KR20200103341A - Method for evauating a maintanance of machine - Google Patents

Abstract

The present invention relates to a mechanical facility maintenance evaluation method, and more particularly, to a mechanical facility maintenance evaluation method that can evaluate the suitability of maintenance work of a mechanical facility. The objective of the present invention is to provide a mechanical facility maintenance evaluation method that can evaluate the suitability of maintenance work of a mechanical facility. According to a desirable embodiment of the present invention, the mechanical facility maintenance evaluation method comprises the following steps of: calculating, by a suitability evaluation part, an actual limit life of a machine on which maintenance has been performed after maintenance of the machine; calculating, by the suitability evaluation part, the maintenance suitability of the machine; and determining whether maintenance is suitable based on whether the maintenance suitability is less than or equal to a preset rate. According to the present invention, a machine operator can be well aware of the maintenance suitability and use the machine up to the virtual limit life through maintenance by evaluating the maintenance suitability based on the virtual limit life.

Description

METHOD FOR EVAUATING A MAINTANANCE OF MACHINE

The present invention relates to a maintenance evaluation method of mechanical equipment, and more particularly, to a maintenance evaluation method of a mechanical equipment capable of evaluating the appropriateness of maintenance work of the mechanical equipment.

The reliability of a machine refers to the characteristic (or probability of operating) that a component, product or system maintains a designed function without failure under a given operating environment (operation) condition for a required period of time.

1 is a diagram for explaining the concept of reliability of a machine (source: Korea Institute of Machinery and Materials Reliability Evaluation Center). 1, in the commercialization stage of a product, reliability evaluation comprehensively evaluates required performance, environmental resistance, life (durability), safety, etc., and analyzes failures and life problems occurring in this process to improve design and performance or reliability. It means a'comprehensive quality assurance' system that supports certification.

Test evaluation for reliability certification includes i) design of life test conditions, analysis of life data, and life test including acceleration tests that are tested under conditions harsher than use conditions to shorten test time. ii) Vibration, temperature, acceleration, dust, impact, etc. Iii) Tensile, compression, fatigue test, impulse test and withstand pressure test, performance test including performance test of driving device efficiency, performance test of various machinery and megatronic parts iv) 3D shape measurement, It is made through precise measurement including measurement of flatness and surface roughness.

Products that pass such reliability certification are commercialized and installed and operated on site.

However, the reason that the product installed on the site is operated under conditions different from the test and evaluation conditions, the reason why the maintenance/repair of the product is not appropriate, other mechanical properties that are not identified, and the reason that there are factors that are not reflected in the test evaluation conditions, etc. As a result, the lifetime guaranteed by the manufacturer may not be guaranteed. In addition, product defects, human accidents, and economic losses occur due to unexpected mechanical defects.

In order to prevent accidents caused by such mechanical defects, various techniques for monitoring the condition of machine facilities have been proposed.

Korean Patent No. 10-1797402 proposes a technique for diagnosing mechanical defects based on frequency analysis and learning functions.

Korean Patent Registration No. 10-1936283 measures index data on mechanical defects, matches the failure history and cause, and stores them in time series, extracts a plurality of preset feature values for diagnosis from the index data, and extracts the features. It classifies the type of defect through machine learning on the indicator data using the value, receives newly inputted time-series indicator data of the deterioration process for the facility to be measured for defects, and is preset for prediction from the newly input indicator data of the deterioration process. Extracting a plurality of feature values, clustering the deterioration process using the extracted feature values, and generating a regression model by extracting a predictor within the classified section, and calculating the residual life of the facility to predict defects using the generated regression model. Suggest a technique.

As such, the existing technology is a method of determining whether a machine facility is defective or predicting its lifespan using various algorithms. Machine facility monitoring technology has evolved as a technology that predicts the failure and life of mechanical facilities by establishing a network (for example, an IOT network) to collect status information of current machine facilities and analyzing the status information collected through the network. Are doing. Big data technology and artificial intelligence technology are being actively applied to predict failure and lifespan.

However, there is still incomplete failure and life prediction technology. This is because mechanical properties that are not identified and factors that are not reflected in the test evaluation conditions must necessarily exist in the machine equipment. And, the advancement of the failure and life prediction technology incurs a corresponding cost and acts as a factor that increases the price of a machine facility or a monitoring facility.

In addition, it is difficult in the market environment to develop precision technology for predicting failure and life of all mechanical equipment.

Following the current trend of the 4th industry, various facilities failure and life prediction technologies using big data technology, artificial intelligence technology, and sensor network technology are emerging in various industrial fields.

There is a need for technology to solve the incompleteness of the mechanical equipment diagnosis technology in the transitional stage of the failure and life prediction technology for the establishment of advanced mechanical equipment diagnosis technology.

In order to use the machine equipment for a long time and prevent unexpected accidents, maintenance of the machine equipment is carried out periodically. Through maintenance, the performance of actual machine cost can be improved compared to before maintenance. However, it is impossible to evaluate how appropriately the maintenance was performed.

1. Korean Patent Registration No. 10-1797402 (Announcement date: 2017.11.15, Machine defect diagnosis method and device) 2. Korean Patent Registration No. 10-1936283 (Announcement date: 2019.1.8, Diagnosis and prediction method for mechanical defects)

An object of the present invention is to provide a method for evaluating maintenance of mechanical equipment capable of evaluating the suitability of maintenance of the mechanical equipment.

According to a preferred embodiment of the present invention, a method for evaluating maintenance of a machine facility includes: calculating, by a conformance evaluation unit, an actual limit life of the machine maintained after maintenance of the machine; Calculating, by a suitability evaluation unit, a degree of suitability for maintenance of the machine; And determining whether maintenance is suitable based on whether or not the maintenance suitability is equal to or less than a preset analogy.

Here, the suitability evaluation unit is the following equation,

Where ta = the difference between the virtual limit life and the actual limit life before maintenance

According to, the suitability of maintenance can be calculated.

In addition, the suitability evaluation unit may determine that maintenance is good if the calculated suitability of the maintenance is less than or equal to a preset ratio.

In the present invention, by predicting the remaining life of the machine using the virtual life curve and the measured life curve, it is possible to prevent damage due to delay in maintenance and repair due to the uncertainty of the remaining machine life prediction technology.

According to the present invention, by evaluating the suitability of maintenance based on the virtual limit life, it is possible to make the machine operator well aware of the maintenance suitability, and through the maintenance, the machine can be used up to the virtual limit life.

1 is a diagram for explaining a reliability concept of a machine.
2 is a schematic diagram of a machine monitoring system in which the present invention is operated.
3 is a diagram for describing a method for diagnosing an abnormality and evaluating an apparatus according to an exemplary embodiment of the present invention.
4 is a diagram for explaining conformity evaluation according to an exemplary embodiment of the present invention.
5 is a flowchart of a method for evaluating maintenance of a mechanical facility according to an exemplary embodiment of the present invention.

In the present invention, various modifications may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and described in detail. However, this is not intended to limit the present invention to a specific embodiment, it is to be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention.

In describing each drawing, similar reference numerals have been used for similar elements. In describing the present invention, when it is determined that a detailed description of a related known technology may obscure the subject matter of the present invention, a detailed description thereof will be omitted.

Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. These terms are used only for the purpose of distinguishing one component from another component.

For example, without departing from the scope of the present invention, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

The term and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

When a component is referred to as being "connected" or "connected" to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in the middle. Should be.

On the other hand, when a component is referred to as being "directly connected" or "directly connected" to another component, it should be understood that there is no other component in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention.

Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present application, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof, does not preclude in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in this application. Does not.

Hereinafter, a machine monitoring device according to a preferred embodiment of the present invention will be described with reference to the accompanying drawings. 2 is a schematic diagram of a machine monitoring system in which the present invention is operated. 3 is a diagram for describing a method for diagnosing an abnormality and evaluating an apparatus according to an exemplary embodiment of the present invention. 4 is a diagram for explaining conformity evaluation according to an exemplary embodiment of the present invention.

Referring to FIG. 2, the machine monitoring system may include a machine 10 and a machine monitoring device 20.

First to nth sensors 11-1, 11-2, ..., 11-n, hereinafter, collectively referred to as '11' may be installed at each of the plurality of points of the machine 10. The sensor 11 may be installed at a location (enclosure, inside the enclosure, rotation shaft, pump inlet, etc.) for sensing evaluation items (vibration, temperature, rotation speed, pressure, etc.) for reliability certification. The sensor 11 may be installed at a position (a machine case for vibration detection, a blade shaft for rotational speed detection) for detecting factors affecting the target life of the machine.

The machine monitoring device 20 includes a raw data acquisition unit 21, an actual measurement data acquisition unit 22, a life curve generation unit 23, an abnormality diagnosis unit 24, a device evaluation unit 25, and a conformity evaluation unit 26. ), a display unit 27 may be included.

The raw data acquisition unit 21 can acquire raw data for generating a virtual life curve to be described later and generate a virtual life curve. In this case, the raw data may be information input from the outside. The raw data may be time-series sensing data for an evaluation item extracted in an evaluation step for reliability authentication. The raw data acquisition unit 21 may generate a virtual life curve by extending the time-series sensing data on the evaluation items extracted in the evaluation step for reliability certification to a target life span (eg, 10 years). . Time-series sensing data for an evaluation item extracted in an evaluation step for reliability certification may be sensing data for a life test. Alternatively, a virtual life curve for the target life span prepared by the manufacturer of the machine through experiment or simulation is provided to the raw data acquisition unit 21, and the raw data acquisition unit 21 is used as a virtual life curve for machine diagnosis to be described later. Can be used. The raw data acquisition unit 21 receives the virtual life curve generated by substituting the initial value for the test item of the reliability test extracted from the machine into a preset life function, and converts the received virtual life curve into a virtual life curve for machine diagnosis. Can be used as a life curve.

The measured data acquisition unit 22 may acquire sensing data from the sensor 11 in real time.

The life curve generator 23 may generate a measured life curve using real-time sensing data acquired from the sensor 11.

Referring to FIG. 3, the measured life curve may be generated in the form of a curve function through a known curve approximation technique using real-time sensing data collected through the sensor 11 for a preset period after installation of the machine. The measured life curve may be updated every time a preset update period elapses or in real time. In this case, the measured life curve may be generated by approximating the sensing data from the time of installation of the machine to the time of update. The measured life curve may be for the whole machine, part of the machine, or parts, and at least one may be provided for each machine.

In FIG. 3, the virtual life curve refers to a virtual life curve generated by the raw data acquisition unit 21. The virtual life curve can be created based on sensing data for test items under the reliability test conditions of an accredited reliability certification body. The imaginary life curve may be a simulation result for a test item in a reliability test. The virtual life curve may be generated by substituting an initial value for the test item of the reliability test extracted from the machine into a preset life function. The virtual life curve may be for the whole machine, part of the machine, or parts, and at least one may be provided for each machine. The measured life curve may be information reflecting all environments (ambient temperature, actual machine operating time, vibration, maintenance, etc.) encountered when a machine is installed and operated on site.

In FIG. 3, the reference performance value may be a performance value of the entire machine, part of the machine, or parts guaranteed at the time of machine manufacturing provided by the machine manufacturer. The reference performance value may be provided for the entire machine, part of the machine, or for each part.

In FIG. 3, the critical performance value may be a performance value of the whole machine, part of the machine, or parts indicating when the machine or part should be replaced.

In FIG. 3, t may be a machine operating time.

In FIG. 3, tl1 may mean a virtual limit life according to a virtual life curve. In FIG. 3, tl2 may mean an actual limit life according to the measured life curve.

The abnormality diagnosis unit 24 may diagnose a machine condition and provide an alarm using the virtual life curve and the measured life curve. The abnormal state may mean a state in which any one of the monitoring items (reliability evaluation items) using the sensor 11 can reach the threshold performance value after the lapse of a preset threshold time.

The abnormality diagnosis unit 24 may grasp a time point tl2 at which the measured life curve reaches the critical performance value by using the measured life curve generated by the life curve generator 11 in real time. And, the remaining life can be determined according to the following equation.

here,

t12 = point at which the measured life curve reaches the critical performance value (in other words, the maximum operating time from the point of machine installation)

tnow = usage time to date

And, the remaining life can be corrected according to the following equation.

In addition, the abnormality diagnosis unit 24 may provide an alarm for maintenance when the corrected remaining life is less than or equal to a preset threshold remaining life. As described above, the present invention uses the above equation in consideration of the uncertainty of the remaining life arising from the difference between the virtual life curve and the measured life curve in the section defined by the reference performance value and the critical performance value, which are the criteria for life calculation. This can shorten the remaining life. As a result, damage due to delays in maintenance and repair time can be prevented due to uncertainty in the machine remaining life prediction technology. In addition, the present invention can prevent frequent maintenance and repair to ensure the uncertainty of the machine's remaining life prediction technology, and guide the maintenance and repair timing with a margin based on an appropriate standard of uncertainty.

The machine evaluation unit 25 may calculate a difference (Δx) between the performance value according to the real-time virtual life curve and the performance value according to the measured life curve. In addition, when the performance value according to the measured life curve is smaller than the performance value according to the real-time virtual life curve by more than a preset threshold difference, the machine evaluation unit 25 may provide an alarm notifying of product defects to the outside.

By determining product defects based on the difference between the performance value according to the real-time virtual life curve and the performance value according to the measured life curve, it is possible to prevent accidental damage caused by product defects by the machine user, and the machine user is more secure. And can buy a machine.

Referring to FIG. 4, the suitability evaluation unit 26 may calculate an actual limit life at the time when maintenance is completed (T maintenance). To this end, the suitability evaluation unit 26 substitutes the performance value at the time of completion of maintenance into the actual life curve spinning equation generated by the life curve generation unit 23 before maintenance (in other words, , The actual life curve spinning equation generated by the life curve generation unit 23 before maintenance is moved by Δx in the positive (+) direction based on the performance value axis) After maintenance, the actual life curve equation can be generated. In addition, the suitability evaluation unit 26 may calculate the limit life after maintenance (tl2-1) using the actual life curve equation after maintenance. And, by calculating the difference between the limit life after maintenance (tl2-1) and the limit life before calibration (tl2), the limit life extended by maintenance (t extension life) can be calculated. And, it is possible to calculate the suitability of maintenance according to the following equation.

Where ta = the difference between the virtual limit life and the actual limit life before maintenance

The suitability evaluation unit 26 may determine that maintenance is good if the suitability of maintenance is less than or equal to a preset ratio (30%). like this. According to the present invention, by evaluating the suitability of maintenance based on the virtual limit life, it is possible to make the machine operator well aware of the maintenance suitability, and through the maintenance, the machine can be used up to the virtual limit life.

The life curve generator may continuously update the actual life curve equation after maintenance by using real-time sensing data collected from the sensor 11 after maintenance.

The display unit 27 may display the graphs of FIGS. 3 and 4 in real time. The display unit 27 is an alarm for maintenance and repair. Product failure alarm. The result of the conformity assessment for maintenance can be output as a video.

Hereinafter, a method for evaluating maintenance of a mechanical facility according to an exemplary embodiment of the present invention will be described with reference to FIGS. 1 to 5. 5 is a flowchart of a method for evaluating maintenance of a mechanical facility according to an exemplary embodiment of the present invention. The configuration of the machine monitoring device described above may be more clearly defined by the following description.

First, the suitability evaluation unit 26 may calculate the actual limit life of the machine maintained after maintenance of the machine (S51). Details on the actual limit life of the machine maintained after maintenance may be as previously seen.

Then, the suitability evaluation unit 26 may calculate a maintenance suitability for the machine (S52).

The suitability evaluation unit 26 is the following equation,

Where ta = the difference between the virtual limit life and the actual limit life before maintenance

According to, the suitability of maintenance can be calculated. Details on the calculation of the fitness may be as previously described.

In addition, the suitability evaluation unit 26 may determine whether or not the maintenance suitability is equal to or less than a preset ratio (S53).

If it is determined in S53 that the maintenance suitability is equal to or less than a preset ratio, the suitability evaluation unit 26 may determine that the maintenance is suitable (S54).

In contrast, if it is determined in S53 that the maintenance suitability exceeds a preset ratio, it may be determined that maintenance is inappropriate (S55).

In this case, the suitability evaluation unit 26 may provide a determination result of the maintenance suitability through the display unit 27.

10: machine
11-1, 11-2, ..., 11-n: sensor
20: mechanical monitoring device
21: raw data acquisition unit
22: measurement data acquisition unit
23: life curve generator
24: abnormality diagnosis unit
25: machine evaluation unit
26: Conformity Assessment Department
27: display unit

Claims (3)

Calculating, by a suitability evaluation unit, an actual limit life of the machine maintained after maintenance of the machine;
Calculating, by a suitability evaluation unit, a degree of suitability for maintenance of the machine;
And determining whether maintenance is suitable based on whether the maintenance suitability is equal to or less than a preset analogy.
The method of claim 1,
The conformity evaluation unit is the following equation,

Where ta = the difference between the virtual limit life and the actual limit life before maintenance
Maintenance evaluation method of a mechanical equipment, characterized in that calculating the suitability of maintenance according to.
The method of claim 2,
And the suitability evaluation unit determines that maintenance is good if the calculated suitability of the maintenance is less than or equal to a preset ratio.

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