基于多小波包的齿轮故障诊断方法研究

提出了一种全新的基于多小波包的齿轮箱故障诊断方法。在机械故障诊断领域,小波分析已经被应用在利用齿轮振动信号进行的故障诊断中。由于小波函数空间在高尺度上频带较宽,因此隐藏在信号中的在较高频段发生的窄带故障信号的频率成分不能被精确地诊断。提出的多小波变换,通过划分小波变换不同层的频带克服了单小波(标量小波)系统的这种缺陷。通过多小波包变换,可以自动并精确地划分不同小波包结点的频率段,从而对频率段较窄的瞬变故障信号进行精确的诊断。对齿轮箱的仿真实验结果表明,应用多小波包系统,不但可以对齿轮系统中包含瞬变现象的故障信号进行诊断,而且可以精确确定齿轮中坏齿的位置。

Research of Fault Diagnosis of Gears Based on Multiwavelet Packets

A new diagnosis method for the fault of gearboxes based on multiwavelet packets system is introduced. In the field of mechanical fault diagnosis, wavelet analysis is used in gear diagnosis. The wavelet function spaces at higher scales are broadband, so that the frequency content of the narrow-band phenomena hidden in the signal occured at relatively high frequencies cannot be diagnosed precisely. This deficiency of the scalar wavelet systems can be overcome by dividing the frequecncy bands of different levels. Using the multiwavelet packets transform, one attains this achievement automatically and more precisely. The simulation results show that using multiwavelet packets system, not only can the fault containing transient phenomena in the gearing system be diagnoses, but also its location can be determined precisely.