JP2019020182A - Mechanical structure fault rate prediction system and fault rate predicting device equipped therewith - Google Patents

Abstract

To provide a technique for quickly and comprehensively predicting a fault rate on the weld section of a mechanical structure and a fault rate prediction system in which the technique is implemented.SOLUTION: Provided is a mechanical structure fault rate prediction system equipped with a computing device and a database. The database stores a second parameter that corresponds to a first parameter, the first parameter being a parameter that has a correlation with the state quantity of the mechanical structure, the second parameter being a stochastic parameter that pertains to a change amount of the state quantity of the mechanical structure. The computing device analyzes a response to an external force acting on the mechanical structure and thereby calculates the first parameter, extracts the second parameter corresponding to the first parameter from the database, and calculates the state quantity by the first parameter and the second parameter.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a failure rate prediction system and a failure rate prediction device, and more particularly to a system and device for improving the failure rate prediction of a welded portion of a mechanical structure.

  In recent years, the use environment of machine structures has been diversified, and the use in harsh environments has increased. Along with this, it is required to accurately predict the life of a mechanical structure at the time of designing or operating the mechanical structure. The lifetime of a mechanical structure varies depending on various factors such as the manufacturing method, material structure, residual stress, and shape. The variation directly affects the setting of the safety factor at the time of design and the determination of the repair time at the time of operation. For this reason, it is desired to accurately and efficiently grasp the probabilistic distribution of the lifetime of the mechanical structure, that is, the failure rate.

  As one method for predicting the life of a mechanical structure with high accuracy, a method of analyzing a structural response to an external force by a structural analysis using a finite element analysis is widely used. For example, Patent Document 1 proposes a system that predicts damage inside a material constituting a mechanical structure by structural analysis and evaluates the lifetime of the mechanical structure.

JP 2014-71053 A

  In the technique of Patent Document 1, since the calculation of the failure rate of the entire structure requires calculation time such as performing structural analysis by finite element analysis a plurality of times, there is a problem that it takes time to predict the failure rate. In addition, in the deterministic method that does not include a probabilistic factor, the average value of the life can be evaluated, but it is difficult to evaluate the life probabilistically, and it is sometimes difficult to calculate the failure rate itself.

  Therefore, there is a problem to be solved in terms of improving the reliability of the machine structure by accurately predicting the failure rate.

  The object of the present invention has been made in view of the circumstances of the prior art, and it is possible to improve the reliability of a mechanical structure by accurately and efficiently predicting the failure rate of the mechanical structure. A failure rate prediction system and a failure rate prediction apparatus including the failure rate prediction system are provided.

  The above object is a failure rate prediction system for a machine structure including an arithmetic unit and a database, wherein the first parameter is a parameter having a correlation with the state quantity of the machine structure, and the second parameter is the machine structure The database stores the second parameter corresponding to the first parameter, and the arithmetic unit is configured to store the machine structure The first parameter is calculated by analyzing a response to an external force acting on the first parameter, the second parameter corresponding to the first parameter is extracted from the database, and the first parameter and the second parameter are extracted. This is achieved by a failure rate prediction system that calculates the state quantity using the following parameters.

  According to the present invention, it is possible to accurately and efficiently predict a failure rate of a mechanical structure.

Schematic which shows the flow of the data in the failure rate prediction system of Example 1. FIG. Example of data stored in the database in the first embodiment Display example of failure rate in failure rate prediction system of embodiment 1 Schematic which shows the apparatus provided with the failure rate prediction system of Example 1. FIG. Schematic which shows the flow of the data in the failure rate prediction system of Example 2. Example of data stored in the second database in the second embodiment Schematic which shows the flow of the data in the failure rate prediction system of Example 3. Example of data stored in the third database in the third embodiment Schematic which shows the flow of the data in the failure rate prediction system of Example 4. Schematic which shows the flow of the data in the failure rate prediction system of Example 5.

  Hereinafter, embodiments of a failure rate prediction system to which the present invention is applied and a failure rate prediction device in which the system is mounted will be described with reference to the drawings.

  A failure rate prediction system according to a first embodiment to which the present invention is applied and a failure rate prediction apparatus including the failure rate prediction device will be described with reference to FIGS.

  The failure rate prediction system of the present embodiment predicts the failure rate of the mechanical structure 4 when the external force 5 is repeatedly applied to the target mechanical structure 4 or over a long period of time. When the target mechanical structure 4 is a train, the probability that the vehicle body will crack due to external force 5 such as vibration applied during traveling will be predicted, and repair of the vehicle body will be promoted by prompting repair at an appropriate time. It can prevent failure.

  First, the outline | summary of the failure rate prediction apparatus 20 of a present Example is demonstrated using FIG. As shown here, the failure rate prediction device 20 includes an arithmetic device 30 such as a CPU, an input device 40 such as a keyboard and a mouse, an output device 50 such as a display, a main storage device 60A such as a semiconductor memory, and an auxiliary storage such as a hard disk. The computing device 30 executes a program stored in the main storage device 60A while referring to a later-described database stored in the auxiliary storage device 60B. It implements various functions such as the parameter calculation unit 30b, the second parameter calculation unit 30c, the state quantity calculation unit 30d, the failure rate calculation unit 30e, and the failure rate display unit 30f. Here, the main storage device 60 </ b> A and the auxiliary storage device 60 </ b> B are individually provided, but these may be integrated into one storage device 60.

  Next, the outline of processing executed in the failure rate prediction system 1 which is a main part of the failure rate prediction apparatus 20 will be described with reference to FIG. As shown here, the failure rate prediction system 1 includes an arithmetic device 30 and a database 3. The database 3 is stored in the auxiliary storage device 60B or the storage device 60 described above.

  The arithmetic unit 30 holds in advance a structural model for simulating the failure rate of the mechanical structure 4 (for example, the body structure of a train), and the mechanical structure 4 has a predetermined external force 5 (for example, during traveling). The failure rate of the mechanical structure 4 is predicted from the response 100 (for example, deformation of the structural model, vibration) when the vibration is applied.

  Specifically, the response calculation unit 30a of the calculation device 30 analyzes the response 100 of the structural model of the mechanical structure 4 to the external force 5, and based on the analysis result, the first parameter calculation unit 30b calculates the mechanical structure. A first parameter 7 (for example, a stress intensity factor representing a stress field in the vicinity of the crack tip) having a correlation with a state quantity 6 (for example, a crack length) used for determining whether or not the object 4 has failed is calculated. In the database 3, as shown in FIG. 2, a probabilistic second parameter 8 (for example, the application time length of the external force 5 and the number of repetitions of application) regarding the variation in the change rate of the state quantity 6 corresponding to the first parameter. , The second parameter calculation unit 30 c can extract the second parameter 8 corresponding to the value of the first parameter 7 from the database 3. Thus, in the present embodiment, by using the database 3, the desired second parameter 8 can be obtained in a short time without repeating time-consuming operations such as finite element analysis. Even when the arithmetic device 30 having a low value is used, the high-quality second parameter 8 can be acquired in a short time.

  Then, the state quantity calculation unit 30d calculates the state quantity 6 based on these two types of parameters 7 and 8, and the failure rate calculation unit 30e predicts the failure rate 9 based on the calculated state quantity 6, and finally In addition, the predicted failure rate 9 is displayed on the output device 50 via the failure rate display unit 30f.

  According to the failure rate prediction system using this database 3, the relationship between the usage time / number of times of use and the failure rate of the mechanical structure 4 can be obtained without performing a finite element analysis for the entire mechanical structure 4 multiple times. Can be easily predicted.

  FIG. 3 is an example of a prediction result of the failure rate 9 displayed on the output device 50 such as a display. The input device 40 such as a mouse is operated, “time” is set as the horizontal parameter, and “failure” is set as the vertical parameter. It is a graph displayed when "Rate" is selected. The parameters that can be selected on the vertical axis and the horizontal axis are not limited to these, and “crack length” may be selected on the vertical axis, or “number of repetitions of external force” may be selected on the horizontal axis.

  In this failure rate prediction device 20, the failure rate prediction result by the failure rate prediction system is displayed in an easy-to-understand graph format, so that the simulation worker can easily grasp the future failure rate of the mechanical structure 4. Can do. Furthermore, since the failure rate prediction device 20 recommends the time and number of times when the failure rate exceeds a predetermined threshold as the scheduled repair time or the planned number of repairs, the machine structure 4 can be obtained by performing inspection and repair before reaching this point. Can be prevented, and its safety can be properly maintained.

  As described above, according to the present embodiment, until the state quantity 6 reaches a predetermined value in the mechanical structure 4 without performing the finite element analysis for the entire mechanical structure 4 a plurality of times. Since the time and the number of external force repetitions can be calculated as probabilistic values, the failure rate of the mechanical structure 4 can be predicted efficiently.

  Next, the failure rate prediction system 1 according to the second embodiment will be described with reference to FIGS. In addition, duplication description is abbreviate | omitted about the point which is common in Example 1. FIG.

  The failure rate prediction system 1 of the present embodiment shown in FIG. 5 includes a second database 10 in addition to the database 3 of the first embodiment, and the first parameter calculation unit 30b is a machine element of the machine structure 4. The first parameter 7 corresponding to 11 is extracted from the database 10.

  As shown in FIG. 6, the second database 10 includes a boundary condition (for example, whether the deformation mode is bending or tensile (Tensile) with respect to a mechanical element 11 such as a welded part constituting the mechanical structure 4. ) Or a combination thereof), the shape of the machine element 11 and the first parameter 7 are stored in a correspondence relationship between the three parameters. The first parameter 7 in the machine element 11 corresponding to the response 100 of the machine structure 4 is extracted from the database 10 of the second embodiment, and then the second parameter 8 is extracted from the database 3 in the same manner as in the first embodiment. This is an embodiment in which a state quantity 6 is calculated using various types of parameters, and a failure rate 9 is predicted based on the calculated state quantity 6.

  As a result, the failure rate can be predicted comprehensively for each of the machine elements 11 constituting the mechanical structure 4 in consideration of the boundary conditions and the shape thereof, so that an efficient and comprehensive failure rate can be predicted. Become.

  Next, the failure rate prediction system 1 according to the third embodiment will be described with reference to FIGS. In addition, duplication description is abbreviate | omitted about the point which is common in the above-mentioned Example.

  The failure rate prediction system 1 of the present embodiment shown in FIG. 7 includes a third database 12 in addition to the database 3 of the first embodiment, and the first parameter calculation unit 30b includes a response 100 of the mechanical structure 4. The first parameter 7 corresponding to the operating time 110 is extracted from the third database 12.

  As shown in FIG. 8, the third database 12 stores the correspondence between the response of the machine structure 4 and the first parameter 7 for each operating time of the machine structure 4. The parameter calculation unit 30b extracts the first parameter 7 corresponding to the response 100 of the mechanical structure 4 from the third database 12, and thereafter, the second parameter 8 is extracted from the database 3 as in the first embodiment. In this embodiment, the state quantity 6 is calculated using these two kinds of parameters, and the failure rate 9 is predicted based on the calculated state quantity 6.

  Thereby, detailed failure rate prediction corresponding to the complex response 100 in consideration of the operation time 110 of the mechanical structure 4 becomes possible, and the failure rate prediction is more accurate than the failure rate prediction systems of the first and second embodiments. can do.

  Next, the failure rate prediction system 1 according to the fourth embodiment will be described with reference to FIG. In addition, duplication description is abbreviate | omitted about the point which is common in the above-mentioned Example.

  The arithmetic unit 30 of the failure rate prediction system 1 of the present embodiment shown in FIG. 9 calculates the variation 130 of the state quantity 6 based on the measurement value 120 of the state quantity 6 measured by the machine structure 4 in operation. By storing this variation 130 in the database 3, the second parameter 8 stored in the database 3 is updated, and the state quantity 6 is calculated from the updated second parameter 140 and the first parameter 7. In this embodiment, the failure rate 9 is predicted based on the calculated state quantity 6.

  As a result, it is possible to predict the failure rate with higher accuracy based on the state quantity 6 (for example, crack length, etc.) actually measured on the machine structure 4 in operation, and to perform appropriate repairs. The reliability of the structure 4 can be further improved, and efficient operation and repair are also possible.

  The measurement value 120 of the state quantity 6 may be actually measured by an operator or a measurement drone, or may be measured using a sensor provided in advance in the mechanical structure 4.

  Next, the failure rate prediction system 1 according to the fifth embodiment will be described with reference to FIG. In addition, duplication description is abbreviate | omitted about the point which is common in the above-mentioned Example.

  In the failure rate prediction system 1 of the present embodiment shown in FIG. 10, the failure rate 9 is calculated for each of the plurality of machine elements 11 constituting the machine structure 4 by the arithmetic unit 30. Then, the calculated failure rate 9 value is compared, and the magnitude relationship 150 of the failure rate 9 in the machine element 11 is displayed on the output device 50.

  Thereby, the operator can easily identify the machine element 11 that seems to be the earliest malfunction, and can repair the machine element 11 at an appropriate time, so that the operation and repair of the machine structure 4 can be performed more efficiently. It is possible to judge automatically.

  In addition, this invention is not limited to an above-described Example, Various modifications are included. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Further, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Moreover, it is possible to add, delete, and replace other configurations with respect to the configuration of each embodiment.

DESCRIPTION OF SYMBOLS 1 ... Failure rate prediction system 3, 10, 12 ... Database 4 ... Machine structure 5 ... External force 6 ... State quantity 7, 8 ... Parameter 9 ... Failure rate 11 ... Machine element 20 ... Failure rate prediction device 30 ... Arithmetic device 30a ... Response calculation unit 30b ... first parameter calculation unit 30c ... second parameter calculation unit 30d ... state quantity calculation unit 30e ... failure rate calculation unit 30f ... failure rate display unit 40 ... input device 50 ... output device 60 ... storage device 60A ... main storage device 60B ... auxiliary storage device 100 ... response 110 ... operating time 120 ... measured value of state quantity 130 ... variation 140 of measured state quantity ... corrected second parameter 150 ... relationship of failure rate

Claims (6)

A machine structure failure rate prediction system including a computing device and a database,
The first parameter is a parameter having a correlation with the state quantity of the mechanical structure,
When the second parameter is a stochastic parameter related to variation in the amount of change in the state quantity of the mechanical structure,
The database stores the second parameter corresponding to the first parameter;
The computing device calculates the first parameter by analyzing a response to an external force acting on the mechanical structure, extracts the second parameter corresponding to the first parameter from the database, The failure rate prediction system, wherein the state quantity is calculated from the first parameter and the second parameter. A machine structure failure rate prediction system comprising an arithmetic unit, a first database, and a second database,
The first parameter is a parameter having a correlation with the state quantity of the mechanical structure,
When the second parameter is a stochastic parameter related to variation in the amount of change in the state quantity of the mechanical structure,
The first database stores the second parameter corresponding to the first parameter;
The second database stores data on machine elements constituting the machine structure,
The arithmetic device extracts the data corresponding to the response of the mechanical structure from the second database, calculates the first parameter from the data, and the second parameter corresponding to the first parameter. A failure rate prediction system, wherein a parameter is extracted from the first database, and the state quantity is calculated from the first parameter and the second parameter. A machine structure failure rate prediction system comprising an arithmetic unit, a first database, and a third database,
The first parameter is a parameter having a correlation with the state quantity of the mechanical structure,
When the second parameter is a stochastic parameter related to variation in the amount of change in the state quantity of the mechanical structure,
The first database stores the second parameter corresponding to the first parameter;
The third database stores past operation information of the machine structure,
The arithmetic device extracts the operation information corresponding to the response of the mechanical structure from the third database, calculates the first parameter based on the operation information, and the first parameter corresponding to the first parameter A failure rate prediction system, wherein two parameters are extracted from the first database, and the state quantity is calculated from the first parameter and the second parameter. In the failure rate prediction system according to any one of claims 1 to 3,
The failure rate prediction system, wherein the arithmetic unit corrects the second parameter based on measurement data relating to variation in the state quantity in the mechanical structure. In the failure rate prediction system according to claim 2,
The arithmetic device is a device for predicting a failure rate of a plurality of the machine elements, and calculates a magnitude relationship between the failure rates of the plurality of machine elements. The failure rate prediction system according to any one of claims 1 to 5,
An output device for displaying the failure rate predicted by the failure rate prediction system;
An input device for selecting a display format of the output device;
A failure rate prediction apparatus comprising:

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