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Merging sensor data from multiple temperature scenarios for vibration monitoring of civil structures

Etienne Balmès 1 Michèle Basseville 2 Laurent Mevel 2 Houssein Nasser 2 Frédéric Bourquin 3 Fabien Treyssède 3
1 MSSMat - Laboratoire de mécanique des sols, structures et matériaux
2 SISTHEM - Statistical Inference for STructural HEalth Monitoring
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
3 LCPC - Laboratoire Central des Ponts et Chaussées
Abstract : The ambient temperature effect may result in limitations of vibration-based structural health monitoring (SHM) approaches for civil engineering structures. This paper addresses the issue of discriminating changes in modal parameters due to damages and changes in modal parameters due to temperature effects. A non parametric damage detection algorithm is proposed, which only assumes that several datasets are recorded on the safe structure at different and unknown temperatures, and smoothes out the temperature effect using an averaging operation.
Keywords : Subspace identification damage detection sensor data fusion vibration-based monitoring civil engineering structures temperature effect
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https://hal.inria.fr/inria-00164852
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Submitted on : Tuesday, July 24, 2007 - 10:12:59 AM
Last modification on : Friday, February 4, 2022 - 3:21:05 AM
Long-term archiving on: : Thursday, April 8, 2010 - 11:53:00 PM

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  • HAL Id : inria-00164852, version 1

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CNRS | INRIA | UNIV-RENNES1 | IRISA | IFSTTAR | LARA | MSSMAT | UR1-MATH-STIC | UR1-UFR-ISTIC | UNIV-RENNES | INSA-GROUPE | INSA-RENNES | UR1-MATH-NUM | EC-PARIS | LMPS | INRIA2

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Etienne Balmès, Michèle Basseville, Laurent Mevel, Houssein Nasser, Frédéric Bourquin, et al.. Merging sensor data from multiple temperature scenarios for vibration monitoring of civil structures. [Research Report] PI 1824, 2006. ⟨inria-00164852⟩

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