Search Results (2,834)

With the growing demand for high-performance polymer composites, conventional single- and twin-screw extruders often fall short of meeting industrial requirements for effective mixing and compounding. This research investigates the kinematic behavior of the plasticization and transport mechanisms in tri-screw extruders when subjected to a vibrational force field. The study specifically examines how applying vibrational force technology can improve the efficiency of polymer mixing. Vibration force field means that in a three-screw mechanism, an axial vibration is applied to the middle screw to produce a vibration force field. Through the development of mathematical and physical models, this study analyzed the motion dynamics of the screw and the influence of a vibrational force field on polymer transport and mixing efficiency. The findings indicate that, in comparison to traditional twin-screw extruders, tri-screw systems can achieve higher shear and elongational rates, leading to enhanced polymer mixing uniformity. Furthermore, applying an axial vibrational force field significantly influenced the shear and elongational strain rates of the material, thereby optimizing its rheological behavior and processing quality. This research not only establishes a theoretical foundation for the design and optimization of tri-screw extruders but also opens new pathways for the efficient processing of high-viscosity composite materials. Full article

This study describes the design, simulation, and development process of a rehabilitation glove driven by soft pneumatic actuators. A new, innovative finger soft actuator design has been developed through detailed kinematic and workspace analysis of anatomical fingers and their actuators. The actuator design combines cylindrical and ribbed geometries with a reinforcing element—a thicker, less extensible structure—resulting in an asymmetric cylindrical bellow actuator driven by positive pressure. The performance of the newly designed actuator for the rehabilitation glove was validated through numerical simulation in open-source software. The simulation results indicate actuators’ compatibility with human finger trajectories. Additionally, a rehabilitation glove was 3D-printed from soft materials, and the actuator’s flexibility and airtightness were analyzed across different wall thicknesses. The 0.8 mm wall thickness and thermoplastic polyurethane (TPU) material were chosen for the final design. Experiments confirmed a strong linear relationship between bending angle and pressure variations, as well as joint elongation and pressure changes. Next, pseudo-rigid kinematic models were developed for the index and little finger soft actuators, based solely on pressure and link lengths. The workspace of the soft actuator, derived through forward kinematics, was visually compared to that of the anatomical finger and experimentally recorded data. Finally, an ergonomic assessment of the complete rehabilitation glove in interaction with the human hand was conducted. Full article

The aim of this paper is to develop a mathematical model for an unconventional worm gear consisting of a globoid worm and a worm wheel where the teeth are bearings. Using rolling elements such the teeth of the worm wheel (ball bearings) transforms the sliding friction to rolling friction during the process of worm gear meshing, improving power. The geometry of the component elements of the gear is analyzed in correlation with its kinematics. After the creation of the mathematical model, it is validated both analytically (through complex graphic representations) and experimentally (by creating, for a particular case, the 3D model and the concrete physical model (prototype) of the gear through 3D printing). Full article

Optimization procedures provide ligament parameters by minimizing the difference between experimental measurements and computational simulations. Literature values are used as initial guesses of ligament parameters for these optimization procedures. However, it remains unknown how these values affect the estimation of ligament parameters. This study evaluates the effects of the initial guess on estimations of ligament parameters. A synthetic data set was generated using a subject-specific knee computational model, reference ligament parameters and simulated laxity tests. Subsequently, ligament parameters were estimated using an optimization routine and four different initial guesses. The distance of these initial guesses from their true values ranged from 0 to 3.5 kN and from 0 to 3.6% for the stiffness and reference strains, respectively. The optimized ligament parameters had an average absolute mean error ranging from 0.15 (0.09) kN and 0.08 (0.04)% to 3.67 (2.46) kN and 1.25 (0.76)%, while the kinematic error remained below 1 mm and 1.2° for all conditions. Our results showed that the estimations of the ligament parameters worsened as the initial guesses moved farther away from their true values. Moreover, the optimization procedure resulted in suboptimal ligament parameters that provided similar behavior to the true laxity behavior, which is an alarming finding that should be further investigated. Full article

Ground reaction forces (GRFs) are known to be high during front foot contact of fast bowling deliveries in cricket. There is a lack of published data on the GRFs during follow through foot contacts. The aim of this study was to quantify and compare peak GRFs and impulse of the delivery stride and the follow through of fast bowling deliveries. Ten trained male fast bowlers (ball release speed mean ± SD; 32.6 ± 2.3 m/s) competing in the Men’s Victorian Premier League participated in the study. Peak GRF and impulse data were collected using in-ground force plates in a laboratory setting. Linear mixed modelling of GRFs and impulse showed a significant effect of foot strike (p < 0.001). Front foot contact had the greatest magnitude of peak vertical GRF (5.569 ± 0.334 BW) but was not significantly greater than back foot recontact (4.471 ± 0.285 BW) (p = 0.07). Front foot impact had the greatest vertical impulse (0.408 ± 0.018 BW·s) but was similar to back foot (0.377 ± 0.012 BW·s) and front foot (0.368 ± 0.006 BW·s) recontacts (p = 0.070 to 0.928). The high GRF and impulse during the follow through highlights the need for further kinetic and kinematic research on this phase of the fast bowling delivery. Full article

In order to solve the problem of mowing between plants in Xinjiang trunk orchards, an obstacle avoidance mower suitable for trunk orchard planting mode was designed. The whole structure, working principle and main parameter design of the obstacle avoidance mower are introduced. The finite element analysis and kinematic analysis of the cutter are carried out on the premise of using a Y-shaped cutter and its arrangement, and the condition that the inter-row mower does not leak is determined. Through the modal analysis of the frame, the range of the first six natural frequencies of the frame is determined and compared with the frequency of the main excitation source of the machine to determine the rationality of the frame design. On the premise of simplifying the inter-plant obstacle avoidance mechanism into a two-dimensional model for kinematics analysis, the motion parameters of the key components of the machine were determined. At the same time, the virtual kinematics simulation single-factor test of the designed inter-plant obstacle avoidance device was carried out with the help of ADAMS 2020 software. Through the reduction in and calculation of the motion trajectory of the simulation test, it was finally determined that the forward speed of the machine, the elastic coefficient of the reset spring and the compression speed of the hydraulic cylinder were the main influencing factors of the inter-plant obstacle avoidance mower. The orthogonal test was designed and the optimal solution of the three test factors was determined. The optimal solution is taken for further field test verification. The results show that when the tractor forward speed is 1.5 km∙h⁻¹, the hydraulic cylinder compression speed is 225 mm∙s⁻¹, and the elastic coefficient of the reset spring is 29 N∙mm⁻¹, the average leakage rate between the orchard plants is 7.64%, and the obstacle avoidance pass rate is 100%. The working stability is strong and meets the design requirements. Full article

Planar underactuated mechanical systems have been a popular research issue in the area of mechanical systems and nonlinear control. This paper reviews the current research status of control methods for a class of planar underactuated manipulator (PUM) systems containing a single passive joint. Firstly, the general dynamics model and kinematics model of the PUM are given, and its control characteristics are introduced; secondly, according to the distribution position characteristics of the passive joints, the PUM is classified into the passive first joint system, the passive last joint system, and the passive intermediate joint system, and the analysis and discussion are carried out in respect to the existing intelligent control methods. Finally, in response to the above discussion, we provide a brief theoretical analysis and summarize the challenges faced by PUM, i.e., uncertainty and robustness of the system, unified control methods and research on underactuated systems with uncontrollable multi-passive joints; at the same time, the practical applications have certain limitations that need to be implemented subsequently, i.e., anti-jamming, multi-planar underactuated robotic arm co-control and spatial underactuated robotic arm system development. Aiming at the above challenges and problems in the control of PUM systems, we elaborate on them in points, and put forward the research directions and related ideas for future work, taking into account the contributions of the current work. Full article

Due to the complex growth positions of dragon fruit and the difficulty in robotic picking, this paper proposes a six degrees of freedom dragon fruit picking robot and investigates the manipulator’s motion characteristics to address the adaptive motion issues of the picking manipulator. Based on the agronomic characteristics of dragon fruit cultivation, the structural design of the robot and the dimensions of its manipulator were determined. A kinematic model of the dragon fruit picking robot based on screw theory was established, and the workspace of the manipulator was analyzed using the Monte Carlo method. Furthermore, a dynamic model of the manipulator based on the Kane equation was constructed. Performance experiments under trajectory and non-trajectory planning showed that trajectory planning significantly reduced power consumption and peak torque. Specifically, Joint 3’s power consumption decreased by 62.28%, and during the picking, placing, and resetting stages, the peak torque of Joint 4 under trajectory planning was 10.14 N·m, 12.57 N·m, and 16.85 N·m, respectively, compared to 12.31 N·m, 15.69 N·m, and 22.13 N·m under non-trajectory planning. This indicated that the manipulator operates with less impact and smoother motion under trajectory planning. Comparing the dynamic model simulation and actual testing, the maximum absolute error in the joint torques was −2.76 N·m, verifying the correctness of the dynamic equations. Through field picking experiments, it was verified that the machine’s picking success rate was 66.25%, with an average picking time of 42.4 s per dragon fruit. The manipulator operated smoothly during each picking process. In the study, the dragon fruit picking manipulator exhibited good stability, providing the theoretical foundation and technical support for intelligent dragon fruit picking. Full article

As a significant subset of unmanned underwater vehicles (UUVs), autonomous underwater vehicles (AUVs) possess the capability to autonomously execute tasks. Characterized by its flexibility, cost-effectiveness, extensive operational range, and robust environmental adaptability, AUV has emerged as the primary technological apparatus for deep-sea exploration and research. In this paper, we present the design of a 10,000 m class AUV equipped with capabilities such as fixed-depth navigation, regional autonomous cruising, full-depth video recording, and temperature and salinity profiling. Initially, we outline the comprehensive design of the AUV, detailing its structural configuration, system components, functional module arrangement, and operational principles. Subsequently, we compute the hydrodynamic parameters using a spatial kinematics model. Finally, the AUV designed in this paper is tested for its functions and performance, such as fixed-depth sailing, maximum speed, and maximum diving depth, and its reliability and practicability are verified. Full article

The impact of ore-rock blocks on the shaft wall of a vertical ore pass is a crucial cause of shaft wall damage and failure. Based on the structure and parameters of the ore pass in a case mine, the first collision’s position of the ore-rock block with respect to the ore pass wall and the angle between the impacting direction of the ore-rock block and the horizontal plane before and after the collision are investigated via a kinematic analysis. The normal and tangential analysis models of ore rock impacting the shaft wall are established and analyzed based on contact mechanics. The results show that: (1) based on the kinematic analysis of ore rock moving in the ore pass and on the colliding condition of the ore-rock block the first time that it collides with the ore pass wall, the coordinates and angles of the collision are proposed; (2) the impacting process of ore rock is categorized into elastic compression, elastic–plastic compression, and rebound of the shaft wall material. The relationship between the normal impact force and the penetrating depth is determined, and the slipping distance of the ore-rock block along the shaft wall and the lost volume of the shaft material are established. (3) The wall material’s normal, tangential, and total restitution coefficient is acquired. (4) The total lost volume during the collision is obtained through the analysis and solution of the model. (5) Based on the characteristics and parameters of the ore pass in the case mine, the influence of the impact velocity and angle of the ore-rock block on the restitution coefficient, maximum normal intrusion depth, maximum tangential displacement, and volume loss of the shaft wall are analyzed by using relevant formulas. Full article

In the study and design of planar mechanisms, graphical techniques for solving kinematic analysis/synthesis and kinetostatics problems have regained interest due to the availability of advanced drawing tools (e.g., CAD software). These techniques offer a deeper physical understanding of a mechanism’s behavior, which can enhance a designer’s intuition and help students develop their skills. Geometric Constraint Programming (GCP) is the term used to describe this modern approach to implementing these techniques. GeoGebra is an open-source platform designed for the interactive learning and teaching of mathematics and related STEM disciplines. It offers an object-oriented programming language and a wide range of geometric tools that can be leveraged to implement GCP. This work presents a systematic technique for studying and designing planar linkages, based on Assur’s groups and GeoGebra’s tools. Although some kinematic analyses and syntheses of planar linkages using GeoGebra have been previously introduced, the proposed systematic approach is novel and could serve as a guide for implementing similar problem-solving methods in other graphical environments. Several case studies will be presented to illustrate this novel approach in detail. Full article

This paper proposes DigitalUpSkilling, a novel IoT- and AI-based framework for improving and personalising the training of workers who are involved in physical-labour-intensive jobs. DigitalUpSkilling uses wearable IoT sensors to observe how individuals perform work activities. Such sensor observations are continuously processed to synthesise an avatar-like kinematic model for each worker who is being trained, referred to as the worker’s digital twins. The framework incorporates novel work activity recognition using generative adversarial network (GAN) and machine learning (ML) models for recognising the types and sequences of work activities by analysing an individual’s kinematic model. Finally, the development of skill proficiency ML is proposed to evaluate each trainee’s proficiency in work activities and the overall task. To illustrate DigitalUpSkilling from wearable IoT-sensor-driven kinematic models to GAN-ML models for work activity recognition and skill proficiency assessment, the paper presents a comprehensive study on how specific meat processing activities in a real-world work environment can be recognised and assessed. In the study, DigitalUpSkilling achieved 99% accuracy in recognising specific work activities performed by meat workers. The study also presents an evaluation of the proficiency of workers by comparing kinematic data from trainees performing work activities. The proposed DigitalUpSkilling framework lays the foundation for next-generation digital personalised training. Full article

The aim of this work was to perform a simulation analysis of the dynamics of a freight wagon with a variant vibration damping: dry friction and viscous damping. The following mathematical models of the damping characteristics are presented: the Maxwell model and the Kolsch model. The differences among the types of damping were first analyzed based on the dynamic responses of the 1 DOF model. Simulation studies were then carried out in a VI-Rail environment with the use of S-curved track models comprising short straight sections connecting the curves. The track models differed in the values of curve radii, cant, and length, which made it possible to run at different speeds. The multibody model of the vehicle represents a typical two-axle freight wagon. The dynamics of the wagon model were investigated for two states: empty and laden. Standard kinematic and dynamic values were compared in order to investigate if the nature of the damping has a significant impact on the dynamic properties of a freight wagon. The analysis of the simulation study showed that replacing dry friction damping with the viscous one can generally reduce forces acting on the wheel–rail contact, which, in turn, can be related to improving the running behavior of wagons while reducing the negative impact on the track. Full article

The efficient, economical, and sustainable production of biodiesel from waste cooking oils (WCOs) depends on the availability of simple, rapid, and low-cost methods to test the quality of potential feedstocks. The aim of this study was to establish the applicability of stochastic modeling of e-nose profiles in the evaluation of recycled WCO characteristics. Olfactory profiles of 10 WCOs were determined using a Sensigent Cyranose^® 320 chemical vapor-sensing device with a 32 sensor-array, and a stepwise multiple linear regression (MLR) analysis was performed to select stochastic parameters (explanatory variables) for inclusion in the final predictive models of the physicochemical properties of the WCOs. The most important model parameters for the characterization of WCOs were those relating to the time of inception of the e-nose signal “plateau” and to the concentration of volatile organic compounds (VOCs) in the sensor region. A comparison of acid values, peroxide values, water contents, and kinematic viscosities predicted by the MLR models with those determined by conventional laboratory methods revealed that goodness of fit and predictor accuracy varied from good to excellent, with all metric values >90%. Combining e-nose profiling with stochastic modeling was successful in predicting the physicochemical characteristics of WCOs and could be used to select suitable raw materials for efficient and sustainable biodiesel production. Full article

This article delineates the enhancement of an autonomous navigation and obstacle avoidance system for a quadruped robot dog. Part one of this paper presents the integration of a sophisticated multi-level dynamic control framework, utilizing Model Predictive Control (MPC) and Whole-Body Control (WBC) from MIT Cheetah. The system employs an Intel RealSense D435i depth camera for depth vision-based navigation, which enables high-fidelity 3D environmental mapping and real-time path planning. A significant innovation is the customization of the EGO-Planner to optimize trajectory planning in dynamically changing terrains, coupled with the implementation of a multi-body dynamics model that significantly improves the robot’s stability and maneuverability across various surfaces. The experimental results show that the RGB-D system exhibits superior velocity stability and trajectory accuracy to the SLAM system, with a 20% reduction in the cumulative velocity error and a 10% improvement in path tracking precision. The experimental results also show that the RGB-D system achieves smoother navigation, requiring 15% fewer iterations for path planning, and a 30% faster success rate recovery in challenging environments. The successful application of these technologies in simulated urban disaster scenarios suggests promising future applications in emergency response and complex urban environments. Part two of this paper presents the development of a robust path planning algorithm for a robot dog on a rough terrain based on attached binocular vision navigation. We use a commercial-of-the-shelf (COTS) robot dog. An optical CCD binocular vision dynamic tracking system is used to provide environment information. Likewise, the pose and posture of the robot dog are obtained from the robot’s own sensors, and a kinematics model is established. Then, a binocular vision tracking method is developed to determine the optimal path, provide a proposal (commands to actuators) of the position and posture of the bionic robot, and achieve stable motion on tough terrains. The terrain is assumed to be a gentle uneven terrain to begin with and subsequently proceeds to a more rough surface. This work consists of four steps: (1) pose and position data are acquired from the robot dog’s own inertial sensors, (2) terrain and environment information is input from onboard cameras, (3) information is fused (integrated), and (4) path planning and motion control proposals are made. Ultimately, this work provides a robust framework for future developments in the vision-based navigation and control of quadruped robots, offering potential solutions for navigating complex and dynamic terrains. Full article