基于旋转不变信号参数估计技术与模式搜索算法的异步电动机转子故障检测新方法  

Detection of Rotor Fault in Induction Motors by Combining Estimation of Signal Parameters via Rotational Invariance Technique and Pattern Search Algorithm

作　　者：孙丽玲[1] 许伯强[1] 李志远[1] 

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,保定071003

出　　处：《机械工程学报》2012年第13期89-95,共7页Journal of Mechanical Engineering

基　　金：国家自然科学基金(50407016);中央高校基本科研业务费专项基金(11QG55)资助项目

摘　　要：提出一种基于旋转不变信号参数估计技术(Estimation of signal parameters via rotational invariance technique,ESPRIT)与模式搜索算法(Pattern search algorithm,PSA)的异步电动机转子故障检测新方法。模拟形成转子故障情况下的定子电流信号并以之检验ESPRIT性能。结果表明:即使对于短时信号,ESPRIT仍具备高频率分辨力,可以准确估计定子电流各个分量的频率;但对其幅值、初相角的估计欠缺准确性、稳定性。随后,采用PSA确定各个频率分量的幅值、初相角。对一台异步电动机完成了转子故障检测试验,结果表明:基于ESPRIT与PSA的异步电动机转子故障检测方法是切实可行的,并且因仅需短时信号即可达到高频率分辨力而适用于负荷波动情况。A detection method for rotor fault in induction motors, which is based on estimation of signal parameters via rotational invariance technique（ESPRIT） and pattern search algorithrn（PSA）, is presented. The performance of ESPRIT is tested with the simulated stator current signal of an induction motor with rotor fault, providing the results that ESPRIT can indeed identify accurately the frequencies of the components of interest in the simulated signal even with short-time sample. However it can not estimate the amplitudes and initial phases of those components with accuracy and stability. PSA is introduced to determine the amplitudes and initial phases of the frequency components in the simulated signal and the results are really satisfactory. Thus paves the way to detect rotor fault in induction motors by combining ESPRIT and PSA. The related experiment on an induction motor is conducted and the results demonstrate that the ESPRIT-PSA-based method to detect rotor fault in induction motors is effective even with short-time sample, as makes it a promising choice for induction motors operating with fluctuant load.

关 键 词：异步电动机 转子故障 检测 旋转不变信号参数估计技术 模式搜索算法 

分 类 号：TH165[机械工程—机械制造及自动化]