变分模态分解和改进的自适应共振技术在轴承故障特征提取中的应用  

Application of variational mode decomposition and improved adaptive resonance technology in bearing fault feature extraction

作　　者：李华[1] 伍星[1] 刘韬[1] 陈庆[1] LI Hua;WU Xing;LIU Tao;CHEN Qing(Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学机电工程学院,云南昆明650500

出　　处：《振动工程学报》2018年第4期718-726,共9页Journal of Vibration Engineering

基　　金：国家自然科学基金资助项目(51465022);云南省重点项目(20161PE00008);昆明理工大学引入人才基金资助项目(KKSY201401096;14118992)

摘　　要：针对滚动轴承早期故障特征提取困难的问题,提出了基于变分模态分解(Variational Mode Decomposition,VMD)和改进的自适应共振技术的滚动轴承故障特征提取方法。针对轴承故障信号所在频带难以选择的问题,提出了基于改进的自适应共振技术(Improved Adaptive Resonance Technology,IART)的IMF选取方法。首先,确定模态数,提出了峭度最大值的模态数确定方法;然后,对原始振动信号进行VMD分解,获得既定数目的本征模态分量(Intrinsic Mode Function,IMF);其次,利用IART选取包含丰富故障信息的IMF分量;最后,(如有需要)对选取的IMF分量进行基于IART的带通滤波,并进行包络解调分析提取故障特征频率。将该方法应用到轴承仿真数据和实际数据中,能够实现轴承故障特征的精确诊断,证明了该方法的有效性。According to the difficult problem that the fault features extraction of rolling bearings in early failure duration,an incipient fault diagnosis method for rolling bearings based on the variational mode decomposition(VMD)and the improved adaptive resonance technology(IART)is proposed.According to the problem that the frequency band of the bearing fault signal is difficult to choose,an intrinsic mode function(IMF)selection method based on IART is proposed.Firstly,the mode number determination method based on kurtosis maximum value is proposed here to determine the mode number.Then,the original vibration signal is decomposed by VMD to obtain IMF,and the IMF component with abundant fault information is selected by IART.Finally,the selected IMF component is subjected to band-pass filtering based on IART if necessary,and the fault characteristic frequency is extracted by envelope demodulation analysis.The method can be applied to the bearing simulation data and the actual data,which can realize the accurate diagnosis of bearing fault characteristics and prove the effectiveness of the method.

关 键 词：故障诊断 滚动轴承 变分模态分解 峭度 改进的自适应共振 

分 类 号：TH165.3[机械工程—机械制造及自动化] TN911.7[电子电信—通信与信息系统]