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Structural health monitoring with dependence on non-harmonic periodic hidden covariates

Luong Ha Nguyen and James Alexandre Goulet

Article (2018)

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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

Bayesian; Dynamic Linear Models; Hidden covariates; Structural Health Monitoring; Kalman filter; Dam

Subjects: 1100 Structural engineering > 1100 Structural engineering
1100 Structural engineering > 1104 Structural analysis
2700 Information technology > 2717 Modelling and simulation studies
Department: Department of Civil, Geological and Mining Engineering
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: 08 Jun 2023 15:52
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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