小波包分析在齿轮故障诊断中的应用

APPLICATION OF WAVELET PACKET ANALYSIS TO GEAR FAULT DIAGNOSIS

基于小波包对信号的高分辨率分解和重构能力,把信号分解到不同频段,然后选择有效频段进行故障信号重构,分离出故障信息。通过对含有周期冲击的信号进行分解处理,展示了小波包分析在特征提取中的优点。通过对减速箱齿轮故障信号进行降噪、分解处理,表明该方法可以有效地提取故障信号中的周期冲击成分。

Vibration signals are frequently used in mechanical fault diagnosis. However, in many cases, because of very low signal-to-noise ratio (SNR), it is difficult to detect the real fault. In the paper, a de-noising method based on Wavelet Package is introduced. The advantage of the method in extracting impulsive signals buried in noise is revealed by applying it to two simulated impulsive signals with additive noise. The application of the method to gear fault diagnosis also gets an expected result.