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《Journal of Hubei University for Nationalities(Natural Science Edition)》 2018-01
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Power Transformer Fault Diagnosis Based on BP Artificial Neural Network

TAN Zibing;HUANG Xiuchao;ZHONG Jianwei;Jianshi Power Supply Company,State Grid Hubei Electric Power Company;School of Information Engineering,Hubei University for Nationalities;  
The improved three-ratio method is used to handle the characteristic values of a set of dissolved gases in transformer oil;the data is used as input training of the neural network;the weights and threshold are adjusted to determine the parameters of the network through comparison and the error is controlled within the required range.Finally,the obtained probabilistic neural network is used to predict the samples successfully.It is proved that the BP neural network algorithm has very good performance in the diagnosis of transformer faults.
【Fund】: 国家自然科学基金项目(51177060);; 湖北省自然科学基金计划项目(2013CFC125)
【CateGory Index】: TM41;TP183
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