一种负荷突变情况下异步电机转子断条故障在线检测新方法

A New Online Fault Detection Method for Broken Rotor Bars in Induction Motor Considering Effects of Load Mutation

异步电机发生转子断条故障时,其定子电流故障特征频率分量容易被电流基频淹没,加之实际工作中电机负荷突变的干扰,极大地增加了故障特征频率提取及检测的难度。为解决该问题,将解析小波和定子电流谱减法结合,提出一种有效的故障检测新方法。该方法首先利用解析小波变换来判断负荷突变点,然后通过谱减法来消除定子电流频谱中的基频分量,突出故障特征频率,进一步定义故障程度因子来量化转子断条故障程度。仿真和实验分析结果表明,该方法对于负荷突变情况下转子断条故障特征频率更加敏感,能够定量地描述转子故障程度。

When the broken rotor bar fault occurs in induction motors, the induced fault characteristic frequency components are easily masked by the fundamental frequency, and even worse, the interference caused by motor load mutation greatly increases the difficulty in extracting and detecting the fault characteristic frequency. In order to solve the issue, the analytic wavelet analysis and the stator current spectral subtraction method are combined to propose a new effective fault detection method. Firstly, the analytic wavelet is employed to determine the location and the load mutation and then the spectral subtraction operation is performed to eliminate current fundamental component and highlight fault characteristic frequencies. Furthermore, two indicators are defined to quantify fault levels of broken rotor bars. Simulation and experimental resuhs show that the proposed method is more sensitive to fault characteristic frequency in the case of load mutation, meanwhile, describes the rotor fault severity quantitatively.