A fault diagnosis method based on fuzzy preference relation and D-S evidence theory

A technology of preference relationship and fault diagnosis, which is applied in the fields of electrical digital data processing, special data processing applications, character and pattern recognition, etc. It can solve the problems of limited application and lack of robustness, so as to reduce labor costs and economic losses. , describe the overall effect

Pending Publication Date: 2018-12-25
BEIJING UNIV OF CIVIL ENG & ARCHITECTURE
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Problems solved by technology

Lack of robustness is considered as a limitation of D-S evidence theory, which wil...

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  • A fault diagnosis method based on fuzzy preference relation and D-S evidence theory
  • A fault diagnosis method based on fuzzy preference relation and D-S evidence theory
  • A fault diagnosis method based on fuzzy preference relation and D-S evidence theory

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Embodiment Construction

[0060] Below in conjunction with accompanying drawing, the content of specific embodiment of the present invention is described in further detail:

[0061] This intelligent identification embodiment mainly includes the following steps:

[0062] Step 1: For key components in large and complex electromechanical equipment, use vibration sensors, such as piezoelectric acceleration sensors, displacement sensors or eddy current displacement sensors, to collect multi-source state monitoring signals of equipment, and then generate basic probability distribution functions.

[0063] The basic probability distribution function of sensor information is shown in Table 1.

[0064]Table 1 Basic probability distribution function of sensor information

[0065]

[0066] In order to further illustrate the stability of the algorithm, the basic probability distribution functions generated by 40 sensors are simulated, as shown in Table 2. The fusion results are shown in figure 2 .

[0067] T...

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Abstract

The invention provides a method based on fuzzy preference relation and D-S evidence theory. The first step is to obtain the basic probability distribution function of multi-sensor information in mechanical equipment monitoring; In the second step, the credibility of the evidence is obtained by the cosine angle function, that is, the credibility matrix. In the third step, we construct the uncertainty matrix based on Deng entropy variance, measure the uncertainty of evidence, and obtain the preference relationship between the evidence. In the fourth step, the fuzzy preference relation matrix isconstructed by using the preference relation obtained in the previous step, and the ranking value instead of BPA is generated. In the fifth step, the weighted average evidence is obtained by modifyingthe weight vector through the confidence matrix and the ranking value. In the step 6 Fusion of weighted average evidences by Dempster combination rule for n-1 times, decisions are made once the results of the fusion are obtained. The present invention proposes a novel conflict evidence correction technique for obtaining modified weighted average evidence.

Description

technical field [0001] The invention belongs to the field of fault monitoring and diagnosis of large electromechanical equipment systems, and in particular relates to a fault intelligent decision-making method based on fuzzy preference relationship and D-S evidence theory. Background technique [0002] With the development of science and technology and the progress of society, various types of large electromechanical equipment have been widely used in engineering. Once these large-scale equipment fails, it may cause property loss, and even cause casualties in serious cases. For the research of equipment fault diagnosis methods, the complexity of the electromechanical system structure and the diversity of the working environment lead to more and more types of fault-related information, coupled with the limitations of sensor measurement accuracy, imperfect experimental methods and fault occurrence Factors such as the randomness of the location make the fault signals obtained ...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06K9/62G06F17/16
CPCG06F17/16G06F30/20G06F18/25
Inventor 王衍学刘放陈志刚朱爱华白堂博
Owner BEIJING UNIV OF CIVIL ENG & ARCHITECTURE
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