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《Transactions of China Electrotechnical Society》 2004-12
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Fault Diagnosis for Power Transformer Based on BN and DGA

Wang Yongqiang Lü Fangcheng Li Heming (North China Electric Power University Baoding 071003 China)  
Power transformer is very important in power system. Now, dissolved gas analysis (DGA) is the most effective and convenient method in transformer fault diagnosis. This paper advances a new transformer fault diagnosis method based on both Bayesian network (BN) and dissolved gas analysis technique. This method introduces BN method into transformer fault diagnosis and presents a new idea of finding out transformer faults rapid1y and exactly. Then, the transformer fault diagnosis model based on Bayesian network and DGA is constructded. Finally, the application examples in the fault diagnosis of transformer are given which show that this method is effective.
【CateGory Index】: TM41
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