b>a</b>)—conventional WEDG; (<b>b</b>)—tangential feed WEDG; and (<b>c</b>)—twin-wire WEDG [<a href="#B17-machines-08-00069" class="html-bibr">17</a>].</p> Full article ">Figure 4
<p>Redrawn figure of the wire electrical discharge (WED) milling (ref. [<a href="#B26-machines-08-00069" class="html-bibr">26</a>]).</p> Full article ">Figure 5
<p>Redrawn figure of the of wire electrical discharge turning (WEDT) process (ref. [<a href="#B36-machines-08-00069" class="html-bibr">36</a>]).</p> Full article ">Figure 6
<p>Redrawn figure concerning the assisting electrode use in the wire electrochemical discharge machining: (<b>a</b>)—simple version; and (<b>b</b>)—electrochemical discharge-assisted diamond wire cutting [<a href="#B61-machines-08-00069" class="html-bibr">61</a>,<a href="#B62-machines-08-00069" class="html-bibr">62</a>].</p> Full article ">Figure 7
<p>Redrawn figure of the wire tool deflection in the work zone during the WEDM process [<a href="#B72-machines-08-00069" class="html-bibr">72</a>].</p> Full article ">Figure 8
<p>Several factors and groups of factors highlighted when analyzing WEDM as a system.</p> Full article ">Figure 9
<p>Some of the proposed models for the WEDM process.</p> Full article ">Figure 10
<p>Evolution of the number of scientific papers related to the WEDM process in the ScienceDirect database.</p> Full article ">Figure 11
<p>Increasing the number of papers addressing WEDM process optimization issues in the ScienceDirect database.</p> Full article ">
16 pages, 8610 KiB  
Article
Design and Performance of an Elbow Assisting Mechanism
by Giacomo Zuccon, Matteo Bottin, Marco Ceccarelli and Giulio Rosati
Machines 2020, 8(4), 68; https://doi.org/10.3390/machines8040068 - 27 Oct 2020
Cited by 28 | Viewed by 5776
Abstract
An elbow assisting device is presented as based on a cable-driven parallel mechanism with design solutions that are improvements from a previous original design. The new mechanism, ideal for domestic use, both for therapies and exercises, is characterized by low-cost, portable, easy-to-use features [...] Read more.
An elbow assisting device is presented as based on a cable-driven parallel mechanism with design solutions that are improvements from a previous original design. The new mechanism, ideal for domestic use, both for therapies and exercises, is characterized by low-cost, portable, easy-to-use features that are evaluated through numerical simulations and experimental tests whose results are reported with discussions. Full article
(This article belongs to the Special Issue Advanced Autonomous Machines and Designs)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Anatomy of the elbow and movement of flexion–extension of the joint [<a href="#B33-machines-08-00068" class="html-bibr">33</a>].</p> Full article ">Figure 2
<p>Requirements for improvements in CADEL.3 design.</p> Full article ">Figure 3
<p>CADEL first prototype: (<b>a</b>) a kinematic scheme; (<b>b</b>) a lab prototype test [<a href="#B13-machines-08-00068" class="html-bibr">13</a>].</p> Full article ">Figure 4
<p>CADEL.3 design with two rigid platforms connected by a flexible elbow guard.</p> Full article ">Figure 5
<p>Design details of CADEL.3 in <a href="#machines-08-00068-f004" class="html-fig">Figure 4</a>: (<b>a</b>) elbow pad; (<b>b</b>) flexor spasticity aid.</p> Full article ">Figure 6
<p>Kinematic design scheme for CADEL.3 in <a href="#machines-08-00068-f005" class="html-fig">Figure 5</a>: (<b>a</b>) overall structure with parameters; (<b>b</b>) a zoom view of the elbow pad joint.</p> Full article ">Figure 7
<p>Computed results of the simulated operation of CADEL.3 in <a href="#machines-08-00068-f006" class="html-fig">Figure 6</a> during extension elbow motion: (<b>a</b>) for <span class="html-italic">l</span><sub>1</sub> cable; (<b>b</b>) for <span class="html-italic">l</span><sub>2</sub> cable and its segments.</p> Full article ">Figure 8
<p>Computed results of the simulated operation of CADEL.3 in <a href="#machines-08-00068-f006" class="html-fig">Figure 6</a> for bending elbow motion with <span class="html-italic">T</span><sub>2</sub> = 5 N and <span class="html-italic">M</span> = 3.5 Nm when the elbow width increases in terms of <span class="html-italic">r<sub>el</sub></span>: (<b>a</b>) cable tension; (<b>b</b>) shoulder torque.</p> Full article ">Figure 9
<p>A block diagram for the design and operation of the CADEL.3 prototype.</p> Full article ">Figure 10
<p>The CADEL.3 prototype at Lab of Robotics in Padova as in <a href="#machines-08-00068-f009" class="html-fig">Figure 9</a>: (<b>a</b>) worn by a healthy person; (<b>b</b>) installed on a testbed.</p> Full article ">Figure 11
<p>Comparison between results from simulation and lab testing in terms of motor torque during: (<b>a</b>) flexion motion; (<b>b</b>) extension motion.</p> Full article ">Figure 12
<p>Comparison between results from simulation and lab testing in terms of motor power consumption during: (<b>a</b>) flexion motion; (<b>b</b>) extension motion.</p> Full article ">
17 pages, 6383 KiB  
Article
6D Virtual Sensor for Wrench Estimation in Robotized Interaction Tasks Exploiting Extended Kalman Filter
by Loris Roveda, Andrea Bussolan, Francesco Braghin and Dario Piga
Machines 2020, 8(4), 67; https://doi.org/10.3390/machines8040067 - 27 Oct 2020
Cited by 10 | Viewed by 3026
Abstract
Industrial robots are commonly used to perform interaction tasks (such as assemblies or polishing), requiring the robot to be in contact with the surrounding environment. Such environments are (partially) unknown to the robot controller. Therefore, there is the need to implement interaction controllers [...] Read more.
Industrial robots are commonly used to perform interaction tasks (such as assemblies or polishing), requiring the robot to be in contact with the surrounding environment. Such environments are (partially) unknown to the robot controller. Therefore, there is the need to implement interaction controllers capable of suitably reacting to the established contacts. Although standard force controllers require force/torque measurements to close the loop, most of the industrial manipulators do not have installed force/torque sensor(s). In addition, the integration of external sensors results in additional costs and implementation effort, not affordable in many contexts/applications. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper for the online estimation of the interaction wrench, implementing a 6D virtual sensor. Relying on sensorless Cartesian impedance control, an Extended Kalman Filter (EKF) is proposed for the interaction wrench estimation. The described approach has been validated in simulations, taking into account four different scenarios. In addition, experimental validation has been performed employing a Franka EMIKA panda robot. A human–robot interaction scenario and an assembly task have been considered to show the capabilities of the developed EKF, which is able to perform the estimation with high bandwidth, achieving convergence with limited errors. Full article
(This article belongs to the Special Issue Advanced Autonomous Machines and Designs)
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Figure 1
<p>Estimated interaction forces <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">f</mi> <mo>^</mo> </mover> </semantics></math> and torques <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">C</mi> <mo>^</mo> </mover> </semantics></math> (continuous line) vs. real interaction forces <math display="inline"><semantics> <mi mathvariant="bold">f</mi> </semantics></math> and torques <math display="inline"><semantics> <mi mathvariant="bold">C</mi> </semantics></math> (dashed line) for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>1</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 2
<p>Estimated interaction forces <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>f</mi> </msub> </semantics></math> and torques <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>C</mi> </msub> </semantics></math> errors for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>1</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 3
<p>Estimated interaction forces <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">f</mi> <mo>^</mo> </mover> </semantics></math> and torques <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">C</mi> <mo>^</mo> </mover> </semantics></math> (continuous line) vs. real interaction forces <math display="inline"><semantics> <mi mathvariant="bold">f</mi> </semantics></math> and torques <math display="inline"><semantics> <mi mathvariant="bold">C</mi> </semantics></math> (dashed line) for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>2</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 4
<p>Estimated interaction forces <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>f</mi> </msub> </semantics></math> and torques <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>C</mi> </msub> </semantics></math> errors for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>2</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 5
<p>Estimated interaction forces <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">f</mi> <mo>^</mo> </mover> </semantics></math> and torques <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">C</mi> <mo>^</mo> </mover> </semantics></math> (continuous line) vs. real interaction forces <math display="inline"><semantics> <mi mathvariant="bold">f</mi> </semantics></math> and torques <math display="inline"><semantics> <mi mathvariant="bold">C</mi> </semantics></math> (dashed line) for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>3</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 6
<p>Estimated interaction forces <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>f</mi> </msub> </semantics></math> and torques <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>C</mi> </msub> </semantics></math> errors for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>3</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 7
<p>Estimated interaction forces <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">f</mi> <mo>^</mo> </mover> </semantics></math> and torques <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">C</mi> <mo>^</mo> </mover> </semantics></math> (continuous line) vs. real interaction forces <math display="inline"><semantics> <mi mathvariant="bold">f</mi> </semantics></math> and torques <math display="inline"><semantics> <mi mathvariant="bold">C</mi> </semantics></math> (dashed line) for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>4</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 8
<p>Estimated interaction forces <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>f</mi> </msub> </semantics></math> and torques <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>C</mi> </msub> </semantics></math> errors for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>4</mn> </mrow> </semantics></math> simulation scenario.</p> Full article ">Figure 9
<p>Estimated interaction forces <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">f</mi> <mo>^</mo> </mover> </semantics></math> and torques <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">C</mi> <mo>^</mo> </mover> </semantics></math> (continuous line) vs. measured interaction forces <math display="inline"><semantics> <mi mathvariant="bold">f</mi> </semantics></math> and torques <math display="inline"><semantics> <mi mathvariant="bold">C</mi> </semantics></math> (dashed line) for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>1</mn> </mrow> </semantics></math> experimental scenario.</p> Full article ">Figure 10
<p>Estimated interaction forces <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>f</mi> </msub> </semantics></math> and torques <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>C</mi> </msub> </semantics></math> errors for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>1</mn> </mrow> </semantics></math> experimental scenario.</p> Full article ">Figure 11
<p>Experimental assembly task, including the Franka EMIKA panda manipulator and the target gear to be installed.</p> Full article ">Figure 12
<p>Estimated interaction forces <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">f</mi> <mo>^</mo> </mover> </semantics></math> and torques <math display="inline"><semantics> <mover accent="true"> <mi mathvariant="bold">C</mi> <mo>^</mo> </mover> </semantics></math> (continuous line) vs. measured interaction forces <math display="inline"><semantics> <mi mathvariant="bold">f</mi> </semantics></math> and torques <math display="inline"><semantics> <mi mathvariant="bold">C</mi> </semantics></math> (dashed line) for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>2</mn> </mrow> </semantics></math> experimental scenario.</p> Full article ">Figure 13
<p>Estimated interaction forces <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>f</mi> </msub> </semantics></math> and torques <math display="inline"><semantics> <msub> <mover accent="true"> <mi mathvariant="bold">e</mi> <mo>^</mo> </mover> <mi>C</mi> </msub> </semantics></math> errors for the <math display="inline"><semantics> <mrow> <mo>#</mo> <mn>2</mn> </mrow> </semantics></math> experimental scenario.</p> Full article ">
21 pages, 3824 KiB  
Article
Parameter Optimisation in the Vibration-Based Machine Learning Model for Accurate and Reliable Faults Diagnosis in Rotating Machines
by Natalia Espinoza Sepulveda and Jyoti Sinha
Machines 2020, 8(4), 66; https://doi.org/10.3390/machines8040066 - 23 Oct 2020
Cited by 22 | Viewed by 3761
Abstract
Artificial intelligence (AI)-based machine learning (ML) models seem to be the future for most of the applications. Recent research effort has also been made on the application of these AI and ML methods in the vibration-based faults diagnosis (VFD) in rotating machines. Several [...] Read more.
Artificial intelligence (AI)-based machine learning (ML) models seem to be the future for most of the applications. Recent research effort has also been made on the application of these AI and ML methods in the vibration-based faults diagnosis (VFD) in rotating machines. Several research studies have been published over the last decade on this topic. However, most of the studies are data driven, and the vibration-based ML (VML) model is generally developed on a typical machine. The developed VML model may not predict faults accurately if applied on other identical machines or a machine with different operation conditions or both. Therefore, the current research is on the development of a VML model by optimising the vibration parameters based on the dynamics of the machine. The developed model is then blindly tested at different machine operation conditions to show the robustness and reliability of the proposed VML model. Full article
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Figure 1
<p>A typical multi-layer perceptron (MLP) neural network used in the study.</p> Full article ">Figure 2
<p>Schematic of the experimental rig.</p> Full article ">Figure 3
<p>Experimental mode shapes: (<b>a</b>) 50.66 Hz, vertical direction dominant; (<b>b</b>) 56.76 Hz, horizontal direction dominant.</p> Full article ">Figure 4
<p>A typical mounting arrangement of an accelerometer at a bearing housing.</p> Full article ">Figure 5
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x velocity spectra values for the healthy condition at 1800 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 6
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the misalignment condition at 1800 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 7
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the looseness condition at 1800 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 8
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the shaft bow condition at 1800 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 9
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the shaft rub condition at 1800 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 10
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x velocity spectra values for the healthy condition at 2400 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 11
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the misalignment condition at 2400 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 12
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the looseness condition at 2400 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 13
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the shaft bow condition at 2400 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">Figure 14
<p>Estimated RMS and Kurtosis from the measured acceleration signals and their 1x, 2x, 3x velocity spectra values for the shaft rub condition at 2400 RPM (B1, circle; B2, square; B3, cross; and B4, triangle).</p> Full article ">
21 pages, 35678 KiB  
Article
Analysis of the Possibility of Using Wavelet Transform to Assess the Condition of the Surface Layer of Elements with Flat-Top Structures
by Paweł Karolczak, Maciej Kowalski and Magdalena Wiśniewska
Machines 2020, 8(4), 65; https://doi.org/10.3390/machines8040065 - 22 Oct 2020
Cited by 9 | Viewed by 2552
Abstract
The paper focused on a topic related to the possibilities of using wavelet analysis to evaluate the changes in the geometrical structures of the surfaces arising during the honing process with whetstones with variable granularity. The cylinder liners of the combustion engine are [...] Read more.
The paper focused on a topic related to the possibilities of using wavelet analysis to evaluate the changes in the geometrical structures of the surfaces arising during the honing process with whetstones with variable granularity. The cylinder liners of the combustion engine are machined elements. The basics of the wavelet analysis and the differences between filtering with standardized filters (e.g., Gauss filter), Fourier analysis, and the analysis of the results obtained when measuring the surface roughness with other wavelets were described. Trials of honing four cylinder liners were carried out. Roughness measurements of 3D spatial structures of the prepared liners were made. The principle of selecting wavelets for roughness assessment of structures with cross-hatch pattern was described. Roughness structures generated on the honed surfaces of cylinder liners were assessed using Gaussian filtration and Morlet, Daubechies Db6, and Mexican hat wavelets. In order to demonstrate the differences generated when the Gaussian filtration and selected wavelets were used on surface structures, the surfaces obtained with the use of these filtering tools were subtracted from each other, which allowed obtaining information about the changes occurring on the assessed surfaces, which were generated after the use of various filtering tools. For the assessed surfaces, during the subtraction operation, the mean square error was calculated, informing about the degree of similarity of both compared surfaces. The result of the work carried out is the creation of basic recommendations for the selection of wavelets when assessing honed surfaces with different degrees of regularity of the traces generated on them. Full article
(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining)
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<p>Exemplary signal and its transformation using the Fourier transform [<a href="#B4-machines-08-00065" class="html-bibr">4</a>].</p> Full article ">Figure 2
<p>Example of the impact of changes in the scale factor on the wavelet [<a href="#B4-machines-08-00065" class="html-bibr">4</a>].</p> Full article ">Figure 3
<p>Effect of changing the translation parameter on wavelet [<a href="#B4-machines-08-00065" class="html-bibr">4</a>].</p> Full article ">Figure 4
<p>Mitutoyo profilografometer SURFTEST SV-3200.</p> Full article ">Figure 5
<p>Measured roughness of sample no. 1 after filtration with Gaussian filter.</p> Full article ">Figure 6
<p>Results of filtration of the surface geometrical structure of sample 1 with Daubechies wavelet on the 1st row with the 1st level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 7
<p>Results of filtration of the surface geometrical structure of sample 1 with Daubechies wavelet on the 1st row with the 6th level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 8
<p>Results of filtration of the surface geometrical structure of sample 1 with Daubechies wavelet of the 3rd row with the 1st level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 9
<p>Results of filtration of the surface geometrical structure of sample no. 1 with Daubechies wavelet of the 3rd row with the 3rd level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 10
<p>Results of filtration of the surface geometrical structure of sample no. 1 with Daubechies wavelet of the 3rd row on the 5th level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 11
<p>Results of filtration of the surface geometrical structure of sample no. 1 with Daubechies wavelet of the 6th row with the 1st level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 12
<p>Results of filtration of the surface geometrical structure of sample no. 1 with Daubechies wavelet of the 6th row with the 3rd level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 13
<p>Results of filtration of the surface geometrical structure of sample no. 1 with Daubechies wavelet of the 6th row with the 5th level of filtration—(<b>a</b>) waviness, (<b>b</b>) roughness.</p> Full article ">Figure 14
<p>Wavelets used in the research: (<b>a</b>) Daubechies of 6th row, (<b>b</b>) Morlet, (<b>c</b>) Mexican hat [<a href="#B5-machines-08-00065" class="html-bibr">5</a>].</p> Full article ">Figure 15
<p>Surfaces of the samples tested with flat-top structures after their leveling and shape removal: (<b>a</b>) sample 1, (<b>b</b>) sample 2, (<b>c</b>) sample 3, (<b>d</b>) sample 4.</p> Full article ">Figure 16
<p>The surface of sample 1 with a flat-top structure after leveling and shape removal and application of (<b>a</b>) Gaussian filtration, (<b>b</b>) Daubechies wavelet, (<b>c</b>) Morlet wavelet, (<b>d</b>) Mexican hat wavelet.</p> Full article ">Figure 17
<p>Surfaces created as a result of subtracting structure obtained with a wavelet from the structure after applying Gauss filtering: (<b>a</b>) Daubechies wavelet, (<b>b</b>) Morlet wavelet, (<b>c</b>) Mexican hat wavelet. The root mean square error: (<b>a</b>) 0.36 µm, (<b>b</b>) 0.62 µm, (<b>c</b>) 0.68 µm.</p> Full article ">Figure 18
<p>The surfaces of sample no. 2 with a flat-top structure after its leveling, shape removing, and applying: (<b>a</b>) Gauss filtering, (<b>b</b>) Daubechies wavelet, (<b>c</b>) Morlet wavelet, (<b>d</b>) Mexican hat wavelet.</p> Full article ">Figure 19
<p>Surfaces created as a result of subtracting the structure obtained with wavelet from the structure after using Gaussian filtering: (<b>a</b>) Daubechies wavelet, (<b>b</b>) Morlet wavelet, (<b>c</b>) Mexican hat wavelet. The root mean square error: (<b>a</b>) 0.18 µm, (<b>b</b>) 0.27 µm, (<b>c</b>) 0.31 µm.</p> Full article ">Figure 20
<p>The surface of sample no. 3 with a flat-top structure after leveling, shape removing, and applying: (<b>a</b>) Gaussian filter, (<b>b</b>) Daubechies wavelet, (<b>c</b>) Morlet wavelet, (<b>d</b>) Mexican hat wavelet.</p> Full article ">Figure 21
<p>The surface was created as a result of subtracting the structure obtained with the wavelet from the structure after applying Gaussian filtration: (<b>a</b>) Daubechies wavelet 6, (<b>b</b>) Morlet wavelet, (<b>c</b>) Mexican hat wavelet. The root mean square error: (<b>a</b>) 0.28 µm, (<b>b</b>) 0.32 µm, (<b>c</b>) 0.53 µm.</p> Full article ">Figure 22
<p>Surfaces of sample no. 4 with flat-top structure, after leveling, shape removing, and applying: (<b>a</b>) Gaussian filter, (<b>b</b>) Daubechies wavelet, (<b>c</b>) Morlet wavelet, (<b>d</b>) Mexican hat wavelet.</p> Full article ">Figure 23
<p>The surface was created as a result of subtracting the structure obtained with the wavelet with the wavelet from the structure after applying Gaussian filtration (<b>a</b>) Daubechies wavelet, (<b>b</b>) Morlet wavelet, (<b>c</b>) Mexican hat wavelet. The root mean square error: (<b>a</b>) 0.48 µm, (<b>b</b>) 0.72 µm, (<b>c</b>) 1.63 µm.</p> Full article ">
24 pages, 6691 KiB  
Article
Analysis and Synthesis of Control Systems for Spacecraft Solar Arrays
by Anatoly K. Tishchenko, Eugeny M. Vasiljev and Artyom O. Tishchenko
Machines 2020, 8(4), 64; https://doi.org/10.3390/machines8040064 - 21 Oct 2020
Cited by 2 | Viewed by 2763
Abstract
The paper is devoted to the problem of creating highly reliable power supply systems for spacecrafts intended for long-term autonomous flights. Within its framework, the problem of synthesizing a control system for solar arrays is being solved. To solve this problem, a mathematical [...] Read more.
The paper is devoted to the problem of creating highly reliable power supply systems for spacecrafts intended for long-term autonomous flights. Within its framework, the problem of synthesizing a control system for solar arrays is being solved. To solve this problem, a mathematical model of a solar panel was compiled, and a study of its static and dynamic characteristics was carried out. It was found that when the solar panel is controlled using a shunt switch with pulse-width modulation, resonance phenomena appear in the system, leading to an unacceptable change in the polarity of voltages on the photocells. The operating conditions of the solar panels, which exclude the occurrence of the indicated alternating voltages, are found, and appropriate recommendations are given for the choice of the quantization frequency in the system. On the basis of the recommendations received, the transition to a quasi-continuous representation of the control system was carried out, and a graphic-analytical synthesis of the controller providing the required quality indicators of the system was carried out. To ensure the survivability of the power supply system, a method is proposed for the hierarchical organization of the interaction of solar panels, which reproduces the homeostatic properties of biological structures in the system. This property is provided by automatic transfer of control to subsequent levels of the hierarchy as the energy resources of the previous levels are exhausted. In addition, selective control is applied only to that part of the total generated power, which is sufficient to counter the current disturbing influences on the system. This approach to control prevents cascading failures in the system. The paper presents simulation models on which all theoretical positions and methods proposed in the work are tested. Full article
(This article belongs to the Special Issue Selected Papers from the ICIEAM 2020 Conference)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The structure of the solar array control system.</p> Full article ">Figure 2
<p>Equivalent circuit of a solar cell photocell, taking into account reactive components.</p> Full article ">Figure 3
<p>Solar panel simulation model in MatLab package.</p> Full article ">Figure 4
<p>The static characteristics of the solar panel: (<b>a</b>) when the temperature <span class="html-italic">T</span> changes; (<b>b</b>) when the density of the luminous flux <span class="html-italic">W</span> changes.</p> Full article ">Figure 5
<p>Frequency response of the solar panel.</p> Full article ">Figure 6
<p>Solar panel equivalent circuit.</p> Full article ">Figure 7
<p>Comparison of the amplitude frequency characteristics of the equivalent and full equivalent circuits of a solar panel.</p> Full article ">Figure 8
<p>Voltage ripple on the solar panel at different frequencies of current change.</p> Full article ">Figure 9
<p>Change in current <span class="html-italic">I</span><sub>SB</sub>(<span class="html-italic">t</span>) of the panel and voltage <span class="html-italic">U</span><sub>p</sub>(<span class="html-italic">t</span>)on the photocells when the shunt switch is closed.</p> Full article ">Figure 10
<p>Analysis of the influence of switching frequency <span class="html-italic">f</span><sub>PM</sub> on voltage fluctuations <span class="html-italic">U</span><sub>p</sub>.</p> Full article ">Figure 11
<p>Initial <span class="html-italic">L</span><sub>i</sub>, <span class="html-italic">φ</span><sub>i</sub> and desired <span class="html-italic">L</span><sub>d</sub>, <span class="html-italic">φ</span><sub>d</sub> frequency response of the system.</p> Full article ">Figure 12
<p>Transient response of a looped system.</p> Full article ">Figure 13
<p>Stability region <span class="html-italic">D</span>(0) of the system in the plane of coefficients <span class="html-italic">a</span><sub>1</sub> and <span class="html-italic">a</span><sub>2</sub>.</p> Full article ">Figure 14
<p>Root locus of characteristic polynomial for the range of transmission coefficient <span class="html-italic">k</span> = (100…465…3000) × 10<sup>9</sup>.</p> Full article ">Figure 15
<p>Mutual arrangement of regulation ranges for two solar panels.</p> Full article ">Figure 16
<p>Simulation model of a synthesized control system in MatLab.</p> Full article ">Figure 17
<p>Transient processes in the system with abrupt changes in the load current <span class="html-italic">I</span><sub>L</sub> = 5–25–50–25–5 A. <span class="html-italic">I</span><sub>SB1</sub>, <span class="html-italic">I</span><sub>SB2</sub>—currents supplied to the load by solar panels No. 1 and No. 2; <span class="html-italic">U</span><sub>L</sub>—load voltage.</p> Full article ">Figure 18
<p>System response to illumination changes. <span class="html-italic">W</span> = 1000–200–1000 W/m<sup>2</sup>. <span class="html-italic">T</span>=25 °C.</p> Full article ">Figure 19
<p>System response to temperature changes. <span class="html-italic">T</span> = (−110)–(+80)–(−110) °C. <span class="html-italic">W</span> = 1000 W/m<sup>2</sup>.</p> Full article ">Figure A1
<p>Scheme for solving the system of Equations (1)–(6) describing the operation of the photocell.</p> Full article ">Figure A2
<p>Simulation model for the study of transient processes in a solar panel.</p> Full article ">Figure A3
<p>Transient processes in a solar cell at a frequency of 1 kHz.</p> Full article ">Figure A4
<p>Model of the initial part of the system for small deviations.</p> Full article ">Figure A5
<p>Model of solar panel No. 2 with analog equivalents of a pulse-width modulator and a shunt switch.</p> Full article ">
17 pages, 5257 KiB  
Article
The Possibilities of Improving the Fatigue Durability of the Ship Propeller Shaft by Burnishing Process
by Stefan Dzionk, Włodzimierz Przybylski and Bogdan Ścibiorski
Machines 2020, 8(4), 63; https://doi.org/10.3390/machines8040063 - 18 Oct 2020
Cited by 11 | Viewed by 4298
Abstract
Heavily loaded structural elements operating in a corrosive environment are usually quickly destroyed. An example of such an element is a ship propeller operating in a seawater environment. This research presents a fatigue resistance test performed on elements operating in seawater. Different processing [...] Read more.
Heavily loaded structural elements operating in a corrosive environment are usually quickly destroyed. An example of such an element is a ship propeller operating in a seawater environment. This research presents a fatigue resistance test performed on elements operating in seawater. Different processing parameters applied on the samples in particular were compared with the specimens whose surface had been burnished differently and they were compared to specimens with a grinded surface. The research shows that the structural elements whose surface has been burnished can have up to 30% higher fatigue strength in a seawater environment than the elements whose surface has been grinded. During burnishing, an important feature of the process is the degree of cold rolling of the material. The resistance of the component to fatigue loads increases only to a certain level with increasing the degree of the cold rolling. Further increasing the degree of cold rolling reduces the fatigue strength. Introducing additional stresses in the components (e.g., assembly stresses) reduces the fatigue strength of this component in operation and these additional stresses should be accounted for while planning the degree of the cold rolling value. A device that allows for simultaneous turning and shaft burnishing with high slenderness is presented in the appendix of this article. This device can be connected to the computerized numerical control system and executed automatic process according to the machining program; this solution reduces the number of operations and cost in the process. Full article
(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining)
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Figure 1

Figure 1
<p>Scheme of screw shaft joint with ship propeller: 1—ship propeller; 2—hull of a ship; 3—bearing sleeve; 4—screw shaft; 5—area of damage; 6—pitting corrosion; 7—fatigue cracks; 8—fretting corrosion; 9—cover.</p> Full article ">Figure 2
<p>Scheme of forces in screw shaft joint with ship propeller: 1—screw shaft; 2—propeller tightening nut; 3—ship propeller; 4—bearing sleeve; 5—interference surface; 6—conical pressure surface; 7—bearing sliding surface; <span class="html-italic">G</span>—gravity force of propeller; <span class="html-italic">MG</span>—bending moment from propeller gravity force; <span class="html-italic">MGv</span>—bending moment vibration cause by propeller rotation; <span class="html-italic">Fn</span>—propelling force; F<span class="html-italic">nv</span>—longitudinal vibrations of the shaft; <span class="html-italic">Tq</span>—shaft torque; <span class="html-italic">Tqv</span>—vibration of shaft torque; <span class="html-italic">q</span>—unit pressure in junction of shaft and propeller hub; F<span class="html-italic">tq</span>—force of assembly tension.</p> Full article ">Figure 3
<p>Scheme of low plasticity burnishing process: 1—burnishing ball or roll; 2—previous position of burnishing ball; 3—surface before burnishing; 4—wave of material before burnishing element; 5—surface after burnishing; 6—graph of material strain in parallel to the surface direction; 7—roughness zone; 8—grain fragmentation zone; 9—zone of plastic deformation; 10—zone of elastic deformation; 11-core; F—burnishing force; <span class="html-italic">fb</span>—feed of burnishing.</p> Full article ">Figure 4
<p>Drawing of test samples (dimensions are specified in [mm]): (<b>a</b>) conical sample with assembly joint; (<b>b</b>) cylindrical sample; 1—test sample (steel); 2—pressure sleeve (copper alloy); 3—tightening screw.</p> Full article ">Figure 5
<p>Surface profile of burnishing samples: (<b>a</b>) roughness profile; (<b>b</b>) material ratio curve; (<b>c</b>) frequency density curve.</p> Full article ">Figure 6
<p>Photographs of samples: (<b>a</b>) conical test sample; (<b>b</b>) test sample in assembling state as a tightening joint; (<b>c</b>) cylindrical sample.</p> Full article ">Figure 7
<p>Test sample in the connector for fatigue tests (dimensions are specified in [mm]): 1—test sample; 2—pressure sleeve; 3—connector for fatigue test; 4—tightening screw.</p> Full article ">Figure 8
<p>Photograph of testing stand for fatigue strength: 1—support bearing; 2—joints for creating testing loads; 3—plates for assembling water cover sheet for seawater; 4—testing sample in the connector; 5—rubber cover sheet for seawater (in open position); 6—clutch; 7—motor; 8—state base; 9—sample before testing; 10—sample after testing.</p> Full article ">Figure 9
<p>Fatigue testing stand with equipment for testing in seawater: 1—stand body; 2—weight rod; 3—connecting pipe; 4—water pump; 5—seawater container; 6—weights.</p> Full article ">Figure 10
<p>The graph of fatigue strength for the cylindrical samples made with steel (C35) for different burnishing forces and to compare grinding samples. 1—the burnishing; 2—standard deviation of burnishing; 3 and 5—standard deviation of grinding; 4—the grinding; 6—approximating curve as a 2nd degree polynomial.</p> Full article ">Figure 11
<p>The calculated S–N curves for the samples made with steel (C35): 1—burnishing cylindrical samples by force 3 kN; 2—burnishing cylindrical samples by force 6 kN; 3—burnished conical samples by force 6 kN with a pressed-in sleeve; 4—burnished conical sample by force 3 kN with a pressed-in sleeve; 5—grinded cylindrical samples; 6—grinded conical sample with a pressed-in sleeve.</p> Full article ">Figure 12
<p>Fatigue fracture for conical sample burnished with the force 3 kN: 1—pressure sleeve; 2—test sample; 3—brittle fracture; 4—material flaw.</p> Full article ">Figure 13
<p>Fatigue fracture for conical sample burnished with the force 6 kN: 1—brittle fracture; 2—cracks on the sample surface.</p> Full article ">Figure 14
<p>Scheme of the equipment for machining stepped shafts on computerized numerical controlled machine tools by turning and burnishing: 1—stepper motor; 2—equipment body; 3—worm gear; 4—quick-release joint of the hydraulic system; 5—cutting insets; 6—burnishing balls; 7—slide-way of tools; 8—measuring probe; d—direction of tool offset.</p> Full article ">Figure 15
<p>Exemplary instruction sheet for the operation of strengthening burnishing of a B557 type marine tail shaft with the use of the equipment for turning and burnishing.</p> Full article ">
16 pages, 3366 KiB  
Article
An Analytical Method for Generating Determined Torque Ripple in Synchronous Machine with Interior Magnets by Harmonic Current Injection
by Matthias Vollat, Junchao Li and Frank Gauterin
Machines 2020, 8(4), 62; https://doi.org/10.3390/machines8040062 - 15 Oct 2020
Cited by 1 | Viewed by 1931
Abstract
In this paper, we present an extension for an analytical method of calculating the required amplitudes and phase angles of the injected harmonic currents, to generate a determined torque ripple for synchronous machines. With the consideration of reluctance torque in the system equations, [...] Read more.
In this paper, we present an extension for an analytical method of calculating the required amplitudes and phase angles of the injected harmonic currents, to generate a determined torque ripple for synchronous machines. With the consideration of reluctance torque in the system equations, this method is valid not only for synchronous machines with surface magnets, but also for those with interior magnets. First, we describe the machine equations as a function of the phase current and the back electromotive force. We then introduce an analytical way to calculate the reluctance torque. After combining the equations, we establish a linear system of equations. The solution of the equation system yields the amplitudes and phase angles of the harmonic currents to be injected. Finally, we validate the equations for calculating the reluctance Torque and the method to generate the determined torque ripple with several finite element method simulations. This allowed us to generate the desired torque fluctuations even for synchronous machines with interior magnets. Full article
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Figure 1

Figure 1
<p>Simplified electrical equivalent circuit of a synchronous machine in star connection.</p> Full article ">Figure 2
<p>Cross-section through the IPMSM with magnets in V-arrangement used in the validation of the analytical method for calculating the reluctance torque.</p> Full article ">Figure 3
<p>Distribution of the key indicator, <math display="inline"><semantics> <mrow> <msub> <mi>e</mi> <mrow> <mi>f</mi> <mi>u</mi> <mi>n</mi> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> for the constant torque value.</p> Full article ">Figure 4
<p>Distribution of the key indicator, <math display="inline"><semantics> <mrow> <msub> <mi>e</mi> <mrow> <mi>h</mi> <mi>a</mi> <mi>r</mi> <mi>m</mi> </mrow> </msub> </mrow> </semantics></math> for the value of harmonics in torque.</p> Full article ">Figure 5
<p>Time course of the torque for a selected operating point, resulting from the FEM calculation as well as from the analytical calculation with and without reluctance torque.</p> Full article ">Figure 6
<p>Order spectra of the time courses from <a href="#machines-08-00062-f005" class="html-fig">Figure 5</a>. For better representation, the bars for the zeroth order have been hidden and indicated by their numerical values.</p> Full article ">Figure 7
<p>Order spectrum for scenario S1. For better readability, the bars for the zeroth order have been hidden and indicated by their numerical values. Extended harmonic current injection (eHCI) corresponds to the method from <a href="#sec3-machines-08-00062" class="html-sec">Section 3</a>. Generative harmonic current injection (gHCI) corresponds to the approach from [<a href="#B24-machines-08-00062" class="html-bibr">24</a>].</p> Full article ">Figure 8
<p>Order spectrum for scenario S4. For better readability, the bars for the zeroth order have been hidden and indicated by their numerical values. Extended harmonic current injection (eHCI) corresponds to the method from <a href="#sec3-machines-08-00062" class="html-sec">Section 3</a>. Generative harmonic current injection (gHCI) corresponds to the approach from [<a href="#B24-machines-08-00062" class="html-bibr">24</a>].</p> Full article ">
16 pages, 5941 KiB  
Article
Novel Integration of CAPP in a G-Code Generation Module Using Macro Programming for CNC Application
by Trung Kien Nguyen, Lan Xuan Phung and Ngoc-Tam Bui
Machines 2020, 8(4), 61; https://doi.org/10.3390/machines8040061 - 12 Oct 2020
Cited by 13 | Viewed by 4982
Abstract
In the modern manufacturing industry, the role of computer-aided process planning (CAPP) is becoming increasingly crucial. Through the application of new technologies, experience, and intelligence, CAPP is contributing to the automation of manufacturing processes. In this article, the integration of a proposed CAPP [...] Read more.
In the modern manufacturing industry, the role of computer-aided process planning (CAPP) is becoming increasingly crucial. Through the application of new technologies, experience, and intelligence, CAPP is contributing to the automation of manufacturing processes. In this article, the integration of a proposed CAPP system that is named as BKCAPP and G-code generation module provides a completed CAD–CAPP–CNC system that does not involve any manual processing in the CAM modules. The BKCAPP system is capable of automatically performing machining feature and operation recognition processes from design features in three-dimensional (3D) solid models, incorporating technical requirements such as the surface roughness, geometric dimensions, and tolerance in order to provide process planning for machining processes, including information on the machine tools, cutting tools, machining conditions, and operation sequences. G-code programs based on macro programming are automatically generated by the G-code generation module on the basis of the basic information for the machining features, such as the contour shape, basic dimensions, and cutting information obtained from BKCAPP. The G-code generation module can be applied to standard machining features, such as faces, pockets, bosses, slots, holes, and contours. This novel integration approach produces a practical CAPP method enabling end users to generate operation consequences and G-code files and to customize specific cutting tools and machine tool data. In this paper, a machining part consisting of basic machining features was used in order to describe the method and verify its implementation. Full article
(This article belongs to the Section Advanced Manufacturing)
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Figure 1
<p>Principles of the integrated computer-aided design (CAD)–computer-aided process planning (CAPP)–computer numerical control (CNC) G-code flow.</p> Full article ">Figure 2
<p>Examples of machining feature recognition rules.</p> Full article ">Figure 3
<p>Example of machining feature recognition.</p> Full article ">Figure 4
<p>Example of contour feature declaration.</p> Full article ">Figure 5
<p>Toolpaths for (<b>a</b>) rough, and (<b>b</b>) finish machining.</p> Full article ">Figure 6
<p>Interface of the BKCAPP system with three-dimensional (3D) part drawing input.</p> Full article ">Figure 7
<p>The interface of the G-code generation module.</p> Full article ">Figure 8
<p>Cutting simulation for contour features in CNC control system using Fanuc 21: (<b>a</b>) rough machining toolpaths; (<b>b</b>) finish machining toolpaths.</p> Full article ">
18 pages, 960 KiB  
Communication
Strategy for Application of Support Object for Fall Prevention in the Elderly Based on Balance Recovery Characteristics
by Soichiro Matsuda and Yukio Takeda
Machines 2020, 8(4), 60; https://doi.org/10.3390/machines8040060 - 7 Oct 2020
Cited by 1 | Viewed by 2818
Abstract
This research proposes a strategy for applying support objects—equipment, tools, and even furniture/environment from which humans can receive reaction force through their hands—for fall prevention in the elderly. This paper presents an assessment example of support objects based on balance recovery characteristics and [...] Read more.
This research proposes a strategy for applying support objects—equipment, tools, and even furniture/environment from which humans can receive reaction force through their hands—for fall prevention in the elderly. This paper presents an assessment example of support objects based on balance recovery characteristics and a discussion regarding their application according to the assessment results. The balance recovery characteristics depend on the direction in which reaction force can be obtained based on the shape of the support object and direction in which the force is easily exerted on the hand. Evaluation indices for assessing the height and shape of nonportable support objects and determining a position of the tip on the ground of a cane, a typical portable support object, in the anterior direction are briefly introduced based on the authors’ previous works. The strategy for the application of support objects utilizing the evaluation indices is proposed; better use of support objects, their locations, new-shaped ones, and support devices with a new design concept are discussed and introduced based on the values of the calculated indices according to the type/usage of the support objects. Full article
(This article belongs to the Special Issue Selected Papers from Advances of Japanese Machine Design)
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Figure 1

Figure 1
<p>Application examples of support objects. (<b>a</b>) walking instruction system; (<b>b</b>) new-shaped support object; and, (<b>c</b>) cane with damper element.</p> Full article ">Figure 2
<p>Nonportable support objects. (<b>a</b>) support object #1: handrail (cylindrical shape); (<b>b</b>) support object #2: wall (vertical-planar shape); and, (<b>c</b>) support object #3: table (horizontal-planar shape).</p> Full article ">Figure 3
<p>Portable support object. (<b>a</b>) support object #4: cane (line-segment shape); and, (<b>b</b>) definition of moving coordinate system O − x<sub>C</sub>y<sub>C</sub>z<sub>C</sub> and angles α and β.</p> Full article ">Figure 4
<p>Serial mechanism with 7-DOF and inverted pendulum as human model adapted from [<a href="#B8-machines-08-00060" class="html-bibr">8</a>]. (<b>a</b>) overview; (<b>b</b>) serial mechanism with 7-DOF; and, (<b>c</b>) inverted pendulum.</p> Full article ">Figure 5
<p>Overview of manipulating force ellipsoid.</p> Full article ">Figure 6
<p>Model of balance recovery adapted from [<a href="#B8-machines-08-00060" class="html-bibr">8</a>]. (<b>a</b>) View from −y axis; and, (<b>b</b>) view from +z axis.</p> Full article ">Figure 7
<p>Analytical model used in the simulation adapted from [<a href="#B9-machines-08-00060" class="html-bibr">9</a>]. (<b>a</b>) Model without dynamic pair; (<b>b</b>) model with dynamic pair (this model was used in the simulation); and, (<b>c</b>) the definition of outputs i n the simulation.</p> Full article ">Figure 8
<p>Use of both arms: Touching a wall and a table by each hand.</p> Full article ">Figure 9
<p>Example of a support tool on affected-side.</p> Full article ">Figure 10
<p>Difference of width according to environments in which support object is used. (<b>a</b>) Living space; (<b>b</b>) medical facility or nursing home; and, (<b>c</b>) outdoors.</p> Full article ">
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