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《Journal of Shaoyang University(Natural Science Edition)》 2018-05
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Research on Transformer Fault diagnosis based on Probabilistic Neural Networks

LE Guoqing;WANG Hao;Shaoyang University,Hunan Provincial Key Laboratory of Grids Operation and Control on Multi-power Sources Area;  
Whether neural network can be applied on transformer fault diagnosis was analyzed and its unique advantages were verified; then the theory and method of modeling were expounded,a fault diagnosis model based on PNN(Probabilistic Neural Networks) theory was established and was simulated in Matlab environment; finally,RS(Rough Set) theory and PNN neural network are used. With the combination of collaterals,the optimized diagnosis model can be greatly improved in three aspects: stability,accuracy and speed.
【Fund】: 湖南省科技厅科技计划项目(2016TP1023)
【CateGory Index】: TM407
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