基于FVMD的滚动轴承故障特征提取方法

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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了所提方法与传统VMD方法的对比实验。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。

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	张爽1
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关键词 ：变分模态分解, 频谱趋势分割, 滚动轴承, 特征提取

Abstract：Since the mode number K and penalty factor α of variational mode decomposition (VMD) cannot be determined adaptively, a method of rolling bearing fault feature extraction based on fast VMD(FVMD) is proposed. Firstly, the spectrum trend segmentation method is used to determine the spectrum trend segmentation boundary, and then the decomposition mode number K, penalty factor α and initial central frequency ω of VMD are adaptively determined. Secondly, the adaptive decomposition of the original vibration signal is completed based on the parameters K, α and ω, and the kurtosis criterion of effective weight is established to extract the effective intrinsic mode function (IMF) components. Finally, the effective IMF component is calculated by Hilbert envelope demodulation, and the envelope spectrum of the reconstructed signal is obtained to extract the fault features of rolling bearing. Simulation signals, Case Western Reserve University (CWRU) and National Aeronautics and Space Administration (NASA) of rolling bearing data are used to complete the comparative experiments between the proposed method and the traditional VMD method. Experimental results show the effectiveness and feasibility of the proposed method.

Key words： variational mode decomposition spectral trend segmentation rolling bearing feature extraction

收稿日期: 2020-10-26 出版日期: 2022-03-28

引用本文:

张爽1，2，王晓东1，2，李祥1，2，杨创艳1，2. 基于FVMD的滚动轴承故障特征提取方法[J]. 振动与冲击, 2022, 41(6): 236-244.
ZHANG Shuang1,2, WANG Xiaodong1,2, LI Xiang1,2, YANG Chuangyan1,2. Extraction method of rolling bearing fault characteristics based on FVMD. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(6): 236-244.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2022/V41/I6/236

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