Robust SHM Systems Using Bayesian Model Updating
Research output: Contribution to conferences › Paper › Contributed › peer-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 language | English |
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Pages | 272-278 |
Number of pages | 7 |
Publication status | Published - 19 Jun 2023 |
Peer-reviewed | Yes |
Conference
Title | 33rd International Ocean and Polar Engineering Conference |
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Abbreviated title | ISOPE 2023 |
Conference number | 33 |
Duration | 19 - 23 June 2023 |
Website | |
Degree of recognition | International event |
Location | The Westin |
City | Ottawa |
Country | Canada |
External IDs
ORCID | /0000-0001-8735-1345/work/142244658 |
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ORCID | /0000-0003-4752-1519/work/142245450 |
Scopus | 85188671326 |