This paper mainly introduces that the fault vibrating signal of gears was decomposed into time-frequency domains by double-orthogonal wavelet analysis and the fault feature of gears was picked up.
利用双正交小波基将齿轮的故障振动信号分解到时频域，并提取出齿轮的故障特征。
Wavelet analysis is widely used in digital signal and image fields because of its good time frequency localization feature, but it doesn't do well in timely processing of long signals.
小波分析有良好的时-频局部化性能，现被广泛应用于数字信号和图像处理等领域，但其在处理有限长信号时的实时性不太理想。
In the view of feature signal extraction, the local wave time-frequency analysis and information entropy were used to deal with fault diagnosis.
从特征信号提取的角度出发，采用局域波时频分析和信息熵结合的方法进行往复式压缩机故障诊断。
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