An Adaptive Chirp Mode Decomposition-Based Method for Modal Identification of Time-Varying Structures

被引:0
|
作者
Yao, Xiao-Jun [1 ,2 ]
Lv, Yu-Chun [2 ]
Yang, Xiao-Mei [3 ]
Wang, Feng-Yang [1 ]
Zheng, Yong-Xiang [4 ]
机构
[1] Dongguan Univ Technol, Guangdong Prov Key Lab Intelligent Disaster Preven, Dongguan 523808, Peoples R China
[2] Hebei Univ Technol, Sch Civil & Transportat Engn, Tianjin 300401, Peoples R China
[3] Fuzhou Univ, Coll Civil Engn, Fuzhou 350108, Peoples R China
[4] Shijiazhuang Tiedao Univ, Railway Engn Safety Control Minist Educ, Key Lab Rd, Shijiazhuang 050043, Peoples R China
基金
中国国家自然科学基金;
关键词
modal identification; adaptive chirp mode decomposition; time-varying structure; instantaneous frequency; time-frequency distribution; PARAMETER-IDENTIFICATION;
D O I
10.3390/math12193157
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Modal parameters are inherent characteristics of civil structures. Due to the effect of environmental factors and ambient loads, the physical and modal characteristics of a structure tend to change over time. Therefore, the effective identification of time-varying modal parameters has become an essential topic. In this study, an instantaneous modal identification method based on an adaptive chirp mode decomposition (ACMD) technique was proposed. The ACMD technique is highly adaptable and can accurately estimate the instantaneous frequencies of a structure. However, it is important to highlight that an initial frequency value must be selected beforehand in ACMD. If the initial frequency is set incorrectly, the resulting instantaneous frequencies may lack accuracy. To address the aforementioned problem, the Welch power spectrum was initially developed to extract a high-resolution time-frequency distribution from the measured signals. Subsequently, the time-frequency ridge was identified based on the maximum energy position in the time-frequency distribution plot, with the frequencies associated with the time-frequency ridge serving as the initial frequencies. Based on the initial frequencies, the measured signals with multiple degrees of freedom could be decomposed into individual time-varying components with a single degree of freedom. Following that, the instantaneous frequencies of each time-varying component could be calculated directly. Subsequently, a sliding window principal component analysis (PCA) method was introduced to derive instantaneous mode shapes. Finally, vibration data collected under various operational scenarios were used to validate the proposed method. The results demonstrated the effective identification of time-varying modal parameters in real-world civil structures, without missing modes.
引用
收藏
页数:21
相关论文
共 50 条
  • [41] Modal analysis and identification of time varying structures
    Abdelghani, M
    LeRohellec, F
    Crosnier, B
    NEW ADVANCES IN MODAL SYNTHESIS OF LARGE STRUCTURES: NON-LINEAR DAMPED AND NON-DETERMINISTIC CASES, 1997, : 133 - 143
  • [42] Modal parameters identification of time-varying system based on multi-scale chirplet sparse signal decomposition
    Yu, D. (djyu@hnu.edu.cn), 1600, Chinese Mechanical Engineering Society (49):
  • [43] Adaptation of the concept of modal analysis to time-varying structures
    Liu, K
    Kujath, MR
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 1999, 13 (03) : 413 - 422
  • [44] Parametric identification of time-varying systems from free vibration using intrinsic chirp component decomposition
    Sha Wei
    Shiqian Chen
    Xingjian Dong
    Zhike Peng
    Wenming Zhang
    Acta Mechanica Sinica, 2020, 36 : 188 - 205
  • [45] Parametric identification of time-varying systems from free vibration using intrinsic chirp component decomposition
    Wei, Sha
    Chen, Shiqian
    Dong, Xingjian
    Peng, Zhike
    Zhang, Wenming
    ACTA MECHANICA SINICA, 2020, 36 (01) : 188 - 205
  • [46] An integrated multivariate empirical mode decomposition method towards modal identification of structures'
    Sadhu, Ayan
    JOURNAL OF VIBRATION AND CONTROL, 2017, 23 (17) : 2727 - 2741
  • [47] Modal parameter identification of linear time-varying structures using Kriging shape function
    Yang, Wu
    Liu, Li
    Zhou, Sida
    Ma, Zhisai
    Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2015, 36 (04): : 1169 - 1176
  • [48] Modal parameter identification of time-varying systems using the time-varying multivariate autoregressive model
    Liu, Lilan
    Liu, Hongzhao
    Wu, Ziying
    Yuan, Daning
    Li, Pengfei
    Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Vol 1, Pts A-C, 2005, : 1817 - 1822
  • [49] New Parameter-Identification Method Based on QR Decomposition for Nonlinear Time-Varying Systems
    Chen, Tengfei
    He, Huan
    He, Cheng
    Chen, Guoping
    JOURNAL OF ENGINEERING MECHANICS, 2019, 145 (01)
  • [50] Seismic time-frequency analysis via time-varying filtering based empirical mode decomposition method
    Chen, Siyuan
    Cao, Siyuan
    Sun, Yaoguang
    Lin, Ying
    Gao, Jun
    JOURNAL OF APPLIED GEOPHYSICS, 2022, 204