基于ESPRIT与Duffing系统的笼型异步电动机转子断条故障检测  

Detection based on ESPRIT and Duffing system for broken rotor bar fault in cage induction motors

作　　者：许伯强[1] 孙丽玲[1] XU Boqiang;SUN Liling(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University,Beijing 102206,China)

机构地区：[1]华北电力大学新能源电力系统国家重点实验室

出　　处：《电力自动化设备》2020年第2期117-122,共6页Electric Power Automation Equipment

基　　金：国家自然科学基金资助项目(51277077)~~

摘　　要：旋转不变信号参数估计技术(ESPRIT)应用于笼型异步电动机转子断条故障检测时,其频谱分析结果中可能出现实际并不存在的虚假频率分量,从而影响检测效果。针对该问题,采用ESPRIT对定子电流信号进行频谱分析,从而获得定子电流信号的频率分量组成,然后利用Duffing系统对ESPRIT频谱分析结果做进一步处理,以辨识并摒弃其中的虚假频率分量,从而保障笼型异步电动机转子断条故障检测的效果。仿真与实验结果验证了所提方法的有效性。When ESPRIT(Estimation of Signal Parameters via Rotational Invariance Technique) is used in the detection of BRBF(Broken Rotor Bar Fault) in cage induction motors,its spectrum analysis results may include some false frequency components that do not exist actually,thus affecting the detection effect. Aiming at this problem,the spectrum analysis of stator current signal is carried out by ESPRIT to obtain the frequency components of stator current signal,the false frequency components of which are then identified by Duffing system and eliminated to ensure that the detection of BRBF is effective. The simulative and experimental results validate the effectiveness of the proposed method.

关 键 词：异步电动机 转子断条故障 检测 旋转不变信号参数估计技术 DUFFING系统 定子电流信号分析 

分 类 号：TM315[电气工程—电机]