Luong Ha Nguyen and James Alexandre Goulet
Article (2018)
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Open Access to the full text of this document Accepted Version Terms of Use: Creative Commons Attribution Non-commercial No Derivatives Download (683kB) |
Abstract
In Structural Health Monitoring, non-harmonic periodic hidden covariate typically arises when an observed structural response depends on unobserved external effects such as temperature or loading. This paper addresses this challenge by proposing a new extension to Bayesian Dynamic Linear Models (BDLMs) for handling situations where non-harmonic periodic hidden covariates may influence the observed responses of structures. The potential of the new approach is illustrated on the data recorded on a dam in Canada. A model employing the proposed approach is compared to another that only uses a superposition of harmonic hidden components available from the existing BDLMs. The comparative study shows that the proposed approach succeeds in estimating hidden covariates and has a better predictive performance than the existing method using a superposition of harmonic hidden components.
Uncontrolled Keywords
Subjects: |
1100 Structural engineering > 1100 Structural engineering 1100 Structural engineering > 1104 Structural analysis 2700 Information technology > 2717 Modelling and simulation studies |
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Department: | Department of Civil, Geological and Mining Engineering |
Funders: | CRSNG/NSERC |
Grant number: | RGPIN-2016-06405 |
PolyPublie URL: | https://publications.polymtl.ca/3021/ |
Journal Title: | Engineering Structures (vol. 166) |
Publisher: | Elsevier |
DOI: | 10.1016/j.engstruct.2018.03.080 |
Official URL: | https://doi.org/10.1016/j.engstruct.2018.03.080 |
Date Deposited: | 17 Apr 2018 15:29 |
Last Modified: | 07 Apr 2025 14:06 |
Cite in APA 7: | Nguyen, L. H., & Goulet, J. A. (2018). Structural health monitoring with dependence on non-harmonic periodic hidden covariates. Engineering Structures, 166, 187-194. https://doi.org/10.1016/j.engstruct.2018.03.080 |
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