电测与仪表2018，Vol.55Issue(5)：81-87,7.
基于蝙蝠算法优化最小二乘双支持向量机的变压器故障诊断
Fault diagnosis of transformer based on LSTSVM optimized by bat algorithm
雷昳 1刘明真 1田威1
作者信息
- 1. 国网湖北省电力公司检修公司,湖北宜昌443001
- 折叠
摘要
Abstract
Transformer fault diagnosis is an important technical means to ensure the safety operation of power system.In order to improve the accuracy of fault diagnosis of transformer,this paper proposes a fault diagnosis method of transformer which is based on LSTSVM optimized by bat algorithm.For the multiple classification problem of transformer fault diagnosis,in order to reduce the accumulation of errors and improve the accuracy,a Huffman tree is built according to dissimilarity matrix between classes,and then,we established a multi-classification fault diagnosis model based on LSTSVM.And parameter of each classifier in the model is optimized by bat algorithm.The simulation results show that the method in this paper can achieve higher accuracy compared to other method.关键词
变压器/最小二乘双支持向量机/哈夫曼树/蝙蝠算法Key words
transformer/LSTSVM/Huffman tree/bat algorithm分类
信息技术与安全科学引用本文复制引用
雷昳,刘明真,田威..基于蝙蝠算法优化最小二乘双支持向量机的变压器故障诊断[J].电测与仪表,2018,55(5):81-87,7.
