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《Transactions of China Electrotechnical Society》 2003-02
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Fault Diagnosis of Power Transformer Using a Combinatorial Neural Network

Liu Na Gao Wensheng Tan Kexiong (Department of Electrical Engineering Tsinghua University 100084 China)  
Methods of fault classification and organization of combinatorial neural network(CNN)are keys to the diagnosis of power transformer faults with CNN.In this paper,based on the discussion of fault classification methods and a cluster analysis of dissolved gas data of thirteen usual transformer faults,a CNN is introduced to realize the multi resolution recognition of the insulation faults,which not only can make the fault diagnosis be more exace,but also is helpful to establish a significant strategy for the repair work.Finally,the recognition results show that this model is effective.
【Fund】: 国家自然科学基金资助重点项目 ( 5 963 72 0 0 )
【CateGory Index】: TP183;TM41
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