基于变分模态分解的风机滚动轴承早期故障诊断

Incipient Fault Diagnosis for Rolling Bearings Used in Wind Turbine Based on Variational Mode Decomposition

针对海上风电机组滚动轴承故障多且早期故障特征难以提取的问题,提出了一种基于变分模态分解的滚动轴承故障诊断方法。从频率方面研究了模态分量个数对信号特征信息的影响,提出故障特征信息提取时确定分解个数的一般原则,据此确定滚动轴承早期故障振动信号的分解个数并得到若干模态分量,从中筛选出最佳模态分量进行包络解调分析,最终通过对比包络谱特征频率对滚动轴承进行早期故障诊断。

There are many faults occuring in the rolling bearings for offshore wind turbines and the incipient fault fea- ture is difficult to extract. A fault diagnosis method for rolling bearings is proposed based on variational mode decompo- sition（VMD） for extracting fault feature. The effect of number of mode components on characteristic information of sig- nal is studied from the aspects of frequency, and the general principles are proposed to determine decomposition number during extraction of fault feature information. The decomposition number of incipient fault vibration signal of rolling bearings is determined and the several mode components are obtained. The best mode component is selected, and the envelope demodulation analysis is carried out. Finally, the incipient fault diagnosis for rolling bearings is carried out by comparison of characteristic frequency of envelope spectrum.