吉林大学学报（理学版）Issue(2)：313-318,6.DOI:10.13413/j.cnki.jdxblxb.2014.02.30
基于直觉模糊最小二乘支持向量机的变压器故障诊断
Transformer Fault Diagnosis Based on Intuitionistic Fuzzy Least Squares Support Vector Machine
摘要
Abstract
In the light of transformer fault diagnosis based on dissolved gas analysis (DGA)with a small sample size,poor information and the fault diagnosis results is easily affected by the noise in the sample, we proposed an intuitionistic fuzzy least squares support vector machine algorithm (IFLS-SVM).First we derived the related algorithm,and designed the multi-class classifier based on the IFLS-SVM.Then we implemented the power transformers’fault diagnosis using the Matlab software.At last we compared the diagnostic result of the algorithm we proposed with the diagnostic results of the several LS-SVM multi-classification algorithms and BP neural network diagnostic result.Experiments results show that the IFLS-SVM diagnosis is better, with stronger noise immunity.关键词
电力变压器/故障诊断/直觉模糊/最小二乘支持向量机Key words
power transformers/fault diagnosis/intuitionistic fuzzy/least squares support vector machine (LS-SVM)分类
信息技术与安全科学引用本文复制引用
李岩波,张超,郭新辰..基于直觉模糊最小二乘支持向量机的变压器故障诊断[J].吉林大学学报（理学版）,2014,(2):313-318,6.基金项目
国家自然科学基金(批准号:11226263 （）
11201057 （）
61202261)、吉林省科技发展计划项目(批准号:20130101179JC)、吉林省自然科学基金(批准号:201215165)和符号计算与知识工程教育部重点实验室开放课题项目(批准号:93K172013Z01) （批准号:20130101179JC）
