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《Electrical Automation》 2017-06
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Transformer Fault Diagnosis Based on Improved Fish Swarm Algorithm and Support Vector Machine

Cui Qiang;Li Yinglong;Li Zhihong;College of Electric Power Engineering,Nanjing Institute of Technology;  
Power transformer holds a very important position in the whole system,for its operational status is closely related to the stability of the whole power grid. Oil dissolved gas method is widely applied in engineering practice for fault diagnosis of the power transformer.Since transformer fault samples with a small sample database are quite limited in number and the support vector machine( SVM) is a good solution of the multi-class problem of small samples,this paper proposes that the improved fish swarm algorithm should be used for SVM optimization to obtain a global optimal solution and a SVM model of optimal parameters. Analysis of data instances shows the fault diagnosis model of improved fish swarm algorithm can achieve a higher accuracy than the particle swarm optimization fault diagnosis method and the improved three-ratio approach.
【CateGory Index】: TM41
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