非平稳振动信号的小波去噪及其应用

在机械故障诊断中，对故障信号的消噪处理，一直是其重要内容之一。工程中设备运行状态多样，有着大量的非平稳动态信号，但传统的信号处理方法在处理非平稳信号上有所不足。利用小波包分解信号，白噪声的方差和幅值随小波尺度的增加而减小，但是信号的方差和幅值和小波变换无关。按照信号能量的观点，首先把信号进行多层小波包的分解，然后利用其中几个能量大的小波包来重构原始信号。利用该方法在测试信号的去噪处理中，同传统的阈值去噪相比较，该方法可以有效地消除白噪声的干扰，计算简单且有较好的消噪效果。

Wavelet Packets Transform Denoise of Non-stationary Vibration Signal and Its Application to the Fault Diagnosis of Machine

In the fault diagnosis of machine, the denoising of the fault signal are always the one of primary contents. There are many nonstationary signals in the protean porjects,but there are also many deficiency in the conventional denoising of nonstationary signals. In wavelet packets transform, the variance and amplitude of the white noise will minish with the increase of wavelet scale, but the variance and amplitude of the signals have no relation with wavelet transform. According to the viewpoint of the signal energy, wavelet packet decomposition is operated on the digital signals firstly, then some wavelet packets which have largest energy is used to reconstruct the original signal. This method can denoise the fault signal validly. Compared with traditional threshold denoising method, this method makes the computation easier and can also obtain the better denoising effect.