Dokument-ID Dokumenttyp Autoren/innen Persönliche Herausgeber/innen Haupttitel Abstract Auflage Verlagsort Verlag Herausgeber (Institution) Erscheinungsjahr Titel des übergeordneten Werkes Jahrgang/Band ISBN Veranstaltung Veranstaltungsort Beginndatum der Veranstaltung Enddatum der Veranstaltung Ausgabe/Heft Erste Seite Letzte Seite URN DOI Lizenz Datum der Freischaltung OPUS4-55774 Dissertation Viefhues, Eva Subspace-based damage detection in engineering structures considering reference uncertainties and temperature effects Automated vibration-based damage detection is of increasing interest for structural health monitoring of engineering structures. In this context, stochastic subspace-based damage detection (SSDD) compares measurements from a testing state to a data-driven reference model in a statistical framework. In this thesis theoretical developments have been proposed to improve the robustness of SSDD for realistic applications conditions. First, a statistical test has been proposed considering the statistical uncertainties about the model obtained from the reference data. This leads to a precise description of the test's distribution properties and damage detection thresholds. Second, an approach has been developed to account for environmental effects in SSDD. Based on reference measurements at few different environmental conditions, a test is derived with respect to an adequate interpolated reference. The proposed methods are validated in numerical simulations and applied to experimental data from the laboratory and outdoor structures. Universite de Rennes Universite de Rennes 2021 1 191 2022-09-21 OPUS4-52999 Beitrag zu einem Tagungsband Viefhues, Eva; Döhler, M.; Simon, Patrick; Herrmann, Ralf; Hille, Falk; Mevel, L. Cunha, A.; Caetano, E. Stochastic subspace-based damage detection of a temperature affected beam structure Structural health monitoring (SHM) of civil structures often is limited due to changing environmental conditions, as those changes affect the structural dynamical properties in a similar way like damages can do. In this article, an approach for damage detection under changing temperatures is presentedand applied to a beam structure. The used stochastic subspace-based algorithm relies on a reference null space estimate, which is confronted to data from the testing state in a residual function. For damage detection the residual is evaluated by means of statistical hypothesis tests. Changes of the system due to temperature effects are handled with a model interpolation approach from linear parameter varying system theory. From vibration data measured in the undamaged state at some few reference temperatures, a model of the dynamic system valid for the current testing temperature is interpolated. The reference null space and the covariance matrix for the hypothesis test is computed from this interpolated model. This approach has been developed recently and was validated in an academic test case on simulations of a mass-spring-damper. In this paper, the approach is validated experimentally on a beam structure under varying temperature conditions in a climate chamber. Compared to other approaches, the interpolation approach leads to significantly less false positive alarms in the reference state when the structure is exposed to different temperatures, while faults can still be detected reliably. 2021 Proceedings of the 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10 Online meeting 30.06.2021 1 6 2021-07-26 OPUS4-53000 Vortrag Viefhues, Eva Stochastic subspace-based damage detection of a temperature affected beam structure Structural health monitoring (SHM) of civil structures often is limited due to changing environmental conditions, as those changes affect the structural dynamical properties in a similar way like damages can do. In this article, an approach for damage detection under changing temperatures is presentedand applied to a beam structure. The used stochastic subspace-based algorithm relies on a reference null space estimate, which is confronted to data from the testing state in a residual function. For damage detection the residual is evaluated by means of statistical hypothesis tests. Changes of the system due to temperature effects are handled with a model interpolation approach from linear parameter varying system theory. From vibration data measured in the undamaged state at some few reference temperatures, a model of the dynamic system valid for the current testing temperature is interpolated. The reference null space and the covariance matrix for the hypothesis test is computed from this interpolated model. This approach has been developed recently and was validated in an academic test case on simulations of a mass-spring-damper. In this paper, the approach is validated experimentally on a beam structure under varying temperature conditions in a climate chamber. Compared to other approaches, the interpolation approach leads to significantly less false positive alarms in the reference state when the structure is exposed to different temperatures, while faults can still be detected reliably 2021 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10 Online meeting 30.06.2021 2021-07-26 OPUS4-57951 Vortrag Auersch, Lutz Damage detection by flexibility functions and quasi-static moving load tests The contribution shows measurement examples of cars, floors, foundations, railway tracks, a footbridge, and a railbridge. Vibrations may include modes and waves. Namely in soil-structure interaction, modes are damped, shifted and prevented so that alternatives for the modal analysis are necessary: The approximation of the whole spectrum (flexibility function) and of the whole train passage (moving-load response). 2023 Symposium Emerging Trends in Bridge Damage Detection, Localization and Quantification Luxembourg, Luxembourg 05.05.2023 05.05.2023 2023-07-20