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    Identification of Minor Structural Damage Based on Electromechanical Impedance Sensitivity and Sparse Regularization

    Access Status
    Fulltext not available
    Authors
    Fan, X.
    Li, Jun
    Hao, Hong
    Ma, S.
    Date
    2018
    Type
    Journal Article
    
    Metadata
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    Citation
    Fan, X. and Li, J. and Hao, H. and Ma, S. 2018. Identification of Minor Structural Damage Based on Electromechanical Impedance Sensitivity and Sparse Regularization. Journal of Aerospace Engineering. 31 (5).
    Source Title
    Journal of Aerospace Engineering
    DOI
    10.1061/(ASCE)AS.1943-5525.0000892
    ISSN
    0893-1321
    School
    School of Civil and Mechanical Engineering (CME)
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/DE140101741
    URI
    http://hdl.handle.net/20.500.11937/68674
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 American Society of Civil Engineers. This paper proposes a structural damage identification approach based on model updating with electromechanical impedance sensitivity and the sparse regularization technique to identify the location and severity of minor damage in structures. The sensitivities of the resonance frequency shifts in the impedance responses with respect to the stiffness parameters of the host structure are calculated and used to identify the damage with a small number of resonance frequency shifts. Numerical verifications on a single lead zirconate titanate (PZT) transducer patch and a PZT on a narrow aluminum plate structure are conducted to validate the finite-element modeling technique to calculate the impedance. The effectiveness and performance of the proposed structural damage identification approach are demonstrated with numerical simulations on an aluminum plate model attached to a PZT transducer patch. The initial finite-element model and a limited number of resonance frequency shifts in the impedance responses are used for the identification. Sparse regularization, namely, the l1 regularization technique, is used for solving the inverse problem. Single and multiple damage scenarios are considered. The effects of noise in the measured impedance signals and the number of available frequency shifts on the performance of the proposed damage identification approach are investigated. The results demonstrate the performance and robustness of the proposed approach.

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