Park矢量模平方函数与ESPRIT相结合的异步电动机转子断条故障检测新方法

New Detection Method for Broken Rotor Bar Fault in Asynchronous Motor Based on Park's Vector Modulus and ESPRIT

为了能够在异步电动机转子断条故障初发时准确检测并适时安排维修计划,提出利用Park矢量模变换技术与旋转不变信号参数估计技术谱分析方法相结合的方法进行异步电动机转子断条故障检测。经过Park矢量模平方变换可以将工频分量转换为直流量,即可轻而易举的消除工频分量的影响,结合ESPRIT高频率分辨力技术可以在短时采样信号下准确地检测出故障特征频率,与以往检测方法相比计算量大为减少。对一台异步电机分别进行仿真与实验验证,仿真与实验结果同时显示,该方法能够准确提取到转子断条故障特征信号,计算快速,频率分辨力高。鉴于此,将Park矢量模平方函数与ESPRIT结合的异步电动机转子断条故障检测方法效果理想。

For instant detection of broken rotor bar （BRB） fault in an asynchronous motor, a new method for detecting BRB fault was proposed based on Park＇s vector modulus and estimation of signal parameters via rotational invariance technique （ESPRIT）. The power frequency can be easily filtered after the transformation of Park＇s vector modulus to transform the power frequency component into the DC component, thus the effect of the power frequency component will be eliminated. Using the algorithm of ESPRIT, the fault＇s characteristic frequency can be accurately calculated with the short-time sampling signals, and the computation amount can be greatly reduced. Simulation and experiment were carried out to validate the accuracy of the proposed method. Results show that the new method can fleetly extract the fault＇s characteristic frequencies with high frequency resolution.