变分模态分解和同步挤压小波变换识别时变结构瞬时频率

PDF(2322 KB)

振动与冲击 ›› 2018, Vol. 37 ›› Issue (20) : 24-31.

论文

刘景良1 郑锦仰1 林友勤2 邱仁辉1 骆勇鹏1

作者信息 +

Instantaneous frequency identification of time-varying structures using variational mode decomposition and synchrosqueezing wavelet transform

LIU Jingliang1,ZHENG Jinyang1,LIN Youqin2,QIU Renhui1,LUO Yongpeng1

Author information +

文章历史 +

摘要

针对土木工程领域存在的时变多分量响应信号，提出一种变分模态分解定理和同步挤压小波变换理论相结合的时变结构响应信号瞬时频率识别新方法。该方法首先利用响应信号的小波量图判断分量信号的个数，然后通过变分模态分解定理将多分量信号自适应地分解为多个分量信号，最后对分解得到的分量信号进行同步挤压小波变换并识别其瞬时频率。通过一个多分量信号数值算例、一个质量突变悬臂梁试验和一个时变拉索试验验证该方法的有效性，研究结果表明：提出的新方法能够有效识别时变结构响应信号的瞬时频率，且识别效果优于传统的希尔伯特-黄变换和连续小波变换。

Abstract

A combined method based on variational mode decomposition (VMD) and synchrosqueezing wavelet transform (SWT) was proposed to identify instantaneous frequencies from multi-component response signals of civil engineering structures.The wavelet scalogram was first introduced to estimate the number of the components contained in a response signal.Then, the VMD was used to decompose the response signal into several mono-components self-adaptively and the SWT was performed on the decomposed component signals to extract their instantaneous frequencies.A multi-component simulation, an aluminum cantilever beam test with abrupt mass reduction and a steel cable test with time-varying tension forces were used to verify the effectiveness and accuracy of the proposed method.The results demonstrated that the proposed method performs better than the traditional Hilbert-Huang transform and the continuous wavelet transform.

导出引用

刘景良1 郑锦仰1 林友勤2 邱仁辉1 骆勇鹏1. 变分模态分解和同步挤压小波变换识别时变结构瞬时频率[J]. 振动与冲击, 2018, 37(20): 24-31

LIU Jingliang1,ZHENG Jinyang1,LIN Youqin2,QIU Renhui1,LUO Yongpeng1. Instantaneous frequency identification of time-varying structures using variational mode decomposition and synchrosqueezing wavelet transform[J]. Journal of Vibration and Shock, 2018, 37(20): 24-31

参考文献

[1] Huang N E，Wu Z. A review on Hilbert-Huang transform：Method and its applications to geophysical studies[J]. Reviews of Geophysics，2008，46(2)： G2006.
[2] Smith J S. The local mean decomposition and its application to EEG perception data[J]. Journal of the Royal Society Interface，2005，2(5)：443-445.
[3] Wu Z，Huang N E. Ensemble empirical mode decompositio：a noise-assisted data analysis method[J]. Advances in Adaptive Data Analysis，2009，1(1)：1-41.
[4] 黎恒，李智，莫玮，等. 噪声干扰环境下抑制EMD模态混叠方法[J]. 信号处理，2015，31(8)：956-961.
LI Heng，LI Zhi，MO Wei，et al. Resolving the mode-mixing problem of EMD in the presence of noise[J]. Journal of Signal Processing，2015，31(8)：956-961.
[5] 刘长良，武英杰，甄成刚. 基于变分模态分解和模糊C均值聚类的滚动轴承故障诊断[J]. 中国电机工程学报，2015，35(13)：3358-3365.
LIU Chang-liang，WU Ying-jie，ZHEN Cheng-gang. Rolling bearing fault diagnosis based on variational mode decomposition and fuzzy C means clustering[J]. Proceedings of the CSEE，2015，35(13)：3358-3365.
[6] Dragomiretskiy K，Zosso D. Variational mode decomposition[J]. IEEE Transactions on Signal Processing，2014，62(3)：531-544.
[7] Wang Y，Markert R，Xiang J，et al. Research on variational mode decomposition and its application in detecting rub-impact fault of the rotor system[J]. Mechanical Systems and Signal Processing，2015，60-61：243-251.
[8] 张蒙，朱永利，张宁，等. 基于变分模态分解和多尺度排列熵的变压器局部放电信号特征提取[J]. 华北电力大学学报，2016，43(6)：31-37.
ZHANG Meng，ZHU Yong-li，ZHANG Ning，et al. Feature extraction of transformer partial discharge signals based on varitional mode decomposition and multi-scale permutation entropy[J]. Journal of North China Electric Power University，2016，43(6)：31-37.
[9] Chen S，Dong X，Peng Z，et al. Nonlinear chirp mode decomposition：A variational method[J]. IEEE Transactions on Signal Processing，2017，65(22)：6024-6037.
[10] 向玲，张力佳. 变分模态分解在转子故障诊断中的应用[J]. 振动、测试与诊断，2017，37(4)：793-799.
XIANG Ling，ZHANG Li-jia. Application of variational mode decomposition in fault diagnosis of rotors[J]. Journal of Vibration，Measurement and Diagnosis，2017，37(4)：793-799.
[11] 郑小霞，周国旺，任浩瀚，等. 基于变分模态分解和排列熵的滚动轴承故障诊断方法[J]. 振动与冲击，2017，36(22)：22-28.
ZHENG Xiao-xia，ZHOU Guo-wang，REN Hao-han，et al. A rolling bearing fault diagnosis method based on variational mode decomposition on permutation entropy[J]. Journal of Vibration and Shock，2017，36(22)：22-28.
[12] 唐贵基，王晓龙. 变分模态分解方法及其在滚动轴承早期故障诊断中的应用[J]. 振动工程学报，2016，49(5)：638-648.
TANG Gui-ji，WANG Xiao-long. Variational mode decomposition method and its application on incipient fault diagnosis of rolling bearing[J]. Journal of Vibration Engineering，2016，49(5)：638-648.
[13] 赵洪山，郭双伟，高夺. 基于奇异值分解和变分模态分解的轴承故障特征提取[J]. 振动与冲击，2016，35(22)：183-188.
ZHAO Hong-shan，GUO Shuang-wei，GAO Duo. Fault feature extraction of bearing faults based on singular value decomposition and variational modal decomposition[J]. Journal of Vibration and Shock，2016，35(22)：183-188.
[14] Daubechies I，Lu J，Wu H T. Synchrosqueezed wavelet transforms：An empirical mode decomposition-like tool[J]. Applied and Computational Harmonic Analysis，2011，30(2)：243-261.
[15] 刘景良，任伟新，王佐才，等. 基于同步挤压小波变换的结构瞬时频率识别[J]. 振动与冲击，2013，32(18)：37-42.
LIU Jing-liang，Ren Wei-xin，WANG Zuo-cai，et al. Instantaneous frequency identification based on synchrosqueezing wavelet transformation[J]. Journal of Vibration and Shock，2013，32(18)：37-42.
[16] 汪祥莉，王斌，王文波，等. 混沌干扰中基于同步挤压小波变换的谐波信号提取方法[J]. 物理学报，2015，64(10)：15-24.
WANG Xiang-li，WANG Bin，WANG Wen-bo，et al. Harmonic signal extraction from chaotic interference based on synchrosqueezed wavelet transform[J]. Acta Physica Sinica，2015，64(10)：15-24.
[17] Wang Z C，Ren W X，Liu J L. A synchrosqueezed wavelet transform enhanced by extended analytical mode decomposition method for dynamic signal reconstruction[J]. Journal of Sound and Vibration，2013，332(22)：6016-6028.
[18] Cao H，Xi S，Chen X，et al. Zoom synchrosqueezing transform and iterative demodulation：Methods with application[J]. Mechanical Systems and Signal Processing，2016，72-73：695-711.
[19] 陈志新，徐金梧，杨德斌，等. 基于经验模态分解的混沌噪声背景下弱信号检测与信号提取[J]. 机械科学与技术，2006，25(2)：220-224.
CHEN Zhi-xin，XU Jin-wu，YANG De-bing，et al. Weak signal detection and extraction against the background of chaotic noise based on empirical mode decomposition[J]. Mechanical Science and Technology，2006，25(2)：220-224.
[20] Carmona R A，Hwang W L，Torresani B. Characterization of signals by the ridges of their wavelet transforms[J]. IEEE Transactions on Signal Processing，1997，45(10)：2586-2590.
[21] 王超，任伟新，黄天立. 基于复小波变换的结构瞬时频率识别[J]. 振动工程学报，2009，22(5)：492-496.
WANG Chao，REN Wei-xin，HUANG Tian-li. Instantaneous frequency identification of a structure based on complex wavelet transform [J]. Journal of Vibration Engineering，2009，22(5)：492-496.