电力系统保护与控制Issue(14)：92-96,5.
改进证据理论与神经网络集成的变压器故障诊断
Transformer fault diagnosis based on improved evidence theory and neural network integrated method
摘要
Abstract
Considering the diversity of the transformer fault types and fault information uncertainty, the paper proposes the fault diagnosis method based on the combination of evidence theory and neural network. In order to realize the reasonable assignment of reliability by Dempster combination rule after the information fusion between strong conflict evidence, the concept of a trust coefficient is introduced to correct fusion results and is used in the synthesis of max-min ant system and neural network algorithm which form the body of evidence. Simulation results show that the method can still get better compliance determination result when the results of the initial diagnostic module is seriously divided, so it achieves effective transformer fault diagnosis.关键词
变压器/证据理论/合成规则/故障诊断Key words
transformer/evidence theory/combination rule/fault diagnosis分类
信息技术与安全科学引用本文复制引用
程加堂,艾莉,段志梅..改进证据理论与神经网络集成的变压器故障诊断[J].电力系统保护与控制,2013,(14):92-96,5.基金项目
云南省教育厅科学研究基金项目 （）
