自适应谱峭度滤波方法及其振动信号检测应用

Adaptive Spectral Kurtosis Filtering and Its Application for Detection of Vibration Signal

谱峭度滤波方法是一种在强背景噪声下也能有效提取振动信号中瞬态成分的方法。笔者针对谱峭度滤波方法中窗宽的自适应选择问题,提出一种自适应谱峭度滤波方法。该方法将小波相关滤波提取的振动信号特征频率作为Morlet小波滤波窗口中心频率,并按最大谱峭度原则自适应选择滤波小波窗口宽度,以确定最优带宽Morlet小波窗。通过强背景噪声下的瞬态成分的提取验证该方法的有效性,并与窗口融合自适应谱峭度滤波方法进行比较。针对轴承故障振动信号检测,应用该方法提取反映轴承故障的冲击响应成分,说明该方法能够实现轴承故障振动特征信号的提取。

Spectral kurtosis is an effective tool for extracting the impulse response from vibration signals with strong background noise.This paper presents an adaptive spectral kurtosis filtering method to overcome the problem of window width adaptive selection.The center frequency of the filtering wavelet window is obtained using wavelet correlation filtering,and the adaptive selection of optimal Morlet wavelet window width can be obtained based on the principle of the maximum spectral kurtosis.The effectiveness of the proposed method is verified through the transient extraction form strong background noise and further proved by comparison with adaptive spectral kurtosis based on merging windows.For the bearing fault vibration signal detection,the proposed method is applied in the extraction of the transients caused by the fault,thus proving the method′s effectiveness in extracting the feature signal for bearing fault detection.