基于小波包分析的齿轮箱故障诊断研究

摘要

通过对齿轮箱正常和故障运行状态的振动信号进行分析，利用小波包理论将3种工况振动信号进行分解。根据不同频带内能量分布的不同以及能量比值指标，有效地进行了3种工况的识别与分类，结果表明。利用小波包分解是齿轮箱故障的一种有效的诊断方法。%Vibration signals of the normal and abnormal running state of the gearbox are analyzed, and the three working vibration signals are decomposed by using Wavelet Packet Theory. According to different energy distribution and energy ratio index of different frequency bands, the three working modes of gearbox are identified and classified effectively. The results indicate that the wavelet packet decomposition is an effective method for gearbox fault diagnosis.