Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Bayesian based nonlinear model updating using instantaneous characteristics of structural dynamic responses

    Access Status
    Fulltext not available
    Authors
    Xin, Y.
    Hao, Hong
    Li, Jun
    Wang, Z.
    Wan, H.
    Ren, W.
    Date
    2019
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Xin, Y. and Hao, H. and Li, J. and Wang, Z. and Wan, H. and Ren, W. 2019. Bayesian based nonlinear model updating using instantaneous characteristics of structural dynamic responses. Engineering Structures. 183: pp. 459-474.
    Source Title
    Engineering Structures
    DOI
    10.1016/j.engstruct.2019.01.043
    ISSN
    0141-0296
    URI
    http://hdl.handle.net/20.500.11937/73745
    Collection
    • Curtin Research Publications
    Abstract

    This paper proposes a Bayesian based nonlinear model updating approach using the instantaneous amplitudes of the decomposed dynamic responses. Uncertainty quantification of the model updating results due to the measurement noise is conducted. The residual of the instantaneous amplitudes of the decomposed structural dynamic responses between the test structure and the analytical nonlinear model is used to construct the maximum likelihood function. Since nonlinear model parameters and simulated error variances of the instantaneous parameters are all unknown, the extended maximum likelihood estimation method is used to update these parameters. The uncertainty in the updated nonlinear model parameters can be evaluated by using the Cram-Rao lower bound theorem with the exact Fisher Information matrix. A numerical study on a three-storey building structure model under earthquake excitation is performed to verify the accuracy and performance of the proposed approach. An experimental verification on a high voltage switch structure under harmonic excitation is conducted to investigate the accuracy of using the proposed approach for nonlinear model updating. Both numerical and experimental results demonstrate that the proposed approach is reliable and accurate for nonlinear model updating, with the capacity of considering the uncertain noise effect in the measurements.

    Related items

    Showing items related by title, author, creator and subject.

    • Damage Detection in Initially Nonlinear Structures Based on Variational Mode Decomposition
      Xin, Y.; Li, Jun ; Hao, Hong (2020)
      Nonlinear characteristics in the dynamic behaviors of civil structures degrade the performance of damage detection of the linear theory based traditional time- and frequency-domain methods. To overcome this challenge, ...
    • A gradient algorithm for optimal control problems with model-reality differences
      Kek, S.L.; Aziz, M.I.A.; Teo, Kok Lay (2015)
      In this paper, we propose a computational approach to solve a model-based optimal control problem. Our aim is to obtain the optimal solution of the nonlinear optimal control problem. Since the structures of both problems ...
    • Improved decentralized structural identification with output-only measurements
      Ni, P.; Xia, Y.; Li, Jun; Hao, Hong (2017)
      © 2017 Elsevier Ltd. This paper proposes an improved decentralized structural identification approach with output-only measurements. The improved approach can be used for system identification of both linear and nonlinear ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.