基于FVMD的滚动轴承故障特征提取方法  

Extraction method of rolling bearing fault characteristics based on FVMD

作　　者：张爽 王晓东[1,2] 李祥[1,2] 杨创艳 ZHANG Shuang;WANG Xiaodong;LI Xiang;YANG Chuangyan(Faculty of Information Engineering&Automation,Kunming University of Science and Technology,Kunming 650500,China;Yunnan Key Laboratory of Artificial Intelligence,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学信息工程与自动化学院,昆明650500 [2]昆明理工大学云南省人工智能重点实验室,昆明650500

出　　处：《振动与冲击》2022年第6期236-244,共9页Journal of Vibration and Shock

基　　金：国家自然科学基金(51765022,61663017);云南省科技计划(2019FD042)。

摘　　要：针对变分模态分解(variational mode decomposition,VMD)中模态数K和惩罚因子α无法自适应确定的问题,提出了基于快速变分模态分解(fast VMD,FVMD)的滚动轴承故障特征提取方法。首先,利用频谱趋势分割方法对滚动轴承振动信号进行分析,确定频谱趋势分割边界,进而自适应确定VMD的分解模态数K和惩罚因子α、模态初始中心频率ω;其次,根据参数K、α、ω,完成原始振动信号的自适应分解,并基于有效权重峭度准则提取有效本征模态函数(intrinsic mode function,IMF)分量;最后,利用希尔伯特包络解调计算有效IMF分量重构信号的包络频谱图,完成滚动轴承故障特征的提取。使用仿真信号、美国凯斯西储大学(Case Western Reserve University,CWRU)和美国航空航天局(National Aeronautics and Space Administration,NASA)的滚动轴承数据完成所提方法与传统VMD方法的对比试验。结果表明,所提方法能够自适应确定VMD的分解模态数K和惩罚因子α,提高VMD的计算效率,同时有效提取到滚动轴承的故障特征频率,证明了所提方法的有效性和可行性。Since the mode number K and penalty factorαof the variational mode decomposition(VMD)cannot be determined adaptively,a method for rolling bearing fault feature extraction based on fast VMD(FVMD)was proposed.Firstly,the spectrum trend segmentation method was used to determine the spectrum trend segmentation boundary,and the decomposition mode number K,penalty factorαand initial central frequencyωof VMD were adaptively determined.Then,the adaptive decomposition of the original vibration signal was completed based on the determined parameters K,αandω,and the kurtosis criterion of effective weight was adopted to extract the effective intrinsic mode function(IMF)components.Finally,the effective IMF component was processed by the Hilbert envelope demodulation,and the envelope spectrum of the reconstructed signal was obtained to extract the fault features of the rolling bearing.Simulated signals,and the data from Case Western Reserve University(CWRU)and National Aeronautics and Space Administration(NASA)were used as the rolling bearing sample data to complete the comparative experiments between the proposed method and the traditional VMD method.The experimental results show the effectiveness and feasibility of the proposed method.

关 键 词：变分模态分解(VMD) 频谱趋势分割 滚动轴承 特征提取 

分 类 号：TN911.7[电子电信—通信与信息系统] TH165.3[电子电信—信息与通信工程]