• Title of article

    Moving Window Differential Evolution Independent Component Analysis-Based Operational Modal Analysis for Slow Linear Time-Varying Structures

  • Author/Authors

    Zong, Yongshuo School of Informatics - Xiamen University, China , Chen, Jinling School of Informatics - Xiamen University, China , Tao,Siyi School of Informatics - Xiamen University, China , Wang, Cheng College of Computer Science and Technology - Huaqiao University, China , Xiahou, Jianbing School of Informatics - Xiamen University, China

  • Pages
    9
  • From page
    1
  • To page
    9
  • Abstract
    In order to identify time-varying transient modal parameters only from nonstationary vibration response measurement signals for slow linear time-varying (SLTV) structures which are weakly damped, a moving window differential evolution (DE) independent component analysis- (ICA-) based operational modal analysis (OMA) method is proposed in this paper. Firstly, in order to overcome the problems in traditional ICA-based OMA, such as easy to go into local optima and difficult-to-identify high-order modal parameters, we combine DE with ICA and propose a differential evolution independent component analysis- (DEICA-) based OMA method for linear time invariant (LTI) structures. Secondly, we combine the moving widow technique with DEICA and propose a moving window differential evolution independent component analysis- (MWDEICA-) based OMA method for SLTV structures. The MWDEICA-based OMA method has high global searching ability, robustness, and complexity of time and space. The modal identification results in a three-degree-of-freedom structure with slow time-varying mass show that this MWDEICA-based OMA method can identify transient time-varying modal parameters effectively only from nonstationary vibration response measurement signals and has better performances than moving window traditional ICA-based OMA.
  • Keywords
    Modal Analysis , Operational , Moving Window , Differential Evolution , Slow Linear Time-Varying Structures
  • Journal title
    Scientific Programming
  • Serial Year
    2020
  • Record number

    2610182