基于EEMD的齿轮故障诊断方法研究

Research Gear Fault Diagnosis Method Based on EEMD

采用基于EMD改进的总体经验模式分解算法(EEMD)对齿轮箱进行故障诊断。首先利用Matlab进行仿真实验,验证了具有自适应特性的EEMD分解方法在消除基本模式分量之间相互混叠现象方面的有效性。然后利用该方法对故障试验台模拟的齿轮点蚀信号进行分解,并对反映故障信息的本征模式分量进行Hilbert包络解调分析。分析结果表明,EEMD方法可以有效地应用于齿轮故障诊断。

The ensemble empirical mode decomposition based on EMD is applied to gearbox fault diagnosis.firstly ,using Matlab to conduct the simulation experiments.It verified the effectiveness of EEMD comparing to EMD in eliminating the mode mixing.secondly,using this method decomposed gear pitting signal into the intrinsic mode function （IMF）, then applying Hilbert transform to some IMF that including fault information.Analysising the power spectrum and the Hilbert envelope spectrum.The results show that EEMD method can be effectively applied to the gear fault diagnosis.