基于小波包和包络分析的滚动轴承故障自动诊断方法

提出了一种基于峭度-小波包-包络分析的滚动轴承故障自动诊断方法。首先用峭度系数判断是否出现故障,再针对故障轴承振动信号非平稳和调幅的特点,用小波包将信号分解到不同的节点上。然后将不同节点的重构信号做包络谱分析,将谱峰处的频率同滚动轴承内圈、外圈、滚珠、保持架等的故障频率进行对比分析,在此基础上,运用最小距离判别法则自动获得故障原因,从而实现滚动轴承故障的自动诊断。通过对实验中采集到的轴承振动信号进行分析,证明了该方法在轴承早期故障诊断中的有效性。

Rolling bearings fault auto-diagnosis based on wavelet packet and envelope analysis

A method of auto-diagnosis based on kurtosis,wavelet packet and envelope is presented for the rolling bearing fault diagnosis.The kurtosis is employed to analyze if the fault has occurred.The fault signals which are non-stationary and modulated are decomposed at different levels by the wavelet packet.The envelope spectrum of reconstructed signals at different levels is illustrated.By contrasting the frequency on spectrum peak and the fault frequency of inner race,outer race,balls and rolling element,the auto-diagnosis of the rolling bearing fault is realized by min-distance principle.Satisfactory results have been obtained from the experimental vibration signals and the effectiveness of the proposed method is demonstrated in auto-diagnosing for the rolling bearing faults.