滚动轴承振动信号小波域自适应滤波方法

Application of Wavelet Analysis-adaptive Filtering in Vibration Signals for Rolling Ball Bearing

针对滚动轴承故障特征的提取问题,提出一种振动信号小波域自适应滤波方法。小波自适应滤波是一种新的非线性滤波方式,可以有效地提取出信号的边缘轮廓及信号的形状特征。计算机仿真证实小波域自适应滤波具有抑制信号噪声、保留信号非线性特征方面的作用。工程实验结果表明,利用小波域自适应滤波可以从滚动轴承振动信号中成功提取隐藏在噪声中的冲击故障特征。

To extract fault feature of rolling ball bearing, a novel approach is proposed according to the wavelet analysis - adaptive filtering. As a nonlinear filtering algorithm, wavelet analysis - adaptive filtering is able to identify the feature of fringe and shape of the signal. The effect of noise reduction and nonlinear feature reservation is validated by computer simulation. The result shows that the impact feature, it can not be identified from noisy data directly, and is successful extracted by wavelet analysis - adaptive filtering.