小波变换域双谱分析及其在滚动轴承故障诊断中的应用

BISPECTRUM ANALYSIS IN THE WAVELET TRANSFORM DOMAIN AND ITS APPLICATION TO THE FAULT DIAGNOSIS OF ROLLING BEARINGS

工程信号不仅会受到高斯噪声干扰,而且也会受到非高斯噪声干扰。而传统双谱分析方法从理论上仅能抑制高斯噪声,但对非高斯噪声是无能为力的。针对传统双谱存在的不足,将小波变换和双谱分析结合,提出了一种基于小波变换域非参数化双谱故障诊断方法,并应用到滚动轴承故障诊断中。考虑到滚动轴承信号幅值调制特点,在本方法中,对处理信号采用了希尔伯特变换技术,以进行解调。实验结果表明,小波域双谱优于传统双谱,特别是在非高斯噪声情况下,小波域双谱更有优势;研究为滚动轴承故障诊断提供了一种新的有效方法。

The engineering signal is always disturbed by Gaussian noise and non-Gaussian noise. The traditional bispectrum has good insensitivity to independent Gaussian noise. However, it is incapable of avoiding the disturbance of non-Gaussian noise. In view of the deficiency of traditional bispectrum, a new fault diagnosis method based on bispectrum analysis in the wavelet transform domain is proposed, and applied in the fault diagnosis of rolling bearing. Considering modulated amplitude of bearing signal,the Hilbert transform is adopted in signal processing. The experiment results show that the proposed method is superior to the traditional bispectrum analysis, especially in the case of existance of non-Gaussian noise. The research provides a new and efficient method for the fault diagnosis of rolling bearings.