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System fault diagnosis method based on Malek model

A system fault diagnosis method technology, applied in the direction of response error generation, instrumentation, electrical digital data processing, etc., can solve the problem of system fault diagnosis algorithm failure, etc., to solve the system fault diagnosis problem, efficiently search, reduce The effect of load

Inactive Publication Date: 2017-05-31
GUANGXI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the system fault diagnosis algorithm based on the Malek diagnosis model has not been seen yet.

Method used

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  • System fault diagnosis method based on Malek model
  • System fault diagnosis method based on Malek model
  • System fault diagnosis method based on Malek model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0085] In order to verify the performance of the algorithm of the present invention, the algorithm is written in Matlab language, and the experiment is carried out on a computer with a memory of 4.00GB and a CPU of Core(TM) i52.5GHz.

[0086] A system fault diagnosis method based on the Malek model, including the following steps:

[0087] Step 1: Under the Malek model, specify the fault-free node method to generate the initial population. Each individual in the generated initial population, that is, a binary string corresponds to the multi-machine system, and each individual bit, that is, a binary bit, corresponds to the node; the specific method includes the following steps:

[0088] (1) In a multi-machine system containing n nodes, randomly designate a node k as fault-free;

[0089] (2) According to the degree of node k, find the node j adjacent to node k, if S(k,j)=0, it means that the test results of node k and node j are the same, and the test result of node j The state...

Embodiment 2

[0130] In order to test and evaluate the beneficial effect of the algorithm of the present invention in system fault diagnosis, the average CPU time of the two diagnostic algorithms is compared. Diagnosis algorithm one is the system fault diagnosis algorithm under the Malek model of the present invention; The concrete steps of diagnosis algorithm two are as follows:

[0131] Step 1: Specify the fault-free node method to generate the initial population;

[0132] Step 2: Calculate the fitness of individuals in the population, and determine whether there is an individual with a fitness value of 1, if not, go to step 3;

[0133] Step 3: Perform the following genetic operations on the population:

[0134] 3.1 Select operation, same as diagnosis algorithm one;

[0135] 3.2 Variation operation, that is, variation method 2 described in Example 1;

[0136] 3.3 Crossover operation, same as diagnosis algorithm 1;

[0137] 3.4 After the crossover operation, judge whether the number t ...

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Abstract

The invention discloses a system fault diagnosis method based on a Malek model. The system fault diagnosis method comprises the following steps: indicating a fault-free node method to generate an initial population in the Malek model; calculating the fitness of individuals in the population and judging whether individuals with the fitness value of 1 are contained in the population or not; carrying out selecting operation and optimal storage; carrying out mutation operation; carrying out crossed operation and judging whether a t-diagnosable system is met; calculating the fitness value of the individuals in a new population and judging whether the individuals with the fitness value of 1 are contained in the new population. According to the diagnosis method, in virtue of the characteristics of parallel genetic algorithm and high global searching ability, the efficiency of positioning fault sets is improved, and meanwhile, the aspect of judging the accuracy of a target fault set is also superior to that of a traditional PMC model in combination with the Malek comparison model. The method is applied to system fault diagnosis problems, so that the target fault set can be found out more accurately and more quickly.

Description

technical field [0001] The invention relates to an intelligent fault diagnosis algorithm, and in particular provides a system fault diagnosis method based on a Malek model. Background technique [0002] With the advent of the era of big data, the multi-computer system carries a large amount of data, information, algorithms, etc. However, once the multi-computer system covering a large number of PCs fails, how to accurately and quickly find out the fault node is currently facing major problem. The idea of ​​system-level fault diagnosis is to establish a suitable diagnostic model with the help of the node's own communication capabilities, and combine with effective diagnostic algorithms to find out the fault set. There are currently six diagnostic models, which are PMC, BGM, Chwa&Hakimi, Malek, MM, and MM* models. According to the test or comparison between nodes, it can be divided into two categories: test model and comparison model. The principle of the test model is to l...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/07
CPCG06F11/079
Inventor 刘翠归伟夏
Owner GUANGXI UNIV
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