交流接触器触头系统运动分析及故障诊断研究  

Research on Motion Analysis and Fault Diagnosis of Contact System of AC Contactor

作　　者：刘树鑫[1] 宋健[1] 刘洋[1] 曹云东[1] 李静[1] Liu Shuxin;Song Jian;Liu Yang;Cao Yundong;Li Jing(Key Lab of Special Electric Machine and High Voltage Apparatus State Shenyang University of Technology,Shenyang 110870 China)

机构地区：[1]沈阳工业大学,特种电机与高压电器教育部重点实验室,沈阳110870

出　　处：《电工技术学报》2021年第S02期477-486,共10页Transactions of China Electrotechnical Society

基　　金：国家自然科学基金(51977132);辽宁省重大专项(2020JH1/10100012);辽宁省教育厅科学研究(LQGD2020001)资助项目。

摘　　要：为了解决现有交流接触器触头系统故障诊断技术存在的运行状态识别率较低的问题,该文以改进多尺度排列熵(MMPE)与能量矩为特征向量,提出一种基于粒子群优化(PSO)算法最小二乘支持向量机(LSSVM)的交流接触器触头系统运动分析及故障诊断方法,能够有效提高运行状态识别率。经实测数据验证表明,所提方法可以完成交流接触器运行状态的有效识别,能够更有效地完成交流接触器故障定性诊断,并可以有针对性地对设备进行检修和维护。In order to solve the problem of low recognition rate in the current fault diagnosis technology of AC contactor contact system,this paper proposes a new method based on particle swarm optimization(PSO)based on modified multi-scale permutation entropy(MMPE)and energy moment.The least squares support vector machine(LSSVM)based on PSO can effectively improve the recognition rate of AC contactor contact system.The experimental data show that the proposed method can effectively identify the operation status of AC contactor,and can more effectively complete the qualitative diagnosis of AC contactor fault,and can effectively guide and targeted equipment maintenance and repair.

关 键 词：交流接触器 改进多尺度排列熵 能量矩 粒子群优化-最小二乘支持向量机 故障诊断 

分 类 号：TM572.2[电气工程—电器]