电力系统保护与控制2012，Vol.40Issue(2)：106-110,5.
基于免疫优化多分类SVM的变压器故障诊断新方法
A novel approach based on multi-class support vector machine of immune optimization for transformer fault diagnosis
韩富春 1高文军 1廉建鑫 1杨洁2
作者信息
- 1. 太原理工大学电气与动力工程学院,山西太原030024
- 2. 山西大同新荣供电支公司,山西新荣037002
- 折叠
摘要
Abstract
Considering the fact that the parameter setting for support vector machine (SVM) impacts on the classification accuracy and the traditional SVM can not deal with multi-class classification directly, a novel approach for transformer fault diagnosis based on multi-class support vector machine of immune optimization is presented, in which the parameters in SVM are optimized by immune algorithm. Multi-class algorithm model is established on the basis of one-category classification algorithm, hypersphere centers are obtained in high-dimensional feature space, and then the minimum distances are calculated between the sample and the center in order to determine the fault type the sample belongs to. The superiority of SVM in processing finite samples is fully brought into play, and blindness is greatly reduced about parameter selection of SVM. Simulation results show that the algorithm can detect transformer faults with a higher diagnosis rate in the case of limited samples, and prove the correctness and effectiveness of the method.关键词
变压器/免疫算法/支持向量机/故障诊断Key words
transformer/ immune algorithm/ support vector machine/ fault diagnosis分类
信息技术与安全科学引用本文复制引用
韩富春,高文军,廉建鑫,杨洁..基于免疫优化多分类SVM的变压器故障诊断新方法[J].电力系统保护与控制,2012,40(2):106-110,5.
