Intelligent Detection and Analysis for Transformer Faults Based on Neural Network
Junfeng Han · Electric Switchgear · 2009
The common fault diagnosis method of transformer is put forward by use of neural network BP algorithm,and the transformer′s fault intelligence detection and analysis is achieved.In this paper,simulations of Matlab are carried out for different neural network structures,different activation transfer functions,different quantities of training samples and different training functions so that the best diagnosis scheme of neural network can be determined.Through simulation,the proper activation transfer function and training function are found.The experimental results show that the proposed method is able to obtain higher quality solutions efficiently than the conventional approaches.