Bartels, JH, Potthast, T, Kitahara, M, Marx, S and Beer, M 
ORCID: 0000-0002-0611-0345
(2023)
Robust SHM Systems Using Bayesian Model Updating.
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2024-04-15_JB_Autorenmanuskript.pdf - Author Accepted Manuscript Download (588kB) | Preview |
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.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Divisions: | Faculty of Science and Engineering > School of Engineering |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 22 Apr 2024 07:41 |
| Last Modified: | 27 Apr 2024 09:26 |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3180470 |
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