基于小波包分析的电机滚动轴承故障诊断

电机滚动轴承发生故障时的信号是非平稳的,小波包变换对故障特征提取有明显的优势,给出了利用小波包对故障信号进行分析的方法。确定轴承参数以及对故障信号的采集,并计算各类故障特征频率,选择小波基和确定最佳的分解层数,之后在Matlab软件环境下对信号进行小波包分解和重构,得到滚动轴承各类故障信号的功率谱,最后把实验结果与计算结果做对比,证实了该方法可以有效地把轴承中的故障信息成分检测出来,从而判断滚动轴承的故障类型。

Fault Diagnosis of Motor Rolling Bearing Based on Wavelet Packet Analysis

The vibration signal of the motor rolling bearing is non stationary,and the wavelet packet transform has the obvious advantage to the extraction of fault feature.The wavelet packet transform is used to analyze the fault signal.The bearing parameters and the fault signal are collected.The feature frequency of various type of fault is calculated,the wavelet bases are selected and the optimal number of decomposition layers is determined.The signal is decomposed and reconstructed in the Matlab software environment,and the power spectrum of various fault signals of the rolling bearings is obtained.The results show that the method can detect the fault information components effectively and judge the fault types of rolling bearings.