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《Journal of Baoji University of Arts and Sciences(Natural Science Edition)》 2006-02
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Research in ANN of transformer fault diagnosis

WU Hong-qi1,LIU Xia1,JIA Hong-bin2,LIU Feng-ling1(1.Dept.Electronics & Elect.Engn.,Baoji Univ.Arts & Sci.,Baoji 721007,Shaanxi,China;2.Baoji Power Supply Bureau,Baoji 721004,Shaanxi,China)  
Aim To solve the low veracity of solute gas analytical method in transformer fault diagnosis.Method The artificial neural network and the advanced BP training arithmetic operations based on momentum factor technique are used.Results A BP neural network model is established.The network has powerful abilities of studying,generalizing and adapting.Conclusion The neural network is able to diagnose the transformer faults accurately and it has value of applying widely.
【Fund】: 陕西省教育厅自然科学基金项目(03JK159)
【CateGory Index】: TM407
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