基于小波包变换及时间 小波能量谱的振动信号分析研究#br#

基于具有时频分析特性的小波包分析方法，对振动系统的测量信号进行了降噪处理，采用的软 硬阈值折中小波去噪方法兼有软阈值与硬阈值降噪的优点，且通过折中因子的引入，可以在信号分析中更灵活的进行信号处理.对去噪后的信号，基小波时间 能量谱分析，可以很好的将信号的主成分清晰的展示出来，并根据其能量在各频带的分布，可以直观的展示信号特征，为机械振动系统的故障诊断与识别，提供一套理论的方法.研究中所发展的分析方法在机械振动系统及其振动组件的状态监测及故障诊断识别方面有广阔的应用前景.

Vibration Signal Analysis Based on Wavelet Packet Transform and#br# Time Energy Wavelet Spectrum#br#

In the present paper, the measured signal of vibration system is de noised based on Wavelet Packet analysis, which has the properties of both time and frequency analysis. In the denoising process, the compromised threshold wavelet denoising method is adopted, which has the advantage of both the soft threshold and the hard threshold of the wavelet denoising method. Due to the compromised factor, flexible handling in analyzing the signals is permitted. By using time energy Wavelet Spectrum analysis to the denoised signal, the principal component is clearly shown. Based on the calculated energy distribution on the frequency domain, the characters of the signal are displayed clearly, which provides a theoretical method for fault diagnosis and fault identification of mechanical vibration system. Thus, the developed analytical method in the present paper has broad application in the fault diagnosis and fault identification of mechanical vibration system and its components.