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Eingeladener Vortrag
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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.
Falltürme sind Bauwerke, die als Versuchsanlagen sehr speziellen, impulsartigen Belastungen ausgesetzt sind. Am Fallturm auf dem Testgelände Technische Sicherheit (TTS) der BAM wurde bei Routineinspektionen eine Abnahme der strukturellen Integrität in Form von Vorspannungsverlusten in den Bolzen der Stahlverbindungen festgestellt. Um ein Verständnis für die zugrundeliegenden Trag- und Schädigungsmechanismen zu erlangen, wurde ein umfassendes Structural Health Monitoring (SHM) System geplant und am Bauwerk installiert unter Nutzung von digitalen Bauwerksmodellen. Für die Auslegung des Überwachungssystems, insbesondere aber zur Unterstützung der Untersuchung des Schädigungsprozesses, wurden Finite-Elemente-Modelle erstellt. Um sicherzustellen, dass die FE-Modelle das reale Tragwerksverhalten mit ausreichender Genauigkeit abbilden, mussten sie jedoch in Bezug auf die gemessenen Antworten des Tragwerks kalibriert werden. Der vorliegende Beitrag beschreibt experimentelle und numerische Untersuchungen zur Identifizierung des strukturellen Systems des Stahlrohrgitterturms in Vorbereitung einer Überwachungskampagne. Die Auswertung von gemessenen Schwingungen unter ambienter Anregung ermöglichte die Identifizierung der Eigenfrequenzen mehrerer globaler Schwingungsmoden des Fallturms. Zur Modellvalidierung wurde zunächst eine Sensitivitätsanalyse durchgeführt, um die Parameter mit dem größten Einfluss zu ermitteln. Anschließend wurde ein evolutionärer Algorithmus (EA) zur Optimierung nach dem Prinzip der Minimierung der Differenzen zwischen gemessenen und simulierten charakteristischen Antworten eingesetzt. Das aktualisierte Modell wurde schließlich an der dynamischen Reaktion der Turmstruktur infolge einer realen Falltest-induzierten Stoßbelastung validiert. Die Ergebnisse zeigten eine gute Übereinstimmung zwischen numerischen und experimentellen Ergebnissen.
Right from the beginning of applying SHM to bridge structures it was obvious that environmental based perturbations on the measurement significantly influence the ability to identify structural damage.
Strategies are needed to classify such effects and consider them appropriately in SHM. 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 taking into account environmental as well as damage based changes of stiffness values.
With the back-ground of increasing affordability of sensing and computing technology, effort should be made to increase sensitivity, reliability and robustness of procedures, separating environmental from damage caused changes in SHM measures. The contribution describes both general strategies and points out their Advantages and drawbacks. As basis, a review on relevant methods was conducted. The aim of the study is to classify approaches for separating damage describing information from environmental based perturbations in dependency of the SHM objective. And such, it is intended to describe a best practice in designing concepts for Monitoring infrastructure, naturally effected by environmental influences.
Anhand verschiedener Bespiele wird diskutiert, wie Temperaturbeanspruchungen in einer Bauwerksüberwachung sichtbar werden und wie sie zu bewerten sind. Insbesondere der Einfluss auf die Zustandsbewertung im Sinne der Standsicherheit stellt häufig eine große Schwierigkeit dar. Behelfsweise besteht eine grundlegende Möglichkeit darin, ein Tragwerk immer zu seiner schwächsten Phase, d.h. in der Regel im Sommer zu beurteilen. Wie aufgezeigt, können zudem statistische Verfahren geeignet sein, Tragfähigkeitsänderungen zu detektieren.
Als wesentliche Zukunftsaufgaben werden verbesserte Detektionsalgorithmen und physikalisch begründete Modelle zum mechanischen Verhalten angesehen.
Die Akzeptanz schwingungsbasierter Verfahren zur Detektion und Lokalisierung von Schäden in der praktischen Anwendung ist alleinig von der Fähigkeit abhängig, Einflüsse aus veränderlichen Umwelt- und Betriebsbedingungen, insbesondere aber die aus der Temperatur zu eliminieren. Da die in den letzten Jahren immer wichtiger werdenden stochastischen Verfahren zur Schadensde-tektion und -lokalisierung die (statistische) Charakteristik der Messdaten bereits implizit nutzen, sind hier Entwicklung, Anpassung und Anwendung statistischer Algorithmen zur Eliminierung der variierenden Umwelteinflüsse naheliegend.
Auf der anderen Seite wird der saisonale Einfluss auf Bauwerksmessungen in sehr vielen Veröf-fentlichungen dargestellt und es werden häufig verdachtsweise begründete physikalische Zu-sammenhänge für das Verhalten aufgezeigt. Im Regelfall sind die Aussagen aber nicht experi-mentell überprüft und von eher allgemeiner Natur („Asphalt reagiert temperaturabhängig“). Ob-jektspezifische Zusammenhänge, beispielsweise über Versuch an Repräsentanten in der Klima-kammer ermittelt, könnten jedoch sehr hilfreich sein.
This paper deals with vibration-based damage localization and quantification from output-only measurements. We describe an approach which operates on a data-driven residual vector that is statistically evaluated using information from a finite element model, without updating the parameters of the model. First, the damaged elements are detected in statistical tests, and second, the damage is quantified only for the damaged elements. We propose a new residual vector in this context that is based on the transfer matrix difference between reference and damaged states, and compare it with a previously introduced subspace-based residual. We show localization and quantification on both residuals in simulations.
The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure.
The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure.
Damage detection and localization in civil or mechanical structures is a subject of active development and research. A few vibration‐based methods have been developed so far, requiring, for example, modal parameter estimates in the reference and damaged states of the investigated structure, and for localization in addition a finite element model. For structures in operation, temperature has been shown to be a major nuisance to the efficiency of such methods because the modal parameters are varying not only with damage but also due to temperature variations. For detection, a few rejection approaches have been developed. Besides the increased complexity, environmental variation is hardly taken into account in localization approaches. In this paper, we propose a sensitivity‐based correction of the identified modal parameters in the damaged state with respect to the temperature field in the reference state, on the basis of a sensitivity analysis with respect to temperature dependent Parameters of the finite element model in the reference state. The approach is then applied to the stochastic dynamic damage locating vector method, where its improved performance under nonuniform temperature variations is shown in a numerical application on a beam.
The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage localization method based on both a finite element model of a structure and modal parameters estimated
from output-only measurements in the damage and reference states. A statistical version of the Approach takes into account the inherent uncertainty due to noisy measurement data. In this paper, the effect of temperature fluctuations on the performance of the method is analyzed in a model-based approach using a finite element model with temperature dependent parameters. Robust damage localization is carried out by rejecting the temperature influence on the identified modal parameters in the damaged state. The algorithm is illustrated on a simulated structure.
The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage localization method based on both a finite element model of a structure and modal parameters estimated from output-only measurements in the damage and reference states. A statistical version of the Approach takes into account the inherent uncertainty due to noisy measurement data. In this paper, the effect of temperature fluctuations on the performance of the method is analyzed in a model-based approach using a finite element model with temperature dependent parameters. Robust damage localization is carried out by rejecting the temperature influence on the identified modal parameters in the damaged state. The algorithm is illustrated on a simulated structure.
In Operational Modal Analysis, the modal parameters (natural frequencies, damping ratios and mode shapes) obtained from Stochastic Subspace Identification (SSI) of a structure, are afflicted with statistical uncertainty. For evaluating the quality of the obtained results it is essential to know the respective confidence intervals of these figures. In this paper we present algorithms that automatically compute the confidence intervals of modal parameters obtained from covarianceand data-driven SSI of a structure based on vibration measurements. They are applied to the monitoring of the modal parameters of a prestressed concrete highway bridge during a progressive damage test that was accomplished within the European research project IRIS. Results of the covariance- and data-driven SSI are compared.
For the last decades vibration based identification of damage on civil Engineering structures has become an important issue for maintenance operations on transport infrastructure.
Research in that field has been rapidly expanding from classic modal Parameter estimation using measured excitation to modern operational monitoring. Here the difficulty is to regard to the specific environmental and operational influence to the structure under observation. In this paper, two methods accounting for statistical and/or operational uncertainties are applied to measurement data of a progressive damage test on a prestressed concrete bridge. On the base of covariance driven Stochastic Subspace Identification (SSI) an algorithm is developed to monitor and automatically compute confidence intervals of the obtained modal parameters. Furthermore, a null space based non-parametric damage detection method, utilizing a statistical χ2 type test is applied to the measurement data. It can be shown that for concrete bridges the proposed methodology is able to clearly indicate the presence of structural damage, if the damage leads to a change of the structural system.
Damage detection can be performed by detecting changes in the modal parameters between a reference state and the current (possibly damaged) state of a structure from measured output-only vibration data. Alternatively, a subspace-based damage detection test has been proposed and applied successfully, where changes in the modal parameters are detected, but the estimation of the modal parameters themselves is avoided. Like this, the test can run in an automated way directly on the vibration measurements. However, it was assumed that the unmeasured ambient excitation properties during measurements of the structure in the reference and possibly damaged condition stay constant, which is hardly satisfied by any application. A new version of the test has been derived recently that is robust to such changes in the ambient excitation. In this paper, the robust test is recalled and its performance is evaluated both on numerical simulations and a real application, where a steel frame structure is artificially damaged in the lab.
Structural health monitoring with statistical methods during progressive damage test of S101 Bridge
(2014)
For the last decades vibration based damage detection of engineering structures has become an important issue for maintenance operations on transport infrastructure. Research in vibration based structural damage detection has been rapidly expanding from classic modal parameter estimation to modern operational monitoring. Since structures are subject to unknown ambient excitation in operation conditions, all estimates from the finite data measurements are of statistical nature. The intrinsic uncertainty due to finite data length, colored noise, non-stationary excitations, model order reduction or other operational influences needs to be considered for robust and automated structural health monitoring methods. In this paper, two subspace-based methods are considered that take these statistical uncertainties into account, first modal parameter and their confidence interval estimation for a direct comparison of the structural states, and second a statistical null space based damage detection test that completely avoids the identification step. The performance of both methods is evaluated on a large scale progressive damage test of a prestressed concrete road bridge, the S101 Bridge in Austria. In an on-site test, ambient vibration data of the S101 Bridge was recorded while different damage scenarios were introduced on the bridge as a benchmark for damage identification. It is shown that the proposed damage detection methodology is able to clearly indicate the presence of structural damage, if the damage leads to a change of the structural system.
Automatic vibration-based structural health monitoring has been recognized as a useful alternative or addition to visual inspections or local non-destructive testing performed manually. It is, in particular, suitable for mechanical and aeronautical structures as well as on civil structures, including cultural heritage sites. The main challenge is to provide a robust damage diagnosis from the recorded vibration measurements, for which statistical signal processing methods are required. In this chapter, a damage detection method is presented that compares vibration measurements from the current system to a reference state in a hypothesis test, where data9
related uncertainties are taken into account. The computation of the test statistic on new measurements is straightforward and does not require a separate modal identification. The performance of the method is firstly shown on a steel frame structure in a laboratory experiment. Secondly, the application on real measurements on S101 Bridge is shown during a progressive damage test, where damage was successfully detected for different damage scenarios.
In the last ten years, monitoring the integrity of the civil infrastructure has been an active research topic, including in connected areas as automatic control. It is common practice to perform damage detection by detecting changes in the modal parameters between a reference state and the current (possibly damaged) state from measured vibration data. Subspace methods enjoy some popularity in structural engineering, where large model orders have to be considered. In the context of detecting changes in the structural properties and the modal parameters linked to them, a subspace-based fault detection residual has been recently proposed and applied successfully, where the estimation of the modal parameters in the possibly damaged state is avoided. However, most works assume that the unmeasured ambient excitation properties during measurements of the structure in the reference and possibly damaged condition stay constant, which is hardly satisfied by any application. This paper addresses the problem of robustness of such fault detection methods. It is explained why current algorithms from literature fail when the excitation covariance changes and how they can be modified. Then, an efficient and fast subspace-based damage detection test is derived that is robust to changes in the excitation covariance but also to numerical instabilities that can arise easily in the computations. Three numerical applications show the efficiency of the new approach to better detect and separate different levels of damage even using a relatively low sample length.
Fault detection and isolation can be handled by many different approaches. This paper builds upon a hypothesis test that checks whether the mean of a Gaussian random vector has become non-zero in the faulty state, based on a chi2 test. For fault isolation, it has to be decided which components in the parameter set of the Gaussian vector have changed, which is done by variants of the chi2 hypothesis test using the so-called sensitivity and minmax approaches. While only the sensitivity of the tested parameter component is taken into account in the sensitivity approach, the sensitivities of all parameters are used in the minmax approach, leading to better statistical properties at the expense of an increased computational burden. The computation of the respective test variable in the minmax test is cumbersome and may be ill-conditioned especially for large parameter sets, asking hence for a careful numerical evaluation. Furthermore, the fault isolation procedure requires the repetitive calculation of the test variable for each of the parameter components that are tested for a change, which may be a significant computational burden. In this paper, dealing with the minmax problem, we propose a new efficient computation for the test variables, which is based on a simultaneous QR decomposition for all parameters. Based on this scheme, we propose an efficient test computation for a large parameter set, leading to a decrease in the numerical complexity by one order of magnitude in the total number of parameters. Finally, we show how the minmax test is useful for structural damage localization, where an asymptotically Gaussian residual vector is computed from output-only vibration data of a mechanical or a civil structure.
Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders.
Schutzbauwerke von systemkritischen Infrastruktureinrichtungen wie Betonwände und Betonbarrieren müssen Anprallereignissen oder schweren Unfällen in einem vertretbaren Maße widerstehen können. Anprallereignisse können verschiedenster Natur sein. Hierzu zählen Steinschlag, Fahrzeug- oder Flugzeuganprall oder auch Geschosseinschlag. Geschosseinschläge bzw. Bei den Anprall- oder Impaktereignissen wird zwischen hartem und weichem Anprall unterschieden, bei hartem Anprall verformt sich der Anprallkörper nicht oder nur geringfügig, bei weichem Anprall stark.
In diesem Artikel werden Forschungsergebnisse zum harten Anprall auf bewehrte Stahlbetonplatten vorgestellt, welche über die letzten Jahre im Rahmen eines Kooperationsprojekts zwischen dem Institut für Massivbau (IMB) der Technischen Universität Dresden (TUD) und der Bundesanstalt für Materialforschung und -prüfung (BAM) durchgeführt wurden. Auf dem Gelände des Otto-Mohr-Labors (OML) der TUD steht hierfür ein speziell konzipierter Fallturm zur Verfügung. Der Aufbau im Fallturm lässt aktuell druckluftbeschleunigte Impaktversuche mit mittleren Anprallgeschwindigkeiten zu. Die durch Anprall geschädigten Stahlbetonplatten wurden anschließend bei der BAM mit Strahlung tomographisch untersucht. Diese Untersuchungen ermöglichen einen Blick auf die Schädigung und Rissstruktur im Inneren der Stahlbetonplatten.
Ein Schwerpunkt der durchgeführten Untersuchung ist der Vergleich von Testergebnissen mit den häufig angewendeten halbempirischen Berechnungsmethoden zu den erforderlichen Wandstärken und den sich daraus ergebenden zulässigen Anprallgeschwindigkeiten. Bei diesem Vorgehen wird auch die mit analytischen Methoden abschätzbare Durchdringungsgeschwindigkeit bzw. Austrittgeschwindigkeit eines Projektils ermittelt und mit den realen Testergebnissen verglichen. Außerdem wird der Einfluss von sowohl externen als auch internen Strukturparametern auf Risse betrachtet und ein Fazit abgeleitet. Weiterhin werden laufende und zukünftige wissenschaftliche Untersuchungen zum Anprall auf Betonstrukturen am IMB und der BAM genannt.
The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification. Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing.
The structural integrity of outer reinforced concrete (RC) containments of nuclear power plants provides an essential shield against external hazards. If this containment is damaged by an impact event, such as an aircraft crash, the question arises to which degree the reinforced concrete containment still has its protective capability. This concerns both purely structural protection and protection against liquids penetrating the interior of the containment. Due to the dimensions of the containment structures, it is difficult to perform real scale impact experiments, so in the past decades plate geometries at medium scale have been used for investigations. Detailed investigations on the structural behaviour of RC members or RC plates subjected to impact loading have already been presented in Just et al., Hering, Hering et al., Bracklow et al., Hille et al. and Nerger et al.
The following investigations deal with the single and multiple impact event (first hard impact and/or subsequent soft impact) on a RC specimen, which provides the basis for further investigations. A description of the test setup and the test procedure as well as a presentation of the test results from the impact tests are provided.
Furthermore, the experimental program is presented, which the damaged RC specimens are to undergo to deal with the question of how much the impact-damaged RC structure has become permeable to liquid media, such as water and kerosene, depending on the intensity of the impact. The aim of these following investigations is to develop a test setup that can be applied to investigate the liquid penetration behaviour (LPB) of small, medium, and large-scale RC members.
In addition to the liquid penetration experiments, the damaged specimens are to be examined by planar tomography to obtain the damage inside the specimen. The combination of damaging event, fluid penetration behaviour and tomography should enable a comprehensive understanding of the damage to the RC specimen.
At the Bundesanstalt für Materialforschung und -prüfung (BAM) full scale specimens for nuclear transport and storage containers (casks) are tested for their structural integrity in a series of drop tests on the Test Site Technical Safety in Horstwalde, 50 km south of Berlin. These drop tests cause a major stress not only on the casks, but also on the steel tower structure of the test facility, itself. The load pattern makes the structure very interesting for detailed investigation. The focus of the monitoring lies on the bolted joints of the flange connections that are a typical connection for cylindrical elements if welding is technical or economical unfavorable. The definition of the monitoring takes was done by investigating the existing documents and inspection results accompanied by building an initial digital representation of the structure, consisting of two finite element (FE) models and a geometrical 3D point cloud representation. As a first step the structures behavior during static and dynamic loading was analyzed using measurement data and an updated numerical FE Model. The idea behind is to use models for a digital planning and operation/evaluation of the structural health monitoring. A static FE simulation and a dynamic FE simulation are generated, to investigate how the structure behaves under the load conditions.
Nach den bisherigen Regeln werden Bauwerksprüfungen von Brücken in starr definierten Intervallen durchgeführt. Diese starre, periodische, zustandsbasierte Instandhaltungsstrategie soll zukünftig durch eine flexible und prädiktive Instandhaltung ersetzt werden. Hierbei sollen Inspektionen und Instandhaltungsmaßnahmen unterstützt durch autonome Systeme auf der Grundlage von Monitoringdaten geplant und zusätzlich bei unvorhergesehenen Ereignissen ausgelöst werden. Im Rahmen des Verbundforschungsvorhabens AISTEC wird ein Vorgehen für Großbauwerke und kleinere Regelbauwerke zur Umsetzung eines kombinierten globalen, schwingungsbasierten und quasistatischen Monitorings entworfen. An der Maintalbrücke Gemünden – einer semiintegralen Rahmenbrücke aus Spannbeton auf der Schnellfahrstrecke Hannover–Würzburg – wurde als Demonstrator ein Dauermonitoring realisiert.
Stochastische, subspace-basierte, kovarianz-gesteuerte output-only Identifikation von Schädigungen
(2008)
The contribution discusses the processing and analysis of data generated on two different ways of investigations for impact damage in reinforced concrete structures. Damage investigations are essential to determine type and characteristics of damage and thus the residual capacity. Damage describing data is generated using two different types of investigation, a non-destructive tomographic as well as numerical examination. Subsequently, data of both sources was merged and analysed. Within the research project “Behaviour of structural components during impact load conditions caused by aircraft fuel tank collision” reinforces concrete plates were damaged by impact loading, see Hering (2020). Afterwards the damaged specimens were investigated tomographically as well as numerically using several methods and models. Aim of the presented research work was to specify an objective comparability of numerical data with experimentally determined damage patterns and based on this, to establish a quantitative damage evaluation.
Am Fallturm auf dem Testgelände Technische Sicherheit (TTS) der BAM wurden bei Inspektionen Vorspannungsverluste in den Bolzen der Stahlverbindungen festgestellt. Um ein Verständnis für die zugrundeliegenden Trag- und Schädigungsmechanismen zu erlangen und um den Zustand der vorgespannten Schraubverbindungen langzeitlich zu überwachen, wurde am Fallturm ein Structural Health Monitoring (SHM) System installiert. Für die Auslegung des Monitoringsystems sowie zur Unterstützung der Untersuchung des Schädigungsprozesses wurde ein numerisches Modell erstellt und in Bezug auf die gemessenen Antworten des Tragwerks kalibriert.
Im Vortrag werden die experimentellen und numerischen Untersuchungen zur Systemidentifikation des Stahlrohrgitterturms als auch die Überwachungskampagne mit dem eingesetzten Monitoringsystem sowie die Messergebnisse und deren Bewertung vorgestellt.
Subspace-based detection of fatigue damage on jacket support structures of offshore wind turbines.
(2014)
Der Vortrag beschreibt einen im FB 7.2 der BAM entwickelten Algorithmus zur zuverlässigkeitsbasierten Bewertung von Offshore-Tragstrukturen durch eine gesamtlebensdauerbasierte Betrachtung auf Grundlage messtechnischer Überwachung. Ziel ist die Optimierung von Betrieb und Instandhaltung von Offshore-Windenergieanlagen (OWEA). Nach Einführung in die Zuverlässigkeit ermüdungsbeanspruchter Jacket-Strukturen sowie der Vorstellung der probalistischen Modellierung des Tragwerks und des Schadens wird die Aktualisierung der Zuverlässigkeit durch Informationen aus der Schadensdetektion erläutert. Am Beispiel einer 2D-Jacketstruktur wird exemplarisch die Vorgehensweise des Verfahrens aufgezeigt.
Im Rahmen der Präsentation werden die Aktivitäten des Fachbereichs 7.2 Ingenieurbau auf dem Gebiet der messtechnischen Überwachung von Bauwerken vorgestellt. Nach einer kurzen Vorstellung der BAM und deren Auftrag, der initiierten Themenfelder und der Abteilung 7 der BAM werden einige der im FB 7.2 durchgeführten Monitoringprojekte anhand von zugrundeliegenden Zielstellungen vorgestellt. Ausführlicher wird auf das Überwachungssystem der Westendbrücke sowie die geplanten Arbeiten am im Rahmen des Themenfelds Infrastruktur genehmigten Projekts BLEIB eingegangen.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
Unterraumbasierte Detektion von Strukturschäden an Jacket-Gründungen von Offshore-Windenergieanlagen
(2018)
Die vorliegende Arbeit beschreibt die Adaption eines globalen, schwingungsbasierten Verfahrens zur frühzeitigen Erkennung von Strukturschäden an Gründungsstrukturen offshore installierter Windenergieanlagen (OWEA). Damit soll es, Betreibern von Offshore-Windparks ermöglicht werden, im Rahmen periodisch durchgeführter messtechnischer Überwachungsmaßnahmen mit einem gegenüber wiederkehrender Inspektionen wesentlich geringen Aufwand auftretende Schäden an der Struktur zuverlässig zu delektieren.
Das untersuchte und implementierte Verfahren basiert auf der Methode der stochastischen unterraumbasierten Schadensdetektion. Dabei erfolgt eine statistische Analyse des wiederkehrend messtechnisch aufgenommenen dynamischen Antwortverhaltens des mechanischen Systems. Mittels statistischem Test werden signifikante Änderungen in dessen Eigenstruktur und damit Schäden delektiert.
Im Rahmen der vorliegenden Arbeit wurden umfangreiche experimentelle als auch numerische Untersuchungen zur Sensitivität und Robustheit des beschriebenen Schadensindikators durchgeführt. Dazu sind zunächst an einem Labormodell mittels künstlich und reversibel eingebrachter Schäden grundlegende Analysen zu den Einflüssen signal- und verfahrensinhärenter Kenngrößen durchgeführt worden. Auf der Basis dieser Ergebnisse wurde im Anschluss mittels numerischer Analysen das Antwortverhalten von OWEA simuliert und der entwickelte Algorithmus zur Schadensdetektion an den so realisierten Datensätzen angewendet.
Anhand der Ergebnisse der Arbeit wird aufgezeigt, dass, vorausgesetzt die Windenergieanlage befindet sich in Parkposition, eine Detektion von schon geringen Schäden an Gründungs-strukturen mit dem beschriebenen Verfahren, auch unter Einsatz weniger Messaufnehmer, zuverlässig möglich ist.
Unterraumbasierte Detektion von Strukturschäden an Jacket-Gründungen von Offshore-Windenergieanlagen
(2018)
Die vorliegende Arbeit beschreibt die Adaption eines globalen, schwingungsbasierten Verfahrens zur frühzeitigen Erkennung von Strukturschäden an Gründungsstrukturen offshore installierter Windenergieanlagen (OWEA). Damit soll es, Betreibern von Offshore-Windparks ermöglicht werden, im Rahmen periodisch durchgeführter messtechnischer Überwachungsmaßnahmen mit einem gegenüber wiederkehrender Inspektionen wesentlich geringen Aufwand auftretende Schäden an der Struktur zuverlässig zu delektieren.
Das untersuchte und implementierte Verfahren basiert auf der Methode der stochastischen unterraumbasierten Schadensdetektion. Dabei erfolgt eine statistische Analyse des wiederkehrend messtechnisch aufgenommenen dynamischen Antwortverhaltens des mechanischen Systems. Mittels statistischem Test werden signifikante Änderungen in dessen Eigenstruktur und damit Schäden delektiert.
Im Rahmen der vorliegenden Arbeit wurden umfangreiche experimentelle als auch numerische Untersuchungen zur Sensitivität und Robustheit des beschriebenen Schadensindikators durchgeführt. Dazu sind zunächst an einem Labormodell mittels künstlich und reversibel eingebrachter Schäden grundlegende Analysen zu den Einflüssen signal- und verfahrensinhärenter Kenngrößen durchgeführt worden. Auf der Basis dieser Ergebnisse wurde im Anschluss mittels numerischer Analysen das Antwortverhalten von OWEA simuliert und der entwickelte Algorithmus zur Schadensdetektion an den so realisierten Datensätzen angewendet.
Anhand der Ergebnisse der Arbeit wird aufgezeigt, dass, vorausgesetzt die Windenergieanlage befindet sich in Parkposition, eine Detektion von schon geringen Schäden an Gründungs-strukturen mit dem beschriebenen Verfahren, auch unter Einsatz weniger Messaufnehmer, zuverlässig möglich ist.
Risslumineszenz
(2018)
For the last decades vibration based damage detection of engineering structures has become an important issue for maintenance operations on transport infrastructure. Research in vibration based structural damage detection has been rapidly expanding from classic modal parameter estimation to modern operational monitoring. Methodologies from control Engineering especially of aerospace applications have been adopted and converted for the application on civil structures. Here the difficulty is to regard to the specific environmental and operational influence to the structure under observation. A null space based damage detection algorithm is tested for its sensitivity to structural damage of a prestressed concrete road bridge. Specific techniques and extensions of the algorithm are used to overcome difficulties from the size of the structure which is associated with the number of recorded sensor channels as well as from the operational disturbances by a nearby construction site. It can be shown that for concrete bridges the proposed damage detection methodology is able to clearly indicate the presence of structural damage, if the damage leads to a significant change of the structural system. Small damage which do not result in a System change when not activated by loading, do not lead to a modification of the dynamic response behavior and for that cannot be detected with the proposed global monitoring method.
The contribution discusses the processing and analysis of data generated on two different ways of investigations for impact damage in reinforced concrete structures. Damage investigations are essential to determine type and characteristics of damage and thus the residual capacity. Damage describing data is generated using two different types of investigation, a non-destructive tomographic as well as numerical examination. Subsequently, data of both sources was merged and analysed. Within the research project “Behaviour of structural components during impact load conditions caused by aircraft fuel tank collision” reinforces concrete plates were damaged by impact loading, see Hering (2020). Afterwards the damaged specimens were investigated tomographically as well as numerically using several methods and models. Aim of the presented research work was to specify an objective comparability of numerical data with experimentally determined damage patterns and based on this, to establish a quantitative damage evaluation.
Mit dem generellen Ziel, die Anwendbarkeit und Funktionalität des Verfahrens der stochastischen subspace-basierten Schadensdetektion für Strukturen von Offshore-Windenergieanlagen nachzuweisen, wurden experimentelle und numerische Untersuchungen an einer Laborstruktur sowie anschließend numerische Untersuchungen an einer OWEA-Gründungsstruktur durchgeführt.
Das zugrundeliegende Verfahren verwendet einen Ansatz, in weder modale Kenngrößen noch andere benutzerdefinierte Eingaben erfordert, nachdem einmalig der Referenzzustand aufgenommen wurde. Dabei werden ausschließlich dem Belastungsprozess inhärente stochastische Anregungen der betrachteten Struktur genutzt.
Auf der Basis experimentell erzielter Detektionsergebnisse aus einem Ermüdungsversuch an einer Laborstruktur aus Stahl wurden numerische Modelle und Berechnungsalgorithmen entwickelt und getestet. In einem zweiten Schritt wird diese Analysemethodik auf eine fiktive OWEA-Jacketstruktur realer Größe angewendet. An den simulierten Strukturantworten im Ungeschädigten und geschädigten Zustand wird der Detektionsalgorithmus angewendet, um den Einfluss von Sensorposition und Abtastrate auf die Schadensdetektion festzustellen. Unter Berücksichtigung einzelner vereinfachender Annahmen zeigten die Ergebnisse der Anwendung der vorgestellten Detektionsmethodik an den numerisch erzeugte Antwortdatensätzen eine beachtliche Empfindlichkeit des x2-Testwert basierten Schadensindikators. Obwohl nicht unter allen Umständen in einem frühen Stadium nachweisbar, typische Ermüdungsrisse in Schweißverbindungen von aufgelösten Tragwerken haben ab einer Restbiegesteifigkeit von ca. 80% einen signifikanten und detektierbaren Einfluss auf den Schadensindikator.
Künftige Forschungsaktivitäten in diesem Bereich sollten neben der Erkennung von Schäden auch die Lokalisierung und ggf. auch die Quantifizierung zum Ziel haben. Erforderlich dazu ist die Berücksichtigung und Verarbeitung der strukturellen Parameter und ihrer Sensitivitäten im zugrunde liegenden mathematischen Modell.
Altematively to common modal analysis as tool for detectmg changes between a reference and an actual (possibly damaged) structural state, the subspace-based damage detection method has been developed in recent years and successfully adopted to test application data sets. Characteristic for that method is that instead of analyzing modal parameters, a Statistical test with respect to changes of a dynamic signature of structural response is introduced. Therefor, a Gaussian residual vector is extracted from the subspace of an output only Vibration data covariance matrix within the reference state. The paper describes the application of this damage detection method within a laboratory fatigue test on a Steel frame structure. Aim of the investigation was to analyze the usability and efficiency of the detection method for realistic damage on carrying structures of wind energy turbines. In a second Step, a numerical model of the lab test structure is developed and validated. Thus, a comparable numerical Simulation of the fatigue damage detection was feasible and the accuracy of the Simulation procedure could be verified. The present study describes the first Step in a two-step approach for quantifying and optimizing fundamental characteristics of SHM Systems for offshore wind turbine structures concerning a required number of sensors and their optimal location.
Subspace-based detection of fatigue damage on jacket support structures of offshore wind turbines
(2014)
The paper describes the application of the Stochastic Subspace-based Damage Detection (SSDD) method on model structures for an utilization of this approach on offshore wind turbine structures. Aim of the study was therefore to analyze the usability and efficiency of the detection method as well as to determine an optimized set of parameter for realistic damage on support structures of wind energy turbines. Based on results of an experimental fatigue test on a Steel frame laboratory structure a strategy for a numerical verification of the experimentally evolved damage detection was developed, utilizing a time integration approach to simulate the dynamic response. In a second Step the identified modeling and computing methodology is used to numerically investigate the ability to detect damage in real size structural components of offshore wind turbines.