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A Test Optimization Selection Method Considering Critical Faults

A key fault and optimization selection technology, applied in design optimization/simulation, constraint-based CAD, instrumentation, etc., can solve the problems of safe system operation and follow-up maintenance burden, critical faults cannot be detected and isolated, and eliminate serious problems. Threat effect

Active Publication Date: 2021-12-14
NAVAL AVIATION UNIV
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

Although the optimal solution searched by the above algorithm can minimize the test cost and meet the testability index requirements, the abandonment of some tests may cause some critical faults with a small probability to be unable to be detected and isolated, thereby affecting the safe operation and operation of the system. Subsequent maintenance poses a serious burden

Method used

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  • A Test Optimization Selection Method Considering Critical Faults
  • A Test Optimization Selection Method Considering Critical Faults
  • A Test Optimization Selection Method Considering Critical Faults

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Embodiment

[0065] Taking the superheterodyne receiver system as an example, its fault-test correlation matrix is ​​shown in Table 1, t 1 ~t 36 For 36 tests, f 1 ~ f 22 represent 22 failures respectively.

[0066] Table 1 Fault-test correlation matrix of superheterodyne system

[0067]

[0068] Table 2 shows the prior probability of each fault and the three key faults of the system, assuming that the test cost of each alternative test is 1.

[0069] Table 2 System failure prior probability and key failures

[0070] Fault failure rate critical failure Fault failure rate critical failure f 1

[0071] It is stipulated that the fault detection rate and fault isolation rate of the system shall not be lower than 95%, and the critical fault detection rate and critical fault isolation rate shall not be lower than 98%. The remaining parameters are: M=60, ω max = 1.2, ω min =0.4,N max =200, α=β=γ=0.5, c 1 = c 2 = c 3 = 1.4962. After 30 independent calculation...

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Abstract

The invention discloses a test optimization selection method considering key faults. The method includes the steps of obtaining a fault-test correlation matrix, establishing an optimization model, solving the optimization model, and the like. From the perspective of system security, this method analyzes the importance of key faults, and then based on the correlation matrix, takes the minimum test cost as the optimization goal, constrains the fault detection rate, isolation rate and key fault detection rate, isolation rate, and establishes the key The test optimization selection model of the fault is finally solved by the binary particle swarm algorithm based on the improvement of the center of mass and the adaptive adjustment of the inertia weight. The invention can effectively eliminate the serious threat to the safety of equipment caused by missed detection of key faults.

Description

technical field [0001] The invention belongs to the technical field of testing and fault diagnosis, and relates to a test optimization selection method considering key faults. Background technique [0002] With the continuous improvement of the complexity of electronic equipment, problems such as poor testability, high test cost and difficult test diagnosis are gradually exposed in use. An important task of test diagnosis is test optimization selection, that is, to select a set of test sets that meet the testability parameter index requirements in the set of all possible tests in the system, and at the same time, the test cost is the smallest. The test optimization selection problem is a typical set covering and combinatorial optimization problem, which is difficult to solve. Commonly used greedy algorithms, AND-OR graph search algorithms, and AO* methods have problems such as high computational complexity, local convergence, and combinatorial explosion, making it difficult...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/27G06F17/16G06N3/00G06F111/04G06F119/02
CPCG06F17/16G06N3/006G06F2111/04G06F30/333G06F30/20
Inventor 马羚叶文吕晓峰王凤琴刘瑜汪兴海吕鑫燚
Owner NAVAL AVIATION UNIV
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