标题:Fault Diagnosis of Transformer Based on Chaotic Bats Algorithm Optimizing Fuzzy Petri Net
作者:Li, Mengjia ;Liu, Xiujie ;Li, Renhui ;Zheng, Ran ;Zhao, Wenchao
作者机构:[Li, Mengjia ;Zheng, Ran ;Zhao, Wenchao ] Shandong University of Science and Technology, College of Electrical Engineering and Automation, Qingdao, Ch 更多
会议名称:2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
会议日期:May 25, 2018 - May 27, 2018
来源:Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
出版年:2018
页码:885-889
DOI:10.1109/IMCEC.2018.8469756
摘要:A267 at the problem of low accuracy and long training time in the traditional intelligent algorithm of tr ansformer fault diagnosis, a fault diagnosis method based on chaotic bats algorithm optimization fuzzy Petri net (CBA-FPN) is proposed. DGA was considered as feature input, the parameters of FPN were coded into bats, and then the optimal parameters of FPN were founded by chaotic bat optimization algorithm. The fuzzy Petri net model was used to diagnose the transformer according to the optimal parameters. The simulation results show that the proposed algorithm has faster convergence speed and the higher correctness than the method of BP Optimized FPN (BP-FPN) and BA Optimized FPN network(BA-FPN), and has certain application valu e in the transformer fault diagnosis.
© 2018 IEEE.
收录类别:EI
资源类型:会议论文
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