中国电力2012，Vol.45Issue(11)：52-55,4.
基于支持向量机和交叉验证的变压器故障诊断
Transformer Fault Diagnosis Based on C-SVC and Cross-validation Algorithm
张艳 1吴玲1
作者信息
- 1. 自贡电业局调度局,四川自贡 643000
- 折叠
摘要
Abstract
A novel method for power transformer fault diagnosis based on the C-SVC (support vector classification with the optimized penalty parameter C) and cross-validation algorithm is presented, which can monitor and detect latent transformer faults timely and accurately. The training and testing sets of the C-SVC algorithm are built upon the data about the dissolved gases including hydrogen, methyl hydride, ethane, aethylenum and acetylene produced from transformer faults. Through the optimizing process of the penalty parameter and kernel function parameter y in the training set, the optimal support vector machine model can be gotten, with which the classification of data in the testing set can be conducted to determine fault features. The method has been validated by many practical examples to be feasible and efficient with high fault diagnosis accuracy.关键词
变压器/故障诊断/支持向量机/C-SVC算法/交叉验证/核函数参数Key words
transformer/ fault diagnosis/ support vector machine (SVM)/ C-SVC algorithm/ cross-validation/ kernel function分类
信息技术与安全科学引用本文复制引用
张艳,吴玲..基于支持向量机和交叉验证的变压器故障诊断[J].中国电力,2012,45(11):52-55,4.
