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Switching Response Surface Models for Structural Health Monitoring of Bridges

In: Surrogate-Based Modeling and Optimization

Author

Listed:
  • Keith Worden

    (University of Sheffield, Dynamics Research Group, Department of Mechanical Engineering)

  • Elizabeth J. Cross

    (University of Sheffield, Dynamics Research Group, Department of Mechanical Engineering)

  • James M. W. Brownjohn

    (University of Sheffield, Vibration Engineering Section, Department of Civil and Structural Engineering)

Abstract

Structural health monitoring (SHM) is the discipline of diagnosing damage and estimating safe remaining life for structures and systems. Often SHM is accomplished by detecting changes in measured quantities from the structure of interest; if there are no competing explanations for the changes, one infers that they are the result of damage. If the structure of interest is subject to changes in its environmental or operational conditions, one must understand the effects of these changes in order that one does not falsely claim that damage has occurred when one observes measurement changes. This problem—the problem of confounding influences—is particularly pressing for civil infrastructure where the given structure is usually openly exposed to the weather and may be subject to strongly varying operational conditions. One approach to understanding confounding influences is to construct a data-based response surface model that can represent measurement variations as a function of environmental and operational variables. The models can then be used to remove environmental and operational variations so that change detection algorithms signal the occurrence of damage alone. The current chapter is concerned with such response surface models in the case of SHM of bridges. In particular, classes of response surface models that can switch discontinuously between regimes are discussed.

Suggested Citation

  • Keith Worden & Elizabeth J. Cross & James M. W. Brownjohn, 2013. "Switching Response Surface Models for Structural Health Monitoring of Bridges," Springer Books, in: Slawomir Koziel & Leifur Leifsson (ed.), Surrogate-Based Modeling and Optimization, edition 127, pages 337-358, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-7551-4_14
    DOI: 10.1007/978-1-4614-7551-4_14
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