A Novel Fault Diagnosis System on Polymer Insulation of Power Transformers Based on 3-stage GA⁻SA⁻SVM OFC Selection and ABC⁻SVM Classifier.

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作者： Xiaoge,Huang ^[1] ; Yiyi,Zhang ^[2] ; Jiefeng,Liu ^[3] ; Hanbo,Zheng ^[4] ; Ke,Wang ^[5]

作者单位： Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China. nnhuangxg@163.com. ^[1] National Demonstration Center for Experimental Electrical Engineering Education, Guangxi University, Nanning 530004, China. nnhuangxg@163.com. ^[2] Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China. yiyizhang@gxu.edu.cn. ^[3] National Demonstration Center for Experimental Electrical Engineering Education, Guangxi University, Nanning 530004, China. yiyizhang@gxu.edu.cn. ^[4] Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China. liujiefeng9999@163.com. ^[5] National Demonstration Center for Experimental Electrical Engineering Education, Guangxi University, Nanning 530004, China. liujiefeng9999@163.com. ^[6] Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China. hanbozheng@163.com. ^[7] National Demonstration Center for Experimental Electrical Engineering Education, Guangxi University, Nanning 530004, China. hanbozheng@163.com. ^[8] China Electric Power Research Institute, Haidian District, Beijing 100192, China. wangke1@epri.sgcc.com.cn. ^[9]

关键词 artificial bee colony (ABC)dissolved gas analysis (DGA)fault diagnosis genetic algorithm (GA)power transformers simulated annealing (SA) algorithm support vector machine (SVM)

DOI 10.3390/polym10101096

PMID 30961021

发布时间 2023-10-06

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