Study on fault diagnosis method of transformer using multi-neural network and evidence theory

Abstract

In order to solve the problems of power transformer such as the fault can be reflected by different characteristic signal from different side and complexity of fault reason and phenomenon, a synthetic diagnosis method using multi-neural network and evidence theory for transformer fault diagnosis is presented. Various kinds of data are dealt by using neural network's excellent abilities of learning, memory and recognition. Integrating data fusion methods, neural network's preliminary results are diagnosed by evidence theory. It has been shown by experiments that the accuracy rate of transformer fault diagnosis is up to 73%.