Modal parameter identification based on variational mode decomposition

被引:0
|
作者
Zhao Y. [1 ,2 ]
Dou Y. [1 ]
Zhang M. [3 ]
机构
[1] School of Civil Engineering, Hebei University of Technology, Tianjin
[2] School of Civil Engineering, Hebei University of Engineering, Handan
[3] School of Civil Engineering, Dalian University of Technology, Dalian
来源
关键词
Closely spaced modes; Modal parameter identification; Nonlinear system; Variational mode decomposition(VMD);
D O I
10.13465/j.cnki.jvs.2020.02.017
中图分类号
学科分类号
摘要
An out-put only modal parameter identification technique based on variational mode decomposition (VMD) was developed for civil structures. The free decay response (FDR, which can be recorded in free vibration tests or reconstructed from ambient vibration responses) of a structure was decomposed into modal responses using VMD. The instantaneous modal frequencies were calculated from the modal responses with the empirical envelope (EE) method, while the instantaneous modal damping ratios were calculated using a newly developed procedure. Mode shape vectors were indentified using the modal responses extracted from the FDRs by processing all the available sensors data on the structure. The calculated instantaneous modal frequencies and instantaneous modal damping ratios can capture any transient modal parameter variations. A series of numerical and experimental case studies were conducted to demonstrate the efficiency and highlight the superiority of the proposed method in modal parameter identification using free vibration or ambient vibration data. The proposed method was proved to be efficient in modal parameter identification for both linear and nonlinear systems, and can be applied to systems with closely spaced modes and sudden modal parameter variations. © 2020, Editorial Office of Journal of Vibration and Shock. All right reserved.
引用
收藏
页码:115 / 122
页数:7
相关论文
共 50 条
  • [21] Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition
    Miao, Yonghao
    Zhao, Ming
    Lin, Jing
    [J]. ISA TRANSACTIONS, 2019, 84 : 82 - 95
  • [22] A new Developed Modal Parameter Identification Method Based on Empirical Mode Decomposition and Natural Excitation Technique
    Song, Xingyu
    Ma, Hongwei
    Wang, Kun
    [J]. X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017), 2017, 199 : 1020 - 1025
  • [23] Recursive variational mode decomposition enhanced by orthogonalization algorithm for accurate structural modal identification
    Shang, Xu-Qiang
    Huang, Tian -Li
    Chen, Hua-Peng
    Ren, Wei-Xin
    Lou, Meng -Lin
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 197
  • [24] Structural Modal System Identification Using Variational Mode Decomposition and Teager Energy Operators
    Jin H.
    Lin J.
    [J]. Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2019, 39 (03): : 544 - 551
  • [25] Early chatter identification based on an optimized variational mode decomposition
    Yang, Kai
    Wang, Guofeng
    Dong, Yi
    Zhang, Quanbiao
    Sang, Lingling
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 115 : 238 - 254
  • [26] Identification of electromechanical oscillatory modes based on variational mode decomposition
    Arrieta Paternina, Mario R.
    Tripathy, Rajesh Kumar
    Zamora-Mendez, Alejandro
    Dotta, Daniel
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2019, 167 : 71 - 85
  • [27] Modal Parameter Identification of Nonlinear Systems Based on Hilbert Vibration Decomposition
    Xinjian Ren
    [J]. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 2023, 47 : 389 - 397
  • [28] Modal Parameter Identification of Nonlinear Systems Based on Hilbert Vibration Decomposition
    Ren, Xinjian
    [J]. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING, 2023, 47 (01) : 389 - 397
  • [29] A Combined Method for Time-Varying Parameter Identification Based on Variational Mode Decomposition and Generalized Morse Wavelet
    Wang, Chao
    Zhang, Jing
    Zhu, Hong Pin
    [J]. INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS, 2020, 20 (07)
  • [30] Fault identification method for distribution network based on parameter optimized variational mode decomposition and convolutional neural network
    Hou, Sizu
    Guo, Wei
    [J]. IET GENERATION TRANSMISSION & DISTRIBUTION, 2022, 16 (04) : 737 - 749