基于小波包变换的笼型异步电机转子故障诊断

Fault Detection of Rotor Bar Breaking for Squirrel Cage Asynchronous Motor Based on Wavelet Packet Transform

本文分析了笼型异步电动机转子断条故障时的频率特点,阐述了小波包变换异步电动机转子断条故障的频带特征,在分析对比了多种信号处理方法后,本文提出了"自动寻求路径"的小波包树分解算法并选择其作为感应电机故障提取算法。这种算法既具有很好的自适应性和频域精度,又避免了过大的计算量,有效而实时地提取了故障信息。

This paper analyzes frequency character of rotor bar breaking fault for squirrel cage asynchronous motor, reviews the frequency division character based on wavelet packet transform. After carefully analyzing and comparing many signal processing （SP） methods, this paper proposes the ＇Automatically Searching Path＇ Wavelet Packet Binary Tree Decomposition Algorithm and chooses it as the very method to extract the induction motor faults characteristic information, which reflects the induction motor faults （broken rotor bar in this paper）. This method not only bears good self-adaptive capability and high precision in frequency domain, but also avoids the heavy burden of calculation intrinsic to the classical Wavelet Packet Decomposition. So it provides an efficient and effective method to extract the Fault Characteristic Information.