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    A prototype tool of optimal wireless sensor placement for structural health monitoring

    Access Status
    Fulltext not available
    Authors
    Shi, W.
    Wu, Changzhi
    Wang, X.
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Shi, W. and Wu, C. and Wang, X. 2018. A prototype tool of optimal wireless sensor placement for structural health monitoring, pp. 53-73.
    Source Title
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    DOI
    10.1007/978-3-319-91638-5_3
    ISBN
    9783319916378
    School
    School of Design and the Built Environment
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/LP160100528
    URI
    http://hdl.handle.net/20.500.11937/69818
    Collection
    • Curtin Research Publications
    Abstract

    © Springer International Publishing AG, part of Springer Nature 2018. With increasing collapses of civil infrastructures and popularized utilization of large-scale structures, worldwide deployment of structural health monitoring (SHM) systems is of importance in emerging and future SHM industry. A reliable and practical tool of optimal wireless sensor placement (OWSP) can promote implementation of wireless-based SHM systems by reducing construction cost, extending lifetime and improving detection accuracy. This paper presents a prototype of wireless sensor placement (WSP) for bridge SHM based on multi-objective optimisation (MOO) technique and bridge information modelling (BrIM) technology. MOO technique is used to determine sensor locations by simultaneously searching for multiple trade-offs among structural engineering, wireless engineering and construction management. The BrIM model will be used as a platform to validate and visualize the proposed MOO. A BrIM integrated design tool will be developed to improve the efficiency in design stage through visualisation capabilities and semantic enrichment of a bridge model. As future applications, 4D BrIM that combines time-related information in visual environments with the 3D geometric and semantic BrIM model will help engineers and contractors to visualise possible defects and project costs in the real world.

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