Haar小波及其机械故障诊断应用

Haar Wavelet for Mechanical Fault Diagnosis

小波变换是一种时频分析方法,在机械信号处理应用中,基小波常根据其时域波形与被检测的信号成分相似或匹配选择,很少考虑小波其他特性,这种方法并不完善.通过Haar小波说明这个问题,推导了Haar小波连续变换在时间和尺度上的周期性,应用于机械信号处理,有效地提取出故障特征频率.该研究结果开拓了基小波选择的思路.

The wavelet transformation is a kind of time-frequency analysis method. In the mechanical signal processing, the selection of the wavelet base depends on the form of the component required to extract from signal regardless of its other features. This rule is not perfect generally. The paper demonstrates the problem by Haar wavelet. The periodicity of Haar wavelet in both scale and time axes is proven and utilized to analyze the mechanical signals. the results show that Haar wavelet is also a good base in mechanical diagnosis. Thus the research extends the range of wavelet base selection.