Abstract:

For de-noising from low SNR rotor vibration signal, a method based on EMD and wavelet analysis is proposed. Firstly, the noisy signal is decomposed by EMD, and the IMF components are divided to high and low frequency by using consecutive mean square error(CMSE). Then, different thresholds are determined and the useful signal details of high and low frequency IMF components are extracted based on wavelet analysis and combined with the low-frequency IMF components so that the noise of IMF is removed efficiently. Numerical simulation and rotor vibration signal were carried out to evaluate the performance of the proposed method. The results showed that the proposed method outperformed the EMD and wavelet threshold de-noising algorithm.

摘要：

针对低信噪比转子振动信号的去噪问题，提出了EMD和小波分析相结合的去噪方法。首先对含噪信号进行EMD处理，利用连续均方误差准则对IMF分量进行高低频区分。然后设定不同的阈值，利用小波分析对高低频IMF分量进行有用信号的提取，将提取的信号和低频IMF分量叠加重构，实现降噪。为了验证所提方法的有效性，进行了数字仿真和转子振动信号降噪分析，结果表明，所提方法整体上优于EMD和小波阈值去噪方法。

关键词: 振动与波, 混沌信号, EMD, 小波分析, 连续均方误差