基于瞬态冲击响应参数辨识的轴承故障特征检测

Bearing fault feature detection based on parameter identification of transient impulse response

旋转机械的局部故障导致振动信号中出现冲击响应信号,可通过对冲击响应信号的检测与提取,进行局部故障诊断。在Laplace小波相关滤波法识别冲击响应信号的特征参数的基础上,针对周期性冲击响应信号的检测,提出了循环Laplace小波相关滤波法。通过不同信噪比下周期多冲击响应仿真信号中冲击响应成分特征参数辨识及周期检测,验证了方法的有效性。将循环Laplace小波相关滤波法应用于轴承外圈局部严重故障和轻微故障下冲击响应振动信号的辨识,成功识别故障特征的响应参数以及周期。

Localized defects in rotating machinery parts tend to result in impulse response in vibration signal, and the parameter identification of which provides a potential approach for localized fault diagnosis. This paper reviewed the Laplace wavelet correlation filtering and then, based on which, proposed Cyclic Laplace Wavelet Correlation Filtering （CLWCF） for the iden- tification of not only the impulse response parameter but also the cyclic period. Simulation study with cyclic impulse response signal with different SNR shows that CLWCF is effective in detecting the impulse response parameter and the cyclic period. Applications in bearing vibration parameter identification for localized fault diagnosis showed that the CLWCF in bearing vi- bration signal is effective in finding the period that represents the outer race localized fault at different fault seriousness, and thus provide a potential feature detection method for bearing fault diagnosis.