EEMD结合小波包的振动筛轴承信号降噪效果分析

Denoising Analysis of Vibration Screen Bearing Signal Based on EEMD and Wavelet Packet

为解决振动机械故障诊断中如何更有效地在复杂信号中提取有用的故障信号的问题,提出了一种优良降噪算法。先将原始信号用小波包降噪,对降噪后的信号进行EEMD分解,然后将分解得到的固有模态分量(IMF)构建不同的带通滤波器,利用算法逼近度指标和相关系数建立优良降噪算法的判断准则,以此来选择最优的滤波器组合。对振动筛轴承信号进行仿真,用新算法处理仿真信号,结果显示,故障信号被保留下来,其他信号均被滤除。同时用该降噪算法分析了实测振动筛轴承信号,所得的结果合理有效。

In order to solve the problem of how to more effectively extract fault signals in complex signals in vibration machine fault diagnosis,an excellent noise reduction algorithm is proposed in this paper. First use the wavelet packet to the original signal noise reduction,the denoised signal is decomposed by EEMD,Then,the decomposed intrinsic modal function(IMF)are constructed with different bandpass filters,The criterion of excellent noise reduction algorithm is established by using algorithm approximation degree index and correlation coefficient,so as to select the optimal filter combination. The signal of the vibration screen is simulated,and the simulation signal is processed by the excellent noise reduction algorithm. The result shows that the fault signal is preserved and the other signals are filtered out. At the same time,the signals of the vibration screen bearings are analyzed by the algorithm,and the results are reasonable and effective.