柴油机振动信号的小波包奇异值降噪

柴油机的振动信号中含有大量噪声，在进行故障特征提取之前必须加以消除。首先对傅里叶滤波降噪、小波降噪和小波包降噪的效果进行了对比，然后将奇异值分解技术用于信号降噪。最后提出了一种将小波包和奇异值分解相结合的降噪方法。该方法将输入信号进行一次小波包分解，利用奇异值分解方法对分解后的幅值量化系数进行降噪。实例表明，小波包和奇异值分解相结合的方法降噪效果最好。与其他方法相比，用新的方法对柴油机缸盖振动信号进行降噪处理的信噪比最高，且能明显识别出燃烧爆发、气门落座等各个阶段的振动信号，大大提高了特征提取的准确率。

De-noising of diesel vibration signal using wavelet packet and singular value decomposition

The vibration signals of diesel include much noise that must be eliminated before characteristic parameters extraction. Firstly, the effects of vibration-signal de-noising among Fourier transform, wavelet decomposition and wavelet packet decomposition were compared. Secondly, the singular value decomposition was applied to de-noise vibration signals. Finally, a new de-noising method integrated with wavelet packet and singular value was put forward. In this method, vibration signals are decomposed by wavelet packet, and the wavelet packet coefficient is de-noised by singular value decomposition again. The results indicate that the new de-noising method is the best. The signal-to-noise ratio of the vibration signals of diesel cylinder lid is the highest. The diesel vibration wave-form of combustion and valve gets clearly and the extracted characteristic parameters become more precise.