Power transformer fault diagnosis based on fuzzy integral fusion

被引：0

作者：

Zhou Ling ^{[1
]}

Yan Huimin ^{[1
]}

Cao Yonggang ^{[1
]}

机构：

[1] Hohai Univ, Coll Elect Engn, Nanjing 210098, Peoples R China

来源：

PROCEEDINGS OF THE 41ST INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE, VOLS 1 AND 2 | 2006年

关键词：

power transformer; radial basis function (RBF); fuzzy integral; fault diagnosis;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

A new method to identify power transformer faults based on fuzzy integral fusion is presented. Firstly, the membership function of the value of three-ratio are presented and the data of the value of three ratios are processed by fuzzy method. Then the faults are identified by four different radial basis function (RBF) neural networks. Finally results of identification from four different neural networks are fused by fuzzy integral fusion and then form the final diagnosis. The results of simulation by presented method have been proved to be more accuracy than single neural network in identifying the practical transformer fault case.

引用

页码：1087 / 1090

页数：4