电测与仪表2024，Vol.61Issue(10)：67-73,7.DOI:10.19753/j.issn1001-1390.2024.10.009
基于多维信息融合的电力变压器故障诊断方法研究
Research on fault diagnosis method of power transformer based on multi-dimensional information fusion
摘要
Abstract
Considering that the existing transformer fault diagnosis methods are only for a single fault feature,it is difficult to make an accurate and comprehensive judgment on the actual situation of the power transformer.On the basis of multi-dimensional information fusion of power transformer,a fault diagnosis method combining the improved extreme learning machine and the improved D-S evidence theory is proposed.The output of the limit learning ma-chine is optimized by a posteriori probability mapping,and the probabilities of different labels are obtained,and the improved evidence theory is used to fuse the probability distribution matrix.The superiority of this method is veri-fied by comparing and analyzing the diagnosis methods before and after optimization.This method has higher fault i-dentification accuracy,and the accuracy rate reaches 96.50％,and can accurately identify various faults of power transformers,which can provide decision-making basis for condition maintenance.关键词
多维信息融合/电力变压器/故障特征/极限学习机/D-S证据理论Key words
multi-dimensional information fusion/power transformer/fault characteristics/extreme learning ma-chine/D-S evidence theory分类
信息技术与安全科学引用本文复制引用
代泽荟,经权,孟颖,黄磊,韩峰,郑大鹏..基于多维信息融合的电力变压器故障诊断方法研究[J].电测与仪表,2024,61(10):67-73,7.基金项目
国家重点研发计划资助(2017YFC0804101) （2017YFC0804101）
内蒙古电力(集团)有限责任公司科技项目(2021-14) （集团）
