Fault Diagnosis of Power Transformer Based on Adaptive Differential Evolution and Least Square Support Vector Machine

摘要：

　　Least square support vector machine (LS-SVM) can solve small sample,high-dimensional and non-linear multi-classification problem well,so it is applicable to the power transformer fault diagnosis.However,the parameters of LS-SVM have significant effect on the classification results.In this paper,the adaptive differential evolution algorithm (ADE) is applied to optimize the parameters of LS-SVM.The scaling factor and crossover rate are adjusted dynamically in the whole evolution process,so the robustness of the algorithm is improved greatly.The optimized LS-SVM is applied to fault diagnosis of power transformer,the results obtained demonstrate superiority of the proposed approach.

关键词： fault diagnosis power transformer least square support vector machine adaptive differential evolution algorithm parameter optimization

作者: Li Zipin Peng Hui

作者单位: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China

会议类型: 国际会议

会议名称: 2013 3rd International Symposium on Chemical Engineering and Material Properties(2013第三届化学工程和材料性能国际研讨会)(ISCEMP 2013)

会议地点: 三亚

会议语种:英文

页码: 1520-1524

在线出版日期: 2013-06-22（万方平台首次上网日期，不代表论文的发表时间）