Physical parametric identification of time-varying system based onchirp wavelet integration

被引：0
|
作者：
Zhang J. [1 ]
Shi Z. [1 ]
Zhao Z. [1 ]
机构：
[1] State Key Lab of Mechanics and Control of Mechanical Structures, College of Aeronautics, Nanjing University of Aeronautics and Astronautics, Nanjing
来源：
Shi, Zhiyu | 1600年 / Chinese Vibration Engineering Society卷 / 39期
关键词：
Acceleration response; Chirp wavelet integration; Parametric identification; Signal reconstruction; Time-varying system;
D O I：
10.13465/j.cnki.jvs.2020.21.035
中图分类号：
学科分类号：
摘要：
A method of chirp wavelet integration was derived based on the short-time linear change assumption.Applying this method, velocity and displacement response signals of a time-varying structure were reconstructed only with its acceleration response signal. Then, time-varying stiffness and damping of the structure were identified by constructing a least squares algorithm when the structure's mass parameters were known in advance. It was shown that due to introducing frequency modulation slope parameter to characterize the short-term frequency modulation characteristics of a signal, compared with the traditional identification method, this method can better track fast time-varying parameters and greatly improve computational efficiency. In a simulation example, a 3-DOF time-varying structure model was constructed, and its physical parameters were identified under various time-varying conditions to verify the correctness, applicability and anti-noise ability of the proposed method. © 2020, Editorial Office of Journal of Vibration and Shock. All right reserved.
引用
下载
收藏
页码：267 / 273
页数：6
相关论文
共 21 条
  • [1] (1989)
  • [2] YU Kaiping, PANG Shiwei, ZHAO Jie, Advances in method of time-varying linear/nonlinear structural system identification and parameter estimate, Chinese Science Bullletin, 54, 20, pp. 3147-3156, (2009)
  • [3] BAO C X, HAO H, LI Z X, Et al., Time-varying system identification using a newly improved HHT algorithm, Computers and Structures, 87, 23, pp. 1611-1623, (2009)
  • [4] CHENG Junsheng, ZHANG Kang, YANG Yu, Et al., Comparison between the methods of local mean decomposition and empirical mode decomposition, Journal of Vibration and Shock, 28, 5, pp. 13-16, (2009)
  • [5] SHI Z Y, LAW S S, XU X., Identification of linear time-varying MDOF dynamic systems from forced excitation using Hilbert transform and EMD method, Journal of Sound and Vibration, 321, 3, pp. 572-589, (2009)
  • [6] LIU K., Identification of linear time-varying systems, Journal of Sound and Vibration, 206, 4, pp. 487-505, (1997)
  • [7] PANG Shiwei, YU Kaiping, ZOU Jingxiang, Time-varying system identification using recursive subspace method based on free response data, Journal of Vibration Engineering, 18, 2, pp. 233-237, (2005)
  • [8] ZHOU H T, YU K P, CHEN Y S, Et al., Time-varying modal parameters identification by subspace tracking algorithm and its validation method, Shock and Vibration, 2, pp. 1-12, (2018)
  • [9] SHI Z Y, LAW S S, LI H N., Subspace-based identification of time-varying system, Journal of AIAA, 45, 8, pp. 2042-2050, (2007)
  • [10] XU Xiuzhong, HUA Hongxing, ZHANG Zhiyi, Et al., Time-varying modal frequency identification by using time-frequency representation, Journal of Vibration and Shock, 21, 2, pp. 36-40, (2002)
123