基于FOA的变分模态分解在轴承故障诊断中的应用  

Application of Variational Mode Decomposition based on the FOA and in Bearing Fault Diagnosis

作　　者：刘畅 王衍学[1,2] 杨建伟 Liu Chang;Wang Yanxue;Yang Jianwei(School of Mechanical-Electronic and Vehicle Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles,Beijing University of Civil Engineering and Architecture,Beijing 100044,China)

机构地区：[1]北京建筑大学机电与车辆工程学院,北京100044 [2]北京建筑大学城市轨道交通服役性能保障北京市重点实验室,北京100044

出　　处：《机械传动》2020年第5期146-154,共9页Journal of Mechanical Transmission

基　　金：国家自然科学基金(51875032,61463010,51475098);广西自然科学杰出青年基金(2016GXNSFFA380008)。

摘　　要：变分模态分解(VMD)广泛应用于故障诊断中,从振动信号中提取故障特征是故障诊断过程中的关键部分。针对强背景噪声和脉冲干扰下滚动轴承早期故障特征难以提取的问题,提出了一种新的基于果蝇优化算法(FOA)的变分模态分解的轴承故障诊断方法。首先,利用果蝇优化算法自适应优化VMD的惩罚参数α和分解数K,获取最优参数组合;然后,对信号进行VMD分解,得到K个模态分量;最后,基于峭度最大化准则选取最优模态分量进行包络解调分析,提取出故障特征频率。通过仿真信号分析、实际故障轴承信号验证以及与基于果蝇优化算法的多分辨奇异值分解(MRSVD)方法进行对比,证明了所提方法的有效性。The variational mode decomposition(VMD)is widely used in fault diagnosis.Extracting fault characteristics from vibration signals is a critical part in the bearing fault diagnosis.It is difficult to extract early fault signatures under strong background noise and pulse interference.Thus,a new fault diagnosis method is proposed based on the variational mode decomposition and fruit fly optimization algorithm(FOA).Firstly,the fruit fly optimization algorithm is used to optimize the penalty parameterαand the decomposition number K of the VMD adaptively to obtain the optimal parameter combination.Then,the VMD decomposition of the signal is performed to find K modal components.Finally,the optimal modal component is selected based on the kurtosis maximization criterion for envelope demodulation analysis and extracting the frequency of the fault feature.The effectiveness of the presented method is verified by simulation signal analysis,detecting bearing fault signal and comparing with multi-resolution singular value decomposition(MRSVD)approach based on fruit fly optimiza tion algorithm.

关 键 词：变分模态分解 果蝇优化算法 多分辨奇异值分解 轴承 故障诊断 

分 类 号：TH133.33[机械工程—机械制造及自动化] TP18[自动化与计算机技术—控制理论与控制工程]