小波分析应用于笼型异步电动机转子断条在线检测初探

简单介绍了笼型异步电动机转子断条在线检测方法，指出如何正确区分电动机负荷波动与转子断条故障仍是一个亟待解决的突出问题，提出了一种基于小波分析的负荷波动判定方法，它可以对负荷波动进行准确定位，并反映负荷波动范围，同时，该文对应用小波分析提取转子断条故障特征分量的可行性进行了研究，结果表明小波分析对此是不适宜的，提取转子断条故障特征分量还必须依靠傅里叶变换方法，在此基础上，提出了一种基于小波分析，自适应滤波与连续细化傅里叶变换的转子断条在线检测新方法，其突出优点在于可以躲过负荷波动对转子断条在线检测的影响。数字仿真及实验结果证明该方法是切实可行的。

THE APPLICATION OF WAVELET ANALYSIS TO DETECT ROTOR BAR BREAKING FAULT OF SQUIRREL CAGE ASYNCHRONOUS MOTOR ON-LINE

Rotor bar breaking is one frequent fault of squirrel cage asynchronous motor. This paper briefly reviews several schemes to detect rotor bar breaking on-line, and points out that how to distinguish load oscillation and rotor bar b reaking correctly is still the essential problem up to now. Based on wavelet ana lysis, a method to determine whether the load oscillates and then locates it exa ctly is presented in this paper. In addition, the method can reflect the range o f load oscillation. At the same time, this paper discusses the feasibility using wavelet analysis to extract the feature component of rotor bar breaking fault, and draws a conclusion that wavelet analysis is inapplicable to some extent. Con sequently, on-line detection schemes must rely on Fourier transform to extract t he feature component. Based on the researches above mentioned, this paper presen ts a new on-line detection scheme that uses wavelet analysis, self-adaptive fi lt er and continuous subdivision Fourier transform synthetically. Results of numeri cal simulation and experiments show that the new scheme is valid and effective.