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Transformer fault diagnosis based on artificial neural networks (ANN) is widely used, because ANN has essential nonlinear character, parallel processing ability and the ability of self organize and self learning. But there exist problems if we use traditional ANN method alone to diagnose transformer fault, the large input vector dimension and complex training database will cause the computation complexity...
Based on Bayesian optimal classifier, combining with rough set and fuzzy set, a new transformer fault diagnosis and maintenance mode is presented in the paper. In this method fuzzy membership function of the observed information are used to establish posterior probability of primary assumptions in Bayesian optimal classifier, the classified result based on each fault information is for that worked...
Based on rough set and fuzzy set and Bayesian optimal classifier, a novel transformer fault diagnosis and maintenance method is proposed in the paper. The method firstly applies fuzzy subjection degree function of the observed information to establish posterior probability of original assumption in Bayesian optimal classifier, the classified results based on each fault information then are calculated,...
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