A modified blind source separation algorithm for underdetermined structural modal analysis

被引:0
|
作者
Li, Yu-Zu [1 ]
Fang, Sheng-En [2 ]
机构
[1] Fuzhou Univ, Sch Civil Engn, Fuzhou 350108, Fujian, Peoples R China
[2] Fuzhou Univ, Natl & Local Joint Engn Res Ctr Seism & Disaster I, Fuzhou 350108, Fujian, Peoples R China
关键词
Structural modal analysis; Modified blind source separation; Mode decomposition; Multi-synchroextracting transform; Sparse matrix; COMPONENT ANALYSIS; IDENTIFICATION;
D O I
10.1016/j.engstruct.2024.119452
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
To improve the mode decomposition capacity for underdetermined and unclear modes, a modified blind source separation (MBSS) method has been proposed, where a multi-synchroextracting transform algorithm with a sliding window is proposed for a higher sparsity time-frequency spectrum. The proposed transform algorithm incorporates an iterative formula of the instantaneous frequency with a sliding window. Then, it is embedded into the existing novel blind source separation (NBSS) method to highly improve the modal decomposition accuracy. The feasibility of the proposed method has been verified against a numerical 3DOF mass-spring-damper system, a numerical three-story frame structure, and an experimental five-story steel frame. The analysis results demonstrate that the proposed MBSS method can well decompose the acceleration signals, providing better precisions than the NBSS method under the circumstance of unclear and underdetermined modes. Moreover, the proposed method has higher decomposition accuracy for close modes.
引用
收藏
页数:22
相关论文
共 50 条
  • [31] Noise Source Separation based on the Blind Source Separation
    Yang, Yang
    Li, Zuoli
    Wang, Xiuqin
    Zhang, Di
    2011 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, 2011, : 2236 - +
  • [32] Maximum contrast analysis for nonnegative blind source separation
    Yang, Zuyuan
    Xiang, Yong
    Xie, Shengli
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2011, 62 (11) : 3997 - 4006
  • [33] Sparse coding with adaptive dictionary learning for underdetermined blind speech separation
    Xu, Tao
    Wang, Wenwu
    Dai, Wei
    SPEECH COMMUNICATION, 2013, 55 (03) : 432 - 450
  • [34] MULTISCALE BLIND SOURCE SEPARATION
    Behr, Merle
    Holmes, Chris
    Munk, Axel
    ANNALS OF STATISTICS, 2018, 46 (02): : 711 - 744
  • [35] Null space component analysis for noisy blind source separation
    Hwang, Wen-Liang
    Ho, Jinn
    SIGNAL PROCESSING, 2015, 109 : 301 - 316
  • [36] A blind source separation method: Nonlinear chirp component analysis
    Peng, Xujun
    Shi, Zhiyu
    Jin, Pengfei
    Zhang, Xiaoyan
    Yang, Zheng
    Feng, Xuelei
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2024, 216
  • [37] Independent vector analysis for convolutive blind noncircular source separation
    Zhang, Hefa
    Li, Liping
    Li, Wanchun
    SIGNAL PROCESSING, 2012, 92 (09) : 2275 - 2283
  • [38] A Jacobi Generalized Orthogonal Joint Diagonalization Algorithm for Joint Blind Source Separation
    Gong, Xiao-Feng
    Mao, Lei
    Liu, Ying-Liang
    Lin, Qiu-Hua
    IEEE ACCESS, 2018, 6 : 38464 - 38474
  • [39] Underdetermined blind source separation of pipeline leak vibration signals based on empirical mode decomposition and joint approximate diagonalization of eigenmatrices
    Sun, Jiedi
    Xiao, Qiyang
    Wen, Jiangtao
    Yang, Yiguang
    JOURNAL OF VIBROENGINEERING, 2015, 17 (03) : 1326 - 1340
  • [40] A novel damage detection algorithm using time-series analysis-based blind source separation
    Sadhu, A.
    Hazra, B.
    SHOCK AND VIBRATION, 2013, 20 (03) : 423 - 438