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《Power System Technology》 2003-03
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POWER TRANSFORMER FAULT DIAGNOSIS BASED ON INTEGRATED ARTIFICIAL INTELLIGENCE

ZANG Hong-zhi, XU Jian-zheng, YU Xiao-dong (Electrical Engineering College, Shandong University, Jinan 250061, Shandong Province, China)  
An algorithm integrating the advantages of evolutionary algorithm, fuzzy theory, artificial neural network and case-based reasoning is presented. This algorithm improves the shortcoming of each single method of artificial intelligence, narrows the discrepancy among the sampled data, optimizes the initial weight value of network and greatly improves the convergence of artificial neural network. After great many calculations the topological structure and training samples are screened and chosen, through the expert system based on case-based reasoning the optimal source case is retrieved out and the diagnosis conclusion is given. Practical examples of power transformer diagnoses show that the presented method is effective.
【CateGory Index】: TM407
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