POVMD与包络阶次谱的变工况滚动轴承故障诊断

Fault Diagnosis Under Variable Conditions Based on Parameter Optimized Variational Mode Decomposition and Envelope Order Spectrum

针对变转速滚动轴承故障特征提取较难的问题,提出一种基于参数优化变分模态分解(parameter optimized variational mode decomposition,简称POVMD)与包络阶次谱的变工况滚动轴承故障诊断方法。首先,采用POVMD对变转速滚动轴承振动信号进行分解,得到若干个本征模态函数之和;其次,对各个分量的时域信号进行角域重采样,将时变信号转化为平稳信号处理,再利用Hilbert变换估计重采样后的平稳信号的包络;最后,对得到的包络信号进行阶比分析,从谱图中读取故障特征信息。将POVMD方法与经验模态分解进行了对比,仿真信号分析结果表明了POVMD方法的优越性。将提出的变转速滚动轴承故障诊断方法应用于试验数据分析,分析结果表明,所提出的方法能够实现变转速滚动轴承的故障诊断,而且诊断效果优于现有方法。

Based on the parameter optimized variational mode decomposition(POVMD)and envelope order spectrum,a new fault diagnosis method is proposed to extract the fault features of rolling bearing under variable speed condition.First,the vibration signal of rolling bearing is decomposed into several intrinsic mode functions(IMFs)by POVMD.Second,each IMF is resampled in the angular domain and transformed into stationary signals.Then,the Hilbert transform is used to estimate the envelope function of the resampled signals.The obtained envelope functionsare are analyzed using the order tracking technology and the fault feature information is read from the order spectrum.The comparisons show the superiority of POVMD over empirical mode decomposition by analyzing the simulation signals.Finally,the proposed fault diagnosis method for rolling bearing with variable speed is applied on the experimental data analysis and the results show that the propose method can effectively achieve the fault diagnosis of rolling bearing in variable speed.