Application of Fuzzy Neural Network Optimized by MEA to Transformer Fault Diagnosis

摘要：

A new transformer fault diagnostic method based on fuzzy neural network and mind evolutionary algorithm was presented. According to the similartaxis and dissimilation, mind evolutionary algorithm has been used to optimize the membership function parameters and connection weights of fuzzy neural network, and it benefits to find the global optimal solution quickly. The analysis and experimental results showed that the method can improve processing ability of network, and the convergence of method is faster and diagnosis accuracy is higher than that of the GA-fuzzy neural network and PSO- fuzzy neural network. Therefore, the method can be used for the transformer fault diagnosis.

关键词： Transformer fault diagnosis Fuzzy neural network Mind evolutionary algorithm

作者: GAO Jinlan GAO Qian BAI LiLi

作者单位: College of Electrical & Information Engineering, Northeast Petroleum University, Heilongjiang Daqing College of Sciences, Yanshan University, Hebei Qinhuangdao 066004, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 3356-3360

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）