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《Electric Power Automation Equipment》 2012-11
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Identification of interior fault position based on SVM and D-S evidence theory for electric transformer

SIMA Liping,SHU Naiqiu,LI Zipin,HUANG Yong,LUO Xiaoqing(School of Electrical Engineering,Wuhan University,Wuhan 430072,China)  
Since it is difficult to determine the BPA(Basic Probability Assignment) in the transformer information fusion diagnosis method,an identification model based on the multi-SVM(Support Vector Machine) and D-S evidence theory is proposed for the interior fault position of electric transformer.The BPA is objectively realized based on the "one-versus-one" multi-class SVM posterior probability estimation;the complementary information of DGA(Dissolved Gas Analysis) data and routine electrical test data is fully utilized to detect the possible interior fault positions of electric transformer.Practical examples show that,the proposed model identifies the fault positions effectively and is better than the mono-SVM in both accuracy and generalization.
【Fund】: 国家自然科学基金资助项目(51207113)~~
【CateGory Index】: TM41
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