东北电力技术2026，Vol.47Issue(9)：44-50,62,8.
基于电流-角位移与PSO-SVM的GIS隔离开关机械故障诊断
Mechanical Fault Diagnosis of GIS Based on Current-Angular Displacement and PSO-SVM
摘要
Abstract
In view of the current problems such as the low accuracy rate and high misjudgment rate of mechanical fault diagnosis of gas insulated switchgear(GIS)disconnectors using a single feature,as well as the complexity of multi-feature fault diagnosis equipment,it proposes a mechanical fault diagnosis method for GIS disconnectors based on the combination of current and angular displacement.Firstly,it divides the current curve and angular displacement curve into four parts based on the four stages experienced during the o-pening process of the GIS disconnector.It extracts the extreme values and average values of each stage of the curve as characteristic values.It carries out feature selection through neighbor component analysis(NCA),and combines the features with higher weights in-to a diagnostic database.Secondly,it optimizes the key parameters of the support vector machine(SVM)through the particle swarm optimization(PSO)algorithm for fault diagnosis.Finally,taking the ZF6-252 type disconnector as an example,it collects the current and angular displacement data of it under normal operation and in the state of rusted and out-of-pin end covers through the GIS discon-nector fault diagnosis system independently developed by our laboratory.The test results show that the classification accuracy of this method can reach 97.78%,providing a certain reference for the mechanical fault diagnosis of GIS disconnectors.关键词
气体绝缘组合电器/电机电流/角位移/粒子群优化/SVMKey words
GIS/motor current/angular displacement/PSO/SVM分类
信息技术与安全科学引用本文复制引用
彭少卿,荆澜涛,田瑞,李金阔,王亮..基于电流-角位移与PSO-SVM的GIS隔离开关机械故障诊断[J].东北电力技术,2026,47(9):44-50,62,8.基金项目
辽宁省教育厅基本科研项目(LJKMZ20221707) （LJKMZ20221707）
