TIME DOMAIN DATA-BASED MODEL FREE STRUCTURAL NONLINEAR PERFORMANCE IDENTIFICATION

被引:0
|
作者
Xu, Bin [1 ]
He, Jia [1 ]
Masri, Sami F. [1 ]
机构
[1] Hunan Univ, Coll Civil Engn, Changsha 410082, Hunan, Peoples R China
关键词
nonlinear restoring force identification; nonlinear systems; 4-story structure; impact force; time series; least-squares techniques; MR damper; HYSTERETIC SYSTEMS; MDOF SYSTEMS;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In fact, nonlinearity is generic and may arise in a damaged engineering structure. For example, the subsequently open and close of cracks in concrete structures under dynamic loadings make the vibration behavior nonlinear. However, nonlinear dynamical systems theory is far less established than linear system. Usually, the damage is represented by the decrease in structural stiffness and most of the currently available vibration-based system identification and damage detection approaches are based on modal parameters, namely the natural frequencies, mode shapes and damping ratios, and/or their derivations, which are only suitable for linear systems and the basis of modal analysis is no longer valid in the presence of nonlinearity. It has been widely recognized that one of the major challenges in damage detection, early warning and damage prognosis is to obtain reasonably accurate identification of minor nonlinearity such as hysteresis performance of structural members under dynamic excitations which is the direct indicator of damage initiation and development. In this study, a data-based model free nonlinearity identification approach in the form of hysteresis using structural dynamic response and complete and incomplete excitation measurement time series was proposed and validated experimentally with a 4-story frame structure equipped with smart devices of magneto-rheological (MR) dampers to simulate nonlinear performance. Firstly, as an optimization method, the least-squares technique was employed to identify the system matrices of an equivalent linear system of the nonlinear structure model basing on the excitation force by hammer and the corresponding vibration measurements; and secondly, the nonlinear restoring force of the structure was identified and compared with the test measurements finally. Results show that the proposed data-based approach is capable of identifying the nonlinear behavior of engineering structures and present an applicable way for the evaluation of structure damage initiation and development under dynamic loads.
引用
收藏
页码:59 / 69
页数:11
相关论文
共 50 条
  • [31] Time Data-Based Iterative Method for Frequency-Domain Multivariable Systems Identification by Optimized Expansion of Rational Functions
    Oliveira, Marcelo A.
    Pellanda, Paulo C.
    Ades, Roberto
    Silveira, Bruno P.
    JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS, 2019, 30 (05) : 666 - 676
  • [32] Time Data-Based Iterative Method for Frequency-Domain Multivariable Systems Identification by Optimized Expansion of Rational Functions
    Marcelo A. Oliveira
    Paulo C. Pellanda
    Roberto Ades
    Bruno P. Silveira
    Journal of Control, Automation and Electrical Systems, 2019, 30 : 666 - 676
  • [33] TIME-DOMAIN STRUCTURAL IDENTIFICATION USING FREE RESPONSE MEASUREMENTS
    MOUSTAFA, KAF
    INTERNATIONAL JOURNAL OF CONTROL, 1992, 56 (01) : 51 - 65
  • [34] Data-based stability analysis of a class of nonlinear discrete-time systems
    Wang, Zhuo
    Liu, Derong
    INFORMATION SCIENCES, 2013, 235 : 36 - 44
  • [35] Structural Nonlinear Damage Identification Algorithm Based on Time Series ARMA/GARCH Model
    Chen, Liu-jie
    Yu, Ling
    ADVANCES IN STRUCTURAL ENGINEERING, 2013, 16 (09) : 1597 - 1609
  • [36] Data-based modeling and identification for general nonlinear dynamical systems by the multidimensional Taylor network
    Yan, Hong-Sen
    Bi, Zhong-Tian
    Zhou, Bo
    Wan, Xiao-Qin
    Zhang, Jiao-Jun
    Wang, Guo-Biao
    KYBERNETES, 2023, 52 (10) : 4257 - 4271
  • [37] A comparative Study of Model-Based and Data-Based Model Order Reduction Techniques for Nonlinear Systems
    Aizad, T.
    Maganga, O.
    Sumislawska, M.
    Burnham, K. J.
    PROGRESS IN SYSTEMS ENGINEERING, 2015, 366 : 83 - 88
  • [38] Bioartificial human liver cell systems: Data-based identification of performance predictors
    不详
    INTERNATIONAL JOURNAL OF ARTIFICIAL ORGANS, 2005, 28 (09): : 869 - 869
  • [39] Data-Based Adaptive Model Predictive Control for Stochastic Sampled-Data Nonlinear Systems
    Fu, Shijia
    Sun, Haoyuan
    Liu, Zheng
    Han, Honggui
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2024, 54 (11): : 6813 - 6824
  • [40] Study on structural damage identification using acceleration data in time domain
    Zhang, Li-Tao
    Li, Zhao-Xia
    Fei, Qing-Guo
    Zhendong yu Chongji/Journal of Vibration and Shock, 2007, 26 (09): : 138 - 141