TY - JOUR A1 - Viefhues, Eva A1 - Döhler, M. A1 - Hille, Falk A1 - Mevel, L. T1 - Statistical subspace-based damage detection with estimated reference N2 - The statistical subspace-based damage detection technique has shown promising theoretical and practical results for vibration-based structural health monitoring. It evaluates a subspacebased residual function with efficient hypothesis testing tools, and has the ability of detecting small changes in chosen system parameters. In the residual function, a Hankel matrix of Output covariances estimated from test data is confronted to its left null space associated to a reference model. The hypothesis test takes into account the covariance of the residual for decision making. Ideally, the reference model is assumed to be perfectly known without any uncertainty, which is not a realistic assumption. In practice, the left null space is usually estimated from a reference data set to avoid model errors in the residual computation. Then, the associated uncertainties may be non-negligible, in particular when the available reference data is of limited length. In this paper, it is investigated how the statistical distribution of the residual is affected when the reference null space is estimated. The asymptotic residual distribution is derived, where its refined covariance term considers also the uncertainty related to the reference null space estimate. The associated damage detection test closes a theoretical gap for real-world applications and leads to increased robustness of the method in practice. The importance of including the estimation uncertainty of the reference null space is shown in a numerical study and on experimental data of a progressively damaged steel frame. KW - Damage detection KW - Uncertainty quantification KW - Statistical tests KW - Ambient excitation KW - Vibration measurement PY - 2022 U6 - https://doi.org/10.1016/j.ymssp.2021.108241 SN - 0888-3270 VL - 164 SP - 108241 PB - Elsevier Ltd. AN - OPUS4-52998 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva A1 - Döhler, M. A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Mevel, L. ED - Cunha, A. ED - Caetano, E. T1 - Stochastic subspace-based damage detection of a temperature affected beam structure N2 - 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. T2 - 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10 CY - Online meeting DA - 30.06.2021 KW - Damage detection KW - Subspace methods KW - Temperature effects KW - Model interpolation KW - Climate chamber KW - Laboratory beam structure PY - 2021 SP - 1 EP - 6 AN - OPUS4-52999 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva A1 - Döhler, M. A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Mevel, L. T1 - Stochastic subspace-based damage detection of a temperature affected beam structure N2 - 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 T2 - 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10 CY - Online meeting DA - 30.06.2021 KW - Damage detection KW - Subspace methods KW - Temperature effects KW - Model interpolation KW - Climate chamber KW - Laboratory beam structure PY - 2021 AN - OPUS4-53000 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Viefhues, Eva T1 - Subspace-based damage detection in engineering structures considering reference uncertainties and temperature effects N2 - 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. KW - Damage detection KW - Subspace methods KW - Vibrations KW - Uncertainty quantification KW - Environmental effects KW - Civil structures PY - 2021 SP - 1 EP - 191 CY - Universite de Rennes AN - OPUS4-55774 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -