基于EEMD和包络分析的滚动轴承故障诊断研究

Fault diagnosis in rolling bearings based on EEMD and envelope analysis

在较大的背景噪声中,对旋转机械进行监测,包络分析不能从测得的振动信号中解调出故障。基于旋转机械振动信号具有非平稳、非线性特点,提出一种新的基于EEMD和包络分析的滚动轴承故障诊断方法,该方法首先运用EEMD方法将振动信号分解成有限个本征模态分量和残余量,对这些分量进行包络分析,可以解调出故障。通过仿真信号和实际滚动轴承外圈的振动信号分析表明该方法能够有效地识别滚动轴承的故障。

In the large background noise, the fault was not demodulated from the measured vibration signals by envelope analysis. Vibration signals of rotating machinery have the non-stationary and non-linear characteristics. A new method is proposed based on the ensemble empirical mode decomposition and envelope analysis for the rolling bearing fault diagnosis. Firstly, the vibration sig- nals are decomposed into a finite number of Intrinsic Mode Functions （IMFs） and one residue by EEMD. Secondly, the fault characteristic frequency is extracted from the IMFs by envelope analysis. It is showed that this method can effectively identify roll- ing bearing fault through the simulation signal and the actual vibration signals of rolling bearing outer race.