Fault modeling and evaluation method and device considering test failure

Abstract

The invention discloses a fault modeling and evaluation method and device considering test failure. The method comprises the following steps: S1, obtaining product information; s2, calculating the credibility weight of the test; s3, establishing a fault propagation relation model considering test failure; s4, establishing a diagnosis data matching library; and S5, evaluating the fault detection capability of the product considering the test failure. According to the graphical modeling method considering the product test failure, the propagation relation from a fault signal of a product component unit to a test, the propagation relation from the fault signal of the test to the component unit, the propagation relation from the fault signal of the test to other tests and the like are described, and compared with a traditional fault model, the established fault model has the advantages that the reliability is high; the method is closer to product reality, and can accurately reflect a fault propagation path under a test failure condition.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis, and in particular to a fault modeling and evaluation method and device taking test failure into consideration. Background Art

[0002] In recent years, model-based system engineering methods have been widely used in the aerospace field at home and abroad, and digital models are playing an increasingly important role in the entire life cycle of product design, production, verification, and use. As an important part of the product digital model, the fault simulation model is an important means of product fault diagnosis design.

[0003] In traditional fault simulation modeling, considering that the test failure rate level is one order of magnitude lower than the product failure rate level, it is usually assumed that the test is completely reliable and the special case of test failure is ignored. However, with the gradual increase in the number of product tests, test failure has become an important factor that cannot be ignored in the design process. Ignoring the test failure phenomenon in the design stage usually leads to the actual product fault diagnosis related indicators being lower than the design value, the product fault diagnosis ability is overestimated, and ultimately the product fails the physical test in the identification and verification stage, greatly increasing the cost of repeated iterative product design.

[0004] In view of the above problems, the present invention proposes a fault modeling and evaluation method taking test failure into consideration, which integrates product failures and test failures into consideration during the product design phase to accurately implement product failure modeling and evaluation analysis. Summary of the invention

[0005] Based on the technical problems existing in the background technology, the present invention proposes a fault modeling and evaluation method and device considering test failure, including the following steps:

[0006] S1: Get product information;

[0007] S2: Calculate the credibility weight of the test;

[0008] S3: Establish a fault propagation relationship model considering test failure;

[0009] S4: Establish a diagnostic data matching library;

[0010] S5: Evaluation of product fault detection capability considering test failures.

[0011] Preferably, in S1, the obtaining of product information specifically includes the following steps:

[0012] The first step is to obtain product component unit information, including component unit name, failure rate, failure signal transmission relationship, etc.

[0013] The second step is to obtain the product test information, including test name, test type, test object, test failure rate (test failure rate), etc.

[0014] The third step is to obtain the fault propagation information of product test failure. The fault propagation information of test failure includes the signal transmission relationship between the test failure fault signal and the product component unit, and the signal transmission relationship between the test fault signal and the test.

[0015] Preferably, in S2, the calculation of the credibility weight of the test specifically includes the following steps:

[0016] In the first step, λm+j is used to represent the failure rate of the jth test, m is the number of product components, and bm+j is used to represent the credibility weight of the jth test. The calculation formula is as follows:

[0017]

[0018] In the second step, the credibility weight index of all tests is calculated according to the above method.

[0019] Preferably, in S3, the establishment of the fault propagation relationship model considering test failure specifically includes the following operation steps:

[0020] The first step is to define the mathematical expression of the fault model;

[0021] The second step is to define the element graphical expression of the fault model;

[0022] The third step is to establish a graphical model of fault propagation relationship considering test failure.

[0023] Preferably, in the first step, the mathematical expression of the fault model is defined as follows:

[0024] G=<V,L>

[0025] V=<C,T>

[0026] L=<(c,c)...(c,t)...(t,c)...(t,t)>

[0027] Where: G represents a directed graph model, that is, a fault propagation relationship model considering test failure;

[0028] V is a node of a directed graph, i.e., a model element, which includes two categories: product component unit C and test T;

[0029] L is the edge of the directed graph, which represents the propagation relationship of the fault signal, including the fault signal propagation relationship between product components (c, c), the fault signal propagation relationship from product components to tests (c, t), the fault signal propagation relationship from tests to product components (t, c), and the fault signal propagation relationship between tests (t, t).

[0030] Preferably, in the second step, the detailed model elements of the fault model represent the fault signal propagation relationship related to the product component unit, including (c, c), (c, t), (t, c); is the fault signal propagation relationship between tests (t, t), indicating that the fault signal of the test on the left side of the dashed arrow can be transmitted to the test on the right side of the dashed line, and the fault signal will no longer continue to propagate downward.

[0031] Preferably, in the third step, the signal transmission relationship establishes a graphical model of the fault propagation relationship taking into account the test failure.

[0033] Preferably, in S4, the establishment of the diagnostic data matching library specifically includes the following steps:

[0034] In the first step, the columns in the diagnostic data matching library represent tests, and the rows represent product components and tests. The possible values ​​of the matrix elements in the database table include: 0, bm+j, which represents the credibility weight of the test. The specific value selection principles are as follows:

[0035] In the second step, if the fault signal of the i-th product component unit can be transmitted to the j-th test through the arrow, then the element dij in the i-th row and j-th column of the diagnosis matrix D = bm+j;

[0036] Step 3: If the fault signal of the i-th test can be transmitted to the j-th test through an arrow, then the element dm+ij in the m+i-th row and j-th column of the diagnosis matrix D is equal to bm+j.

[0037] Step 4: If the fault signal of the i-th product component unit cannot be transmitted to the j-th test through the arrow, the element dij in the i-th row and j-th column of the diagnosis matrix D is 0;

[0038] Step 5: If the fault signal of the i-th test cannot be transmitted to the j-th test through the arrow, the element dm+ij in the m+i-th row and j-th column of the diagnosis matrix D is 0;

[0039] Step 6. According to the above method, all product components and tests are traversed to obtain a complete diagnostic data matching library.

[0040] Preferably, in S5, the establishment of the diagnostic data matching library specifically includes the following steps:

[0041] The first step is to evaluate the diagnosability of product components. The specific process is as follows:

[0042] S1. Calculate the diagnosability pi of the i-th product component unit when a failure occurs. The calculation formula is as follows:

[0043]

[0044] S2, traverse all product components and calculate the diagnosability of each product component when a failure occurs.

[0045] The second step is to evaluate the diagnosability of test failures. The specific process is as follows:

[0046] S1. Calculate the diagnosability qi when the i-th test fails. The calculation formula is as follows:

[0047]

[0048] S2, traverse all tests and calculate the diagnosability index when a failure occurs in each test;

[0049] The third step is to evaluate the fault detection capability of the product considering the test failure. The specific process is as follows;

[0050] S1. Calculate the product fault detection capability index γ considering test failure. The calculation formula is as follows:

[0051]

[0052] S2. Calculate the product fault detection capability index γ considering test failure.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The present invention proposes a graphical modeling method that takes product test failure into consideration, which describes the propagation relationship from the fault signal of the product component unit to the test, the propagation relationship from the fault signal of the test to the component unit, the propagation relationship from the fault signal of the test to other tests, etc. The established fault model is closer to the actual product than the traditional fault model, and can accurately reflect the fault propagation path in the case of test failure;

[0055] 2. Based on the graphical modeling method that takes product test failure into consideration, the present invention designs a fault detection capability evaluation algorithm that takes test failure into consideration, considers the impact of test failure on fault diagnosis capability, and provides a method for calculating the diagnostic capability calculation index. Compared with the traditional fault detection rate index calculation method, it takes into account the uncertainty of test failure, is closer to product reality, and can accurately reflect the fault detection capability in the case of test failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 Shown is a flow chart of the method of the present invention; Figure 2 Shown is a flow chart of obtaining product information of the present invention; Figure 3 The figure shows a flow chart of the present invention for establishing a fault propagation relationship model taking into account test failure; Figure 4 Shown is a flow chart of the product fault detection capability evaluation considering test failures of the present invention; Figure 5 The figure shows the first graphical model diagram of the fault propagation relationship established by the signal transmission relationship of the present invention taking into account the test failure; Figure 6 The figure shows the second graphical model diagram of the fault propagation relationship established by the signal transmission relationship of the present invention taking into account the test failure. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] See also Figure 1-Figure 4 The present invention provides a technical solution: a fault modeling and evaluation method and device considering test failure, comprising the following steps:

[0062] S1: Get product information;

[0063] S2: Calculate the credibility weight of the test;

[0064] S3: Establish a fault propagation relationship model considering test failure;

[0065] S4: Establish a diagnostic data matching library;

[0066] S5: Evaluation of product fault detection capability considering test failures.

[0067] As a further optimized technical solution of the present invention, in S1, the obtaining of product information specifically includes the following steps:

[0068] The first step is to obtain product component unit information, including component unit name, failure rate, fault signal transmission relationship, etc. Among them, the "component unit name" in the first column on the left is required to include all component units of the product. "→" means that the fault signal of the component unit on the left side of the arrow will be transmitted to the component unit on the right side of the arrow, and the fault signal of one component unit can be transmitted to multiple other components;

[0069] The secondary power supply subsystem is composed of a start-up control circuit module, a power detection circuit module, and a DC conversion circuit module; the satellite navigation receiver subsystem is composed of an integrated interface circuit module, a radio frequency receiving circuit module, a quantizer module, an interface module, and a processor module.

[0070]

[0071] The second step is to obtain the product test information, including test name, test type, test object, test failure rate (test failure rate), etc. Among them, the test type includes periodic BIT, power-on BIT, manual test, etc.; the first column on the left is required to cover all product tests; the test object is filled in with the product component unit name, indicating that the test can detect the occurrence of the product component unit failure. The specific information collection is shown in the following table:

[0072]

[0073] The third step is to obtain the fault propagation information of the product test failure, which includes the signal transmission relationship between the test failure fault signal and the product component unit, and the signal transmission relationship between the test fault signal and the test.

[0074] 1. The relationship between the test failure signal and the signal transmission of the product component unit is shown in the following table.

[0075] The first column on the left should cover all the tests of the product;

[0076]

[0077]

[0078] 2. The signal transmission relationship between the test fault signals is shown in the following table. The first column on the left is required to cover all the tests of the product.

[0079]

[0080] As a further optimized technical solution of the present invention, in S2, the calculation of the credibility weight of the test specifically includes the following steps:

[0081] In the first step, λm+j is used to represent the failure rate of the jth test, m is the number of product components, and bm+j is used to represent the credibility weight of the jth test. The calculation formula is as follows:

[0082]

[0083] In the second step, the credibility weight index of all tests is calculated according to the above method, and the credibility weight index of the test is shown in the following table.

[0084]

[0085]

[0086] As a further optimized technical solution of the present invention, in S3, the establishment of the fault propagation relationship model considering test failure specifically includes the following operation steps:

[0087] The first step is to define the mathematical expression of the fault model;

[0088] The second step is to define the element graphical expression of the fault model;

[0089] The third step is to establish a graphical model of fault propagation relationship considering test failure.

[0090] As a further optimized technical solution of the present invention, in the first step, the mathematical expression of the fault model is defined as follows:

[0091] G=<V,L>

[0092] V=<C,T>

[0093] L=<(c,c)...(c,t)...(t,c)...(t,t)>

[0094] Where: G represents a directed graph model, that is, a fault propagation relationship model considering test failure;

[0095] V is a node of a directed graph, i.e., a model element, which includes two categories: product component unit C and test T;

[0096] L is the edge of the directed graph, which represents the propagation relationship of the fault signal, including the fault signal propagation relationship between product components (c, c), the fault signal propagation relationship from product components to tests (c, t), the fault signal propagation relationship from tests to product components (t, c), and the fault signal propagation relationship between tests (t, t);

[0097] The start-up control circuit module, power detection circuit module, DC conversion circuit module, integrated interface circuit module and radio frequency receiving circuit module are represented by F1, F2, F3, F4 and F5 respectively; the control signal test, IPE2PROM test, Interf interface module test, IOC interface test and telemetry voltage test are represented by T1, T2, T3, T4 and T5 respectively, then V={F1, F2, F3, F4, F5, T1, T2, T3, T4, T5}, C={F1, F2, F3, F4, F5}, and T={T1, T2, T3, T4, T5}.

[0098] As a further optimized technical solution of the present invention, in the second step, the detailed model elements of the fault model represent the fault signal propagation relationship related to the product component unit, including (c, c), (c, t), (t, c); is the fault signal propagation relationship between tests (t, t), indicating that the fault signal of the test on the left side of the dashed arrow can be transmitted to the test on the right side of the dashed line, and the fault signal will no longer continue to propagate downward.

[0099]

[0100] As a further optimized technical solution of the present invention, in the third step, the signal transmission relationship establishes a fault propagation relationship graphical model taking into account the test failure.

[0102] As a further optimized technical solution of the present invention, in S4, the establishment of the diagnostic data matching library specifically includes the following steps:

[0103] In the first step, the columns in the diagnostic data matching library represent tests, and the rows represent product components and tests. The possible values ​​of the matrix elements in the database table include: 0, bm+j, which represents the credibility weight of the test. The specific value selection principles are as follows;

[0104] In the second step, if the fault signal of the i-th product component unit can be transmitted to the j-th test through the arrow, then the element dij in the i-th row and j-th column of the diagnosis matrix D = bm+j;

[0105] Step 3: If the fault signal of the i-th test can be transmitted to the j-th test through an arrow, then the element dm+ij in the m+i-th row and j-th column of the diagnosis matrix D is equal to bm+j.

[0106] Step 4: If the fault signal of the i-th product component unit cannot be transmitted to the j-th test through the arrow, the element dij in the i-th row and j-th column of the diagnosis matrix D is 0;

[0107] Step 5: If the fault signal of the i-th test cannot be transmitted to the j-th test through the arrow, the element dm+ij in the m+i-th row and j-th column of the diagnosis matrix D is 0;

[0108] Step 6: According to the above method, traverse all product components and tests to obtain a complete diagnostic data matching library, as shown below:

[0109]

[0110] As a further optimized technical solution of the present invention, in S5, the establishment of the diagnostic data matching library specifically includes the following steps:

[0111] The first step is to evaluate the diagnosability of product components. The specific process is as follows:

[0112] S1. Calculate the diagnosability pi of the i-th product component unit when a failure occurs. The calculation formula is as follows:

[0113]

[0114] S2. Traverse all product components and calculate the diagnosability of each product component when a failure occurs. The results are shown in the following table:

[0115]

[0116]

[0117] The second step is to evaluate the diagnosability of test failures. The specific process is as follows:

[0118] S1. Calculate the diagnosability qi when the i-th test fails. The calculation formula is as follows:

[0119]

[0120] S2. Traverse all tests and calculate the diagnosability index when a failure occurs in each test. The results are shown in the following table:

[0121]

[0122] The third step is to evaluate the fault detection capability of the product considering the test failure. The specific process is as follows;

[0123] S1. Calculate the product fault detection capability index γ considering test failure. The calculation formula is as follows:

[0124]

[0125] S2. Calculate the product fault detection capability index γ considering test failure;

[0126] The product fault detection capability index considering test failure is calculated to be γ = (0.14*0.01+0.1*0.008+0.1*0.004+0.63*1.35+0.16*2.68+0.68*0.02+0.44*0.5+0.1*0.08) / (0.01+0.003+0.008+0.004+1.35+2.68+0.02+0.5+0.08) = 0.32.

[0127] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0128] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A fault modeling and evaluation method and device considering test failure, characterized in that: The following steps are involved: S1: Get product information; S2: Calculate the credibility weight of the test; S3: Establish a fault propagation relationship model considering test failure; S4: Establish a diagnostic data matching library; S5: Evaluation of product fault detection capability considering test failures.

2. A fault modeling and evaluation method and device considering test failure according to claim 1, characterized in that: In S1, the obtaining of product information specifically includes the following steps: The first step is to obtain product component unit information, including component unit name, failure rate, failure signal transmission relationship, etc. The second step is to obtain the product test information, including test name, test type, test object, test failure rate (test failure rate), etc. The third step is to obtain the fault propagation information of product test failure. The fault propagation information of test failure includes the signal transmission relationship between the test failure fault signal and the product component unit, and the signal transmission relationship between the test fault signal and the test.

3. The method and device for fault modeling and evaluation considering test failure according to claim 1, characterized in that: In S2, the calculation of the credibility weight of the test specifically includes the following steps: In the first step, λm+j is used to represent the failure rate of the jth test, m is the number of product components, and bm+j is used to represent the credibility weight of the jth test. The calculation formula is as follows: In the second step, the credibility weight index of all tests is calculated according to the above method.

4. The method and device for fault modeling and evaluation considering test failure according to claim 1, characterized in that: In S3, the establishment of the fault propagation relationship model considering test failure specifically includes the following steps: The first step is to define the mathematical expression of the fault model; The second step is to define the element graphical expression of the fault model; The third step is to establish a graphical model of fault propagation relationship considering test failure.

5. A fault modeling and evaluation method and device considering test failure according to claim 4, characterized in that: In the first step, the mathematical expression of the fault model is defined as follows: G=<V,L> V=<C,T> L=<(c,c)...(c,t)...(t,c)...(t,t)> Where: G represents a directed graph model, that is, a fault propagation relationship model considering test failure; V is a node of a directed graph, i.e., a model element, which includes two categories: product component unit C and test T; L is the edge of the directed graph, which represents the propagation relationship of the fault signal, including the fault signal propagation relationship between product components (c, c), the fault signal propagation relationship from product components to tests (c, t), the fault signal propagation relationship from tests to product components (t, c), and the fault signal propagation relationship between tests (t, t).

6. A fault modeling and evaluation method and device considering test failure according to claim 4, characterized in that: In the second step, the detailed model elements of the fault model represent the fault signal propagation relationship related to the product component unit, including (c, c), (c, t), (t, c); is the fault signal propagation relationship between tests (t, t), indicating that the fault signal of the test on the left side of the dashed arrow can be transmitted to the test on the right side of the dashed line, and the fault signal will no longer continue to propagate downward.

7. A fault modeling and evaluation method and device considering test failure according to claim 4, characterized in that: In the third step, the signal transmission relationship establishes a graphical model of the fault propagation relationship taking into account the test failure.

8. The method and device for fault modeling and evaluation considering test failure according to claim 1, characterized in that: In S4, the establishment of the diagnostic data matching library specifically includes the following steps: In the first step, the columns in the diagnostic data matching library represent tests, and the rows represent product components and tests. The possible values ​​of the matrix elements in the database table include: 0, bm+j, which represents the credibility weight of the test. The specific value selection principles are as follows; In the second step, if the fault signal of the i-th product component unit can be transmitted to the j-th test through the arrow, then the element dij in the i-th row and j-th column of the diagnosis matrix D = bm+j; Step 3: If the fault signal of the i-th test can be transmitted to the j-th test through an arrow, then the element dm+ij in the m+i-th row and j-th column of the diagnosis matrix D is equal to bm+j. Step 4: If the fault signal of the i-th product component unit cannot be transmitted to the j-th test through the arrow, the element dij in the i-th row and j-th column of the diagnosis matrix D is 0; Step 5: If the fault signal of the i-th test cannot be transmitted to the j-th test through the arrow, the element dm+ij in the m+i-th row and j-th column of the diagnosis matrix D is 0; Step 6. According to the above method, all product components and tests are traversed to obtain a complete diagnostic data matching library.

9. The method and device for fault modeling and evaluation considering test failure according to claim 1, characterized in that: In S5, the establishment of the diagnostic data matching library specifically includes the following steps: The first step is to evaluate the diagnosability of product components. The specific process is as follows: S1. Calculate the diagnosability pi of the i-th product component unit when a failure occurs. The calculation formula is as follows: S2, traverse all product components and calculate the diagnosability of each product component when a failure occurs; The second step is to evaluate the diagnosability of test failures. The specific process is as follows: S1. Calculate the diagnosability qi when the i-th test fails. The calculation formula is as follows: S2, traverse all tests and calculate the diagnosability index when a failure occurs in each test; The third step is to evaluate the fault detection capability of the product considering the test failure. The specific process is as follows; S1. Calculate the product fault detection capability index γ considering test failure. The calculation formula is as follows: S2. Calculate the product fault detection capability index γ considering test failure.

Images