High Voltage Circuit Breaker Fault Diagnosis Based on Neural Fuzzy Petri Nets
Cheng Xuezhen1,2, Zhu Xiaolin1,2, Du Yanbin1,2, Wang Cheng1,3, Cao Maoyong1,2
1. State Key Laboratory of Mining Disaster Prevention and Control Co-Founded by Shandong Province and the Ministry of Science and Technology Shandong University of Science and Technology Qingdao 266590 China; 2.College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao 266590 China; 3. State Grid Shandong Electric Power Company Rizhao Power Supply Company Rizhao 276800 China
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.
程学珍, 朱晓林, 杜彦镔, 王程, 曹茂永. 基于神经模糊Petri网的高压断路器故障诊断研究[J]. 电工技术学报, 2018, 33(11): 2535-2544.
Cheng Xuezhen, Wang Cheng, Cao Maoyong. High Voltage Circuit Breaker Fault Diagnosis Based on Neural Fuzzy Petri Nets. Transactions of China Electrotechnical Society, 2018, 33(11): 2535-2544.
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2018, Vol. 33 
