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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.
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.
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
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.
Energiedissipierende Fassadenverankerung mit Crashmaterial für explosionsbeanspruchte Gebäude
(2014)
Wenn repräsentative Bauwerke wie Botschaften und Flughäfen außergewöhnlichen Lasten aus Explosion ausgesetzt sind, dann kann das Ausmaß des zu erwartenden Schadens aus einer solchen Belastung durch den Einsatz von energiedissipierenden Schutzbauteilen in der Fassadenverankerung begrenzt werden. Bisher ist über das Tragverhalten solcher Schutzbauteile wenig bekannt. In diesem Aufsatz werden Konstruktion und Wirkungsweise einer Verankerung für vorgehängte Fassaden vorgestellt, die in der Lage sind, einen Teil der Stoßenergie über Verformung eines Crashmaterials zu dissipieren. Versuche an einer bauteilähnlichen Konstruktion liefern Informationen über das Tragverhalten der Fassadenverankerung, insbesondere bei dynamischen Belastungen. Aus den Ergebnissen wird ein Konzept für die Vordimensionierung der vorgestellten Schutzbauteile abgeleitet.-----------------------------------------------------------------------------------------------------------------------------------------------------------
In the past few years public awareness of the need to protect structures against blast effects has risen. Blast wave energy is transmitted to the supporting structure by its façade connectors. Energy dissipating protective components placed at the connectors allow protecting people in the building as well as the primary building structure from damage. In this paper we present a protective component that dissipates blast energy by crash material. The report explores the system's fundamentals of operation from an experimental point of view. The results of dynamic tests are the basis of a design concept for the protective components.
Die Forderung, für repräsentative Bauwerke wie Botschaften und Flughäfen auch außergewöhnliche Lasten aus Explosion zu berücksichtigen, wurde in jüngerer Vergangenheit zunehmend gestellt. Das aufgrund dieser Lasten zu erwartende Schadensausmaß kann durch den Einsatz von energiedissipierenden Schutzbauteilen in der Fassadenbefestigung begrenzt werden. Die Dissipation der Explosionsenergie in den Schutzbauteilen kann beispielsweise über ein Crashmaterial erfolgen. In diesem Aufsatz werden Untersuchungen an zementgebundenen Materialien, die diesem Zweck dienen sollen, vorgestellt. Der Einfluss unterschiedlicher Zusätze auf die für ein Crashmaterial maßgebenden Eigenschaften wird in einer Parameterstudie untersucht. Als besonders geeignet wird ein Material identifiziert, bei dem die Zugabe eines Gasbildners das Matrixgefüge im Hinblick auf das gewünschte Kraft-Verformungs-Verhalten positiv verändert. Dynamische Versuche mit diesem Material geben Aufschluss über dessen Komprimierungsverhalten bei hohen Stauchraten.-----------------------------------------------------------------------------------------------------------------------------------------------
In the past few years public awareness of the need to protect structures against blast effects has risen. Energy dissipating protective components placed at the façade connectors allow protecting people in the building as well as the primary building structure from damage due to blast loads. One possibility to dissipate the blast energy is using protective components with crash material. This paper presents tests on cementitious crash materials studying the effect of different additives to the compression-behavior of the material. Additional experiments enable analyzing the material behavior under static and dynamic test conditions.
Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM) approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a general reference model is obtained from data in the reference state at several known reference temperatures. Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches.
Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM) approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a General reference model is obtained from data in the reference state at several known reference temperatures.
Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space Matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches.
Subspace-based damage detection handling temperature effects and uncertainty in the reference
(2019)
Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM)approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a general reference model is obtained from data in the reference state at several known reference temperatures. Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches.
Environmental based perturbations influence significantly the ability to identify structural dam-age in Structural Health Monitoring. Strategies are needed to classify such effects and consider them appropri-ately in SHM. It has to be considered if seasonal effects just mask the structural response or if temperature itself correlates to a weakening of the structure. Various methods have been developed and analyzed to separate environmental based effects from damage induced changes in the measures. Generally, two main approaches have emerged from research activity in this fields: (a) statistics-based tools analyzing patterns in the data or in computed parameters and (b) methods, utilizing the structural model of the bridge considering environmental as well as damage-based changes of stiffness values. With the background of increasing affordability of sensing and computing technology, effort should be made to increase sensitivity, reliability and robustness of proce-dures, separating environmental from damage caused changes in SHM measures. The contribution describes an attempt to evaluate both general strategies, their advantages and drawbacks. In addition, two vibration moni-toring procedures are introduced, allowing for temperature-based perturbations of the monitoring data.