Robust SHM Systems Using Bayesian Model Updating

Research output: Contribution to conferencesPaperContributedpeer-review

Contributors

Abstract

Structural Health Monitoring (SHM) is becoming increasingly important for monitoring infrastructures. However, one of the main challenges is that the changes due to aging are small, not only for structures, but also for SHM systems. Hence, the question is how should we distinguish such changes due to aging from measurement uncertainty. In this study, laser triangulation sensors (LTSs) are tested and the uncertainty due to temperature effects is studied. Furthermore, time-dependent experiments are performed and the SHM system is calibrated over time through Bayesian Model Updating, considering its temperature dependence.

Details

Original languageEnglish
Pages272-278
Number of pages7
Publication statusPublished - 19 Jun 2023
Peer-reviewedYes

Conference

Title33rd International Ocean and Polar Engineering Conference
Abbreviated titleISOPE 2023
Conference number33
Duration19 - 23 June 2023
Website
Degree of recognitionInternational event
LocationThe Westin
CityOttawa
CountryCanada

External IDs

ORCID /0000-0001-8735-1345/work/142244658
ORCID /0000-0003-4752-1519/work/142245450
Scopus 85188671326

Keywords