文章基本信息

标题：A Partial Discharge Fault Identification Algorithm based on SGWT Neural Network
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作者：Wei Zhang ; Qiuli Wu ; Yurong Deng 等
期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2016
卷号：9
期号：5
页码：69-78
DOI：10.14257/ijgdc.2016.9.5.07
出版社：SERSC
摘要：Based on the second generation wavelet and information entropy, in this paper, we recognize the partial discharge pattern using the second generation wavelet (SGWT) and adaptive BP. Firstly, feature extraction of discharge signals are obtained using the SGWT and information entropy. Then, the extracted features are feed into the training BP network. The learning algorithm employed the conjugate gradient methods and the adaptive adjustment to train the error for BP network. Finally, we get the optimum training network, and the simulation results verified the feasibility of the algorithm.
关键词：Partial discharge; wavelet entropy; conjugate gradient; SGWT