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Monitoring Structural Health Using a Probabilistic Measure

Beck, James L. and Au, Siu-Kui and Vanik, Michael W. (2001) Monitoring Structural Health Using a Probabilistic Measure. Computer-Aided Civil and Infrastructure Engineering, 16 (1). pp. 1-11. ISSN 1093-9687. doi:10.1111/0885-9507.00209.

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A Bayesian probabilistic methodology for structural health monitoring is presented. The method uses a sequence of identified modal parameter data sets to continually compute the probability of damage. In this approach, a high likelihood of a reduction in model stiffness at a location is taken as a proxy for damage at the corresponding structural location. The concept extends the idea of using as indicators of damage the changes in model parameters identified using a linear finite-element model and modal parameter data sets from the structure in undamaged and possibly damaged states. This extension is needed because of uncertainties in the updated model parameters that in practice obscure health assessment. These uncertainties arise due to effects such as variation in the identified modal parameters in the absence of damage, as well as unavoidable model error. The method is illustrated by simulating on-line monitoring, wherein specified modal parameters are identified on a regular basis and the probability of damage for each substructure is continually updated. Examples are given for abrupt onset of damage and progressive deterioration.

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Additional Information:© 2001 Computer-Aided Civil and Infrastructure Engineering. Published by Blackwell Publishers.
Issue or Number:1
Record Number:CaltechAUTHORS:20120829-133858966
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:33670
Deposited By: Carmen Nemer-Sirois
Deposited On:29 Aug 2012 21:14
Last Modified:09 Nov 2021 21:36

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