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《Journal of Electric Power Science and Technology》 2011-02
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Transformers fault diagnosis based on fuzzy theory and support vector machine

ZHANG Jin-jiang1,2,LIANG Yao-sheng3,YIN Yu-juan2,GUO Chuang-xin2 (1.Zhejiang University of Science and Technology,Hangzhou 310023,China;2.Zhejiang University,Hangzhou 310027,China;3.Nanning High Voltage Transmission Company,Nanning 530028,China)  
To deal with the complexity of power transformers and the variety of fault mechanisms,a fault diagnosis method based on the fuzzy theory and the support vector machine(SVM) is proposed in this paper.In this method,the fault data are firstly preprocessed using fuzzy theory and then identified using SVM in which multi-objective classification and diagnosis results are achieved by employing the one-against-all method.To counter the difficulty of parameters decision in SVM,the multi-layer adaptive algorithm and the k-fold cross validation method are combined to optimize the parameters.Fault diagnosis cases analysis results show that the proposed method can overcoming the conventional diagnosis methods shortcomings of missing codes and absolute coding borders,and it is with more accurate and suitable in practice applications.
【Fund】: 浙江省自然科学基金(Y1100243)
【CateGory Index】: TM403
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