Application of a combined decision model based on optimal weights in incipient faults diagnosis for power transformer

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• 作者：Yang Tingfang ; Liu Haifeng ; Zeng Xiangjun ; Qiu Wei and Deng Wenbin
• 刊名：IEEJ Transactions on Electrical and Electronic Engineering
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：12
• 期：2
• 页码：169-175
• 全文大小：342K
• ISSN：1931-4981

文摘

A new method for the diagnosis of incipient transformer faults based on a combined decision model using IEC 60599 three-ratio method, grey system theory (GS) algorithm, Dempster–Shafer evidence (DS) theory, and backpropagation (BP) neural network diagnosis method is proposed in this paper. The new method will eliminate the influence of any one individual diagnosis method due to insufficient information or diagnostic prejudices. In order to minimize the sum-of-squared errors of the proposed method, the optimal weights of every individual method which comprises the combined decision model are calculated based on their own diagnosis error ratios. Thus a combined decision model based on optimal weights (CDMOW) is formed. Then the optimal diagnosis result is obtained based on CDMOW. Results of diagnosis instances show that the use of CDMOW not only gives a much higher diagnostic accuracy rate but also more stability in fault diagnosis than any single method composing it.