Test sample selection method for maintenance time verification test of rail transit product

Abstract

A test sample selection method for a maintenance time verification test of a rail transit product comprises the following steps: S1, determining the total failure rate of each component in each failure mode according to the number and failure rate of each component in the rail transit product and the mode proportion of each component in each failure mode; s2, determining a relative proportion and an accumulated proportion of each component in each fault mode according to the total fault rate of each component in each fault mode; s3, determining an alternative interval of the test sample according to the relative proportion and the cumulative proportion of each component in each fault mode; and S4, randomly selecting one test sample from the alternative interval as a test sample of the maintenance time verification test. Compared with the prior art, the method has the advantages that the selection of the maintenance task sample is directly associated with the reliability level and the fault characteristic of the product, so that the selection of the sample meets the task requirement of the product under the actual use condition, and the maintenance time evaluation and verification result is more accurate and credible.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of rail transit product maintenance technology, and particularly relates to a test sample selection method for a maintenance time verification test of a rail transit product. BACKGROUND

[0002] The maintenance time verification test of a rail transit product is a key link for ensuring safe, efficient and economic operation of a rail transit system.

[0003] The test sample of the maintenance time verification test is different from the general meaning of the test sample, and the general test sample generally refers to a component, while the test sample of the maintenance test refers to a maintenance task performed on the component. The effectiveness and reliability of the maintenance test result are determined by the test sample (i.e., the selection of the maintenance task) which can reflect the actual level (here, the level includes the content of the maintenance task and the execution frequency of the maintenance task) in the actual maintenance process, so the selection of the sample must be carefully considered in the maintenance verification test to ensure the scientificity and practicality of the test result.

[0004] The test sample of the existing maintenance time verification test generally adopts a random sampling method, which has at least the following disadvantages: 1. The proportion of failure modes and the difference in failure rate are not considered: the random sampling method generally performs equal probability sampling based on the number of components or tasks, without combining the actual product failure data (such as failure rate and failure mode proportion). For example, the maintenance task of a high-failure-rate component may be underestimated due to the randomness of random sampling, resulting in a sample that cannot truly reflect the maintenance requirements of the high-frequency failure scenario in the actual maintenance. 2. The reliability differences of different car types and line conditions are ignored: the failure modes and frequencies of rail transit products are significantly different under different car types and line conditions. The random sampling method cannot adjust the sample proportion according to the actual working conditions, which may cause the sample to deviate from the target use scenario, and the test result has limited guiding significance for actual maintenance. 3. The accuracy of the data is limited, and evaluation bias cannot be associated with product reliability characteristics: maintenance time evaluation needs to be based on the real failure characteristics of the product, but the random sampling method does not combine the sample selection with the component reliability database, FMEA analysis results, etc. For example, a component has a high failure rate due to design defects in actual use, but random sampling may not preferentially select the maintenance task of this component, so that the test data cannot accurately reflect the maintenance time, and the maintenance time evaluation deviates from the actual demand. SUMMARY

[0005] The present application provides a test sample selection method for a maintenance time verification test of a rail transit product to solve the problem that the random sampling method used in the prior art cannot reflect the actual level in the actual maintenance process, resulting in inaccurate test results.

[0006] To achieve the above purpose, the present application adopts the following technical solutions.

[0007] In one aspect, a test sample selection method for a maintenance time verification test of a rail transit product is provided, comprising the following steps:

[0008] S1, determining the overall failure rate of each component under each failure mode according to the number of components, the failure rate and the mode proportion of each component under each failure mode in the rail transit product;

[0009] S2, determining the relative proportion and cumulative proportion of each component under each failure mode according to the overall failure rate of each component under each failure mode;

[0010] S3, determining the candidate interval of the test sample according to the relative proportion and cumulative proportion of each component under each failure mode;

[0011] S4, randomly selecting a test sample in the candidate interval as the test sample of the maintenance time verification test.

[0012] The above method sets the numerical interval corresponding to different maintenance tasks based on the failure mode proportion, failure rate proportion and cumulative proportion, and then selects the test sample by generating a random number in the interval. The present application directly associates the selection of the maintenance task sample with the reliability level and failure characteristics of the product itself, so that the selection of the sample meets the task requirements of the product under actual working conditions, thereby ensuring that the maintenance time evaluation and verification results are more accurate and reliable. Secondly, the present application retains the randomness of extracting test samples, and to some extent, increases the selection probability of test samples with high failure cumulative proportion, and strengthens the monitoring of maintenance tasks for failure modes with high failure rate. Compared with the traditional pure random sampling method, it is more scientific and reasonable.

[0013] It should be noted that when the test sample size is given in the test scheme, step S4 can be repeatedly executed according to the sample size requirement until the sample size requirement is met; when the test scheme is sequential (i.e., the test sample size is not given in advance in the test scheme, and it is necessary to determine whether to increase the test sample at any time according to the actual situation in the test process until the test termination condition is met), step S4 can be executed when it is necessary to increase the test sample.

[0014] In some embodiments, the candidate interval P k is (q k-1 , Q k ); wherein, q k is the relative proportion of the kth test sample, Q k is the cumulative proportion of the kth test sample, and Λ k is the overall failure rate of the kth test sample, each test sample corresponding to a failure mode of a component.

[0015] In yet another aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory, the processor executing the computer program to implement the steps of the above method.

[0016] In yet another aspect, a computer readable storage medium is provided, having stored thereon a computer program / instructions, characterized in that the computer program / instructions, when executed by a processor, implement the steps of the above method.

[0017] In yet another aspect, a computer program product is provided, comprising a computer program / instructions, characterized in that the computer program / instructions, when executed by a processor, implement the steps of the above method.

[0018] The present application has at least the following technical effects or advantages: As the types of maintenance tasks that may be generated by rail vehicles are diverse, and the reliability levels under different vehicle models and different line conditions differ greatly, the corresponding maintenance tasks are also different. The sample selection method of the present application can directly associate the selection of maintenance task samples with the reliability level and fault characteristics of the product itself, so that the selection of samples meets the task requirements of the product under actual working conditions, thereby ensuring that the maintenance time evaluation and verification results are more accurate and reliable. Secondly, while retaining the randomness of the extracted test samples, the present application to some extent increases the selection probability of test samples with high fault accumulation ratio, and strengthens the monitoring of maintenance tasks for fault modes with high failure rate, which is more scientific and reasonable compared with the traditional purely random sampling method. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 FIG. 1 is a flowchart of a test sample selection method for a maintenance time verification test of a rail transit product according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the drawings in the specification and specific embodiments.

[0021] Referring to Figure 1 A test sample selection method for a maintenance time verification test of a rail transit product, comprising the following steps: S1, determining the overall failure rate of each component under each fault mode according to the number of components in the rail transit product, the failure rate of each component, and the mode ratio of each component under each fault mode;

[0022] S2, determining the relative proportion and cumulative proportion of each component under each fault mode according to the overall failure rate of each component under each fault mode;

[0023] S3, determining the candidate interval P of the test sample according to the relative proportion and cumulative proportion of each component under each fault mode k ;

[0024] Alternative interval P k for (q k-1 ,Q k );in, q k is the relative proportion of the kth test sample, Q k is the cumulative proportion of the kth test sample, Λ k is the overall failure rate of the kth test sample, and each test sample corresponds to a failure mode of a component.

[0025] S4. Randomly select a test sample in the alternative interval as the test sample for the maintenance time verification test.

[0026] The following describes a specific implementation method by taking the generation of 30 test samples required for a system maintenance time verification test as an example.

[0027] 1) Determine the product configuration tree, which must include at least the component name and loading quantity;

[0028] Assume that the system contains two components, and the quantity of components loaded is shown in the following table:

[0029] Table 1 Product configuration tree example

[0030] Component name Number of cars A 1 B 2

[0031] 2) Determine the failure rate of each component through the component reliability database or actual application data; when using actual application data for calculation, the failure rate λ of the i-th component is i It can be calculated by the cumulative working time T and the cumulative number of failures r of the component.

[0032]

[0033] Where α is the given significance level, which is usually taken as 5%; 2 (α,2r+2) is the quantile corresponding to the right tail probability of the chi-square distribution, which can be looked up in a table or calculated using software such as Excel;

[0034] In this example, it is assumed that the failure rate of component A can be retrieved from the database: A ≤1(FPMK); Component B has worked for 1 million kilometers without any failure. Given a significance level of α = 5%, we can calculate:

[0035]

[0036] 3) Determine the failure mode and proportion of each component. If FMEA analysis results are available in the component reliability database, the failure mode and proportion can be obtained from the FMEA analysis results. If no FMEA analysis results are available, analysis and calculation can be performed based on failure data from actual component operation.

[0037] In this example, it is assumed that the component failure modes and proportions can be found in the FMEA analysis report as shown in the following table:

[0038] Table 2 Failure modes and proportions

[0039]

[0040] 4) Calculate the overall failure rate Λ for each component and each mode separately ij :

[0041] Λ ij =n i λ i β ij

[0042] Where n i is the number of components loaded on the vehicle, and the failure rate λ i and mode proportion β ij Obtained from steps 2) and 3);

[0043] The calculation results of this example are shown in the following table:

[0044] Table 3 Overall failure rate

[0045]

[0046]

[0047] 5) Number each component and each mode one by one in the order of components and modes, and record them as k (k = 1, 2, ...);

[0048] 6) Each component and each mode corresponds to a maintenance task, denoted as T k ;

[0049] 7) According to the corresponding relationship between the number (k) and the component (i) mode (j), the overall failure rate Λ obtained in step 4) is ij under

[0050] The subscript is rewritten as Λ k ; Calculate the relative proportion q of each mode for each component k and cumulative proportion Q k :

[0051]

[0052] 8) define the repair task T k alternative interval P k for (q k-1 , Q k );

[0053] The calculation results of this example are shown in the following table:

[0054] Table 4 Calculation results of steps 5-8

[0055]

[0056] 9) generate a random number p between 0 and 1; determine the test sample S: (S = T k | p e P k )

[0057] 10) When the test sample size is given by the test plan, step 9) can be repeated according to the sample size requirement until the sample size requirement is met; when the test plan is sequential (i.e. the test sample size is not given in advance in the test plan, and whether to increase the test sample size needs to be determined at any time according to the actual situation in the test process until the test termination condition is met), step 9) can be executed when the test sample size needs to be increased.

[0058] In this example, 30 test samples need to be generated, so step 9) needs to be executed 30 times, and the calculation results are shown in the following table:

[0059] Table 5 Final test sample list obtained by calculation

[0060]

[0061]

[0062] The test sample selection method of the present application is not only suitable for products of a single type or condition, but also can comprehensively evaluate the effectiveness of maintenance measures by reasonably selecting samples of different types and under different use conditions. This helps to discover problems that may occur under specific conditions, thereby avoiding similar problems in actual application. In addition, the method is also suitable for sequential test plans, i.e. the test sample size is not given in advance, but is determined at any time according to the actual situation in the test process until the test termination condition is met. This flexibility makes the method better adapt to maintenance time evaluation and verification tests of different scales and complexities.

[0063] In the specification provided herein, a large number of specific details are described. However, it can be understood that embodiments of the present application can be practiced without these specific details. In some examples, well-known methods, structures and techniques are not shown in detail in order not to obscure the understanding of the present specification.

[0064] Similarly, it is to be understood that the embodiments of the present application can be alternately practiced by a single integrated circuit, in different combinations of the embodiments than those explicitly described herein, and in other ways than those specifically set forth in the figures and text making up a part of this disclosure. For example, acts, elements and / or devices can be interchanged with one another and / or combined as a part of other acts, elements and / or devices in other embodiments of the application, in different implementations of embodiments of the application, and in various combinations of hardware and software configured to act as described. Further, it is to be understood that certain embodiments of the present application can be performed by hardware components or can be implemented with components other than those described in the figures. It is therefore contemplated to this effect that the certain embodiments of the present application can be implemented in a variety of ways, including application-specific circuits, computer software programmed for specific uses, or by combinations of hardware and software elements.

[0065] Those skilled in the art understand that the modules or units or groups in the devices in the examples disclosed herein can be arranged in the devices as described in the examples, or alternatively can be located in one or more devices different from the devices in the examples. The modules in the foregoing examples can be combined as one module or can be further divided into a plurality of sub-modules.

[0066] Those skilled in the art understand that the modules in the devices in the examples can be adaptively changed and arranged in one or more devices different from the examples. The modules or units or groups in the examples can be combined as one module or unit or group, and can be further divided into a plurality of sub-modules or sub-units or sub-groups. Except that at least some of such features and / or processes or units are mutually exclusive, any combination of all features disclosed in the specification (including the accompanying claims, abstract and drawings) and all processes or units of any method or device so disclosed can be taken. Unless explicitly stated otherwise, each feature disclosed in the specification (including the accompanying claims, abstract and drawings) can be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0067] Further, those skilled in the art understand that although some of the examples described herein include certain features included in other examples but not others, the combination of features of different examples means within the scope of the present application and forms different examples.

[0068] Further, some of the examples described herein are described as combinations of methods or method elements implemented by a processor of a computer system or by other means for performing the functions of the methods. Accordingly, a processor with the necessary instructions for performing such methods or method elements forms a means for performing the methods or method elements. Further, elements of a device described herein are examples of means for performing the functions performed by elements for which such means is claimed.

[0069] The various techniques described herein can be implemented in connection with hardware or software or, where appropriate, with a combination of both. Thus, the methods and apparatus of the application, or certain aspects or portions thereof, can take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the subject application.

[0070] Where the program code is executed in a machine, such as a computer, the computing device generally includes a processor, a storage medium readable by the processor (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. The storage medium is configured to store program code whose execution implements the methods of the application. The program code can be written in any of various suitable programming languages or combinations of languages.

[0071] In a further embodiment, the computer readable medium comprises a computer data signal embodied in a carrier wave, such as a bit stream, that takes a form in which data bytes are encoded.

[0072] As used herein, unless otherwise indicated, the use of the ordinal adjectives "first", "second", "third", etc., merely to distinguish different instances of a same object, and are not intended to imply that a sequence or order to which the objects are described in herein have some inherently developed order.

[0073] While the application has been described in terms of several embodiments, those skilled in the art will recognize that the application can be practiced with modifications and alterations limited only by the spirit and scope of the claims. Additionally, although the application has been described above in the context of particular embodiments, the application can be practiced with the use of other techniques long familiar to those skilled in the art from other applications. Accordingly, the terms "comprises", "comprising", "including", and "containing" as used throughout the specification are expressly understood and intended to mean including, but not limited to. Also, it will be appreciated by persons skilled in the art that the present application is not limited to what has been presently described and disclosed, but could also include all tools, methods, and techniques that are coming within the scope of the appended claims.

[0074] Finally, it is to be understood that the application is not limited in its application to the details of the construction and the arrangement of the components set forth in the description or illustrated in the drawings. The application is capable of other embodiments and of being practiced or being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and not of limitation.

Claims

1. A test sample selection method for a maintenance time verification test of a rail transit product, characterized in that: The steps include: S1. Determine the overall failure rate of each component under each failure mode based on the number and failure rate of each component in the rail transit product and the proportion of each component under each failure mode; S2. Determine the relative proportion and cumulative proportion of each component under each failure mode based on the overall failure rate of each component under each failure mode; S3. Determine the candidate intervals of the test sample based on the relative proportion and cumulative proportion of each component under each failure mode; S4. Randomly select a test sample in the alternative interval as the test sample for the maintenance time verification test.

2. The test sample selection method for the maintenance time verification test of rail transit products according to claim 1, characterized in that: The candidate interval P k for (q k-1 ,Q k );in, q k is the relative proportion of the kth test sample, Q k is the cumulative proportion of the kth test sample, Λ k is the overall failure rate of the kth test sample, and each test sample corresponds to a failure mode of a component.

3. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method according to claim 1 or 2.

4. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to claim 1 or 2 are implemented.

5. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to claim 1 or 2 are implemented.

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