基于神经模糊Petri网的高压断路器故障诊断研究

doi:10.19595/j.cnki.1000-6753.tces.170533

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Abstract In order to improve the stability of high voltage circuit breaker, this paper evaluates and diagnoses the state of high voltage circuit breaker by Petri net theory, for its powerful knowledge expression and logic inference function. According to the logic relationship of the circuit breaker, a fault diagnosis model of high voltage circuit breaker based on Petri is constructed; The failure mode and effect analysis(FMEA) method is used to deal with the fault statistics, and the credibility of place,threshold of transition, weight of place and credibility of transition; Optimize the forward inference algorithm to achieve accurate prediction of high voltage circuit breaker failure; Inverse inference combined with the minimum cut set can effectively avoid the blindness of maintenance. Finally, the part of model is used to deduce and analyze,the correctness and rationality of the reasoning model are verified by the fault tree and the data of statistics.

Key words： Neural fuzzy Petri net high voltage circuit breaker troubleshoot matrix inference neural network algorithm

Received: 28 April 2017 Published: 13 June 2018

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TM561

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.170533 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I11/2535

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