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    Substructure damage identification based on wavelet-domain response reconstruction

    Access Status
    Fulltext not available
    Authors
    Li, Jun
    Hao, Hong
    Date
    2014
    Type
    Journal Article
    
    Metadata
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    Citation
    Li, J. and Hao, H. 2014. Substructure damage identification based on wavelet-domain response reconstruction. Structural Health Monitoring. 13 (4): pp. 389-405.
    Source Title
    Structural Health Monitoring
    DOI
    10.1177/1475921714532991
    ISSN
    1475-9217
    School
    Department of Civil Engineering
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/DE140101741
    URI
    http://hdl.handle.net/20.500.11937/19560
    Collection
    • Curtin Research Publications
    Abstract

    This article presents experimental verification on damage identification of a substructure using a wavelet-domain response reconstruction technique. The response reconstruction is based on the unit impulse response function in the wavelet domain to form a transformation matrix between two different sets of time-domain response vectors. The initial finite element model updating is performed to achieve an accurate model in the intact stage as a baseline, and measuredacceleration responses from the damaged substructure are used for the damage identification. Substructure damage identification is conducted by minimizing the discrepancy between a measured response vector and the reconstructed one. A dynamic response sensitivity-based model updating method is used for the identification of the target substructure. Local damage is identified as a change in the elemental stiffness factors. The adaptive Tikhonov regularization technique is adopted to improve the identification results with measured responses including measurement and environmental noises in laboratory. Experimental studies on a 7-storey plane frame structure are conducted to investigate the accuracy of the presented response reconstruction technique and the performance of substructure damage identification approach. Good response reconstruction accuracy is obtained with the baseline model, and the introduceddamages in the substructure can be identified effectively. The damage locations are identified correctly with a close estimation of damage extents.

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