基于CEEMD和3点对称差分能量算子的滚动轴承故障诊断方法

Fault Diagnosis of Rolling Bearings Based on CEEMD and Demodulation Energy Operator of Symmetrical Differencing

为解决传统信号处理方法提取滚动轴承故障特征不精确和Teager能量算子解调信号的解调频率和幅值误差较大的问题,课题组提出一种基于互补集合经验模态分解和3点对称差分能量算子结合的轴承故障特征提取方法CEEMD-DEO3S。课题组首先对滚动轴承进行CEEMD分解前进行去噪处理来增强信号的故障脉冲;然后利用CEEMD将去噪后信号分解为一系列固有模态函数,并依据相关系数原则选择最能表征故障的敏感分量,重构后进行DEO3S解调,依据解调后得到的幅值和频率计算信号的包络谱。实验分析表明:所提方法解调信号的误差更小,提取轴承故障频率更精确。

To solve the problems of imprecise extraction of rolling bearing fault features by traditional signal extraction methods and large demodulation frequency and amplitude errors of Teager, a bearing fault feature extraction method was proposed based on the combination of CEEMD and DEO3 S. Firstly, the denoising process was carried out before the rolling bearing CEEMD decomposition to enhance fault signal pulse;then, the denoised signal was decomposed into a series of inherent mode functions by CEEMD, and the sensitive component which can best represent the fault was selected based on the principles of correlation coefficient, and the DEO3 S demodulation was carried out after the reconstruction. The envelope spectrum of the signal was calculated according to the amplitude and frequency obtained after demodulation. The experimental analysis show that the smaller is the demodulation signal error of the proposed method, the extraction of bearing failure frequency is more accurate.