1. Operational modal analysis with uncertainty quantification for SDDLV-based damage localization
- Author
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Dionisio Bernal, Michael Döhler, Laurent Mevel, Luciano Marin, Statistical Inference for Structural Health Monitoring (I4S), Département Composants et Systèmes (IFSTTAR/COSYS), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon-PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Lille Nord de France-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon-PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Lille Nord de France-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Northeastern University [Boston]
- Subjects
Engineering ,business.industry ,[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS] ,Structural engineering ,Transfer matrix ,Finite element method ,Vibration ,Stress (mechanics) ,Stress field ,[SPI.GCIV]Engineering Sciences [physics]/Civil Engineering ,Operational Modal Analysis ,Modal ,lcsh:TA1-2040 ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,Uncertainty quantification ,lcsh:Engineering (General). Civil engineering (General) ,business ,Algorithm - Abstract
International audience; The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage localization method based on a finite element model of a structure in a reference state and output-only measurements in both reference and damaged states. A stress field is computed for loads in the null space of a surrogate of the change in the transfer matrix at the sensor positions, where the null space is obtained based on the identified modal parameters in both structural states. Then, the damage location is related to positions where the stress is close to zero. The localization results of this generic approach are perturbed by mainly two sources: modal truncation (not all modes of the structure are available) and modal parameter identification errors (estimation is subject to statistical uncertainties). In this paper, we show how damage localization with the SDDLV approach is improved by taking into account the estimation uncertainties of the underlying identified modal parameters.
- Published
- 2015