中国电机工程学报2016，Vol.36Issue(22)：6231-6237,7.DOI:10.13334/j.0258-8013.pcsee.152495
一种基于M-ary支持向量机的功率变换器故障分类方法
Fault Classification of Power Converters Based on M-ary Support Vector Machine Method
摘要
Abstract
Focusing on the issue of power converter fault diagnosis and location, a genetic algorithm based M-ary support vector machine (SVM) was proposed to enhance the accuracy of fault classification. The proposed method used the genetic algorithm and the within-class and between-class distance criterion to find the suboptimum fault coding which is related to the fault classes of power converters, and the optimized classifier model of M-ary SVM was established for the fault classification of power converters. The experiment results show that this optimized method has better fault classification accuracy than the standard M-ary SVM. Compared with the commonly used one-against-one SVM and one-against-all SVM, the proposed method needs far less number of classifiers and hence, the classification time can be reduced.关键词
功率变换器/故障分类/遗传算法/M-ary支持向量机Key words
power converters/fault classification/genetic algorithm/M-ary support vector machine分类
信息技术与安全科学引用本文复制引用
崔江,叶纪青,陈未,龚春英..一种基于M-ary支持向量机的功率变换器故障分类方法[J].中国电机工程学报,2016,36(22):6231-6237,7.基金项目
国家自然科学基金项目(51377079)；中央高校基本科研业务费项目(NS2014028)。Project Supported by National Natural Science Foundation of China (51377079) （51377079）
The Fundamental Research Funds for the Central Universities (NS2014028) （NS2014028）
