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 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Hille, Falk A1 - Said, Samir A1 - Baeßler, Matthias ED - Curbach, M. ED - Marx, S. ED - Scheerer, S. ED - Hampel, T. T1 - Structural Health Monitoring der Maintalbrücke Gemünden zur Unterstützung einer prädiktiven Instandhaltung N2 - 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. T2 - 11. Symposium Experimentelle Untersuchungen von Baukonstruktionen (SEUB) CY - Online meeting DA - 08.03.2021 KW - Structural Health Monitoring KW - Umwelteinflüsse KW - Prädiktive Instandhaltung PY - 2021 UR - https://tu-dresden.de/bu/bauingenieurwesen/imb/ressourcen/dateien/veranstaltungen/seub/11-seub-2021/2021_SEUB11_06_Herrmann_et_al.pdf?lang=de VL - 55 SP - 66 EP - 76 PB - Technische Universität Dresden CY - Dresden AN - OPUS4-52810 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias A1 - El-Athman, Rukeia T1 - Research Data Management of Structural Health Monitoring Projects and Subsequent Applications of Artificial Intelligence Methods N2 - Structural health monitoring (SHM) intends to improve the management of engineering structures. The number of successful SHM projects – especially SHM research projects – is ever growing, yielding added value and more scientific insight into the management of infrastructure asset. With the advent of the data age, the value of accessible data becomes increasingly evident. In SHM, many new data-centric methods are currently being developed at a high pace. A consequent application of research data management (RDM) concepts in SHM projects enables a systematic management of raw and processed data, and thus facilitates the development and application of artificial intelligence (AI) and machine learning (ML) methods to the SHM data. In this contribution, a case study based on an institutional RDM framework is presented. Data and metadata from monitoring the structural health of the Maintalbrücke Gemünden for a period of 16 months are managed with the RDM system BAM Data Store, which makes use of the openBIS data management software. An ML procedure is used to classify the data. Feature engineering, feature training and resulting data are performed and modelled in the RDM system. T2 - 11th International Conference on Bridge Maintenance, Safety and Management (IABMAS2022) CY - Barcelona, Spain DA - 11.07.2022 KW - Research data management KW - Structural health monitoring KW - Artificial intelligence PY - 2022 SN - 978-1-032-35623-5 SN - 978-1-003-32264-1 U6 - https://doi.org/10.1201/9781003322641-127 SP - 1061 EP - 1068 PB - CRC Press CY - Boca Raton AN - OPUS4-55493 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Gerards, Paul A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for data and structural integrity management for support structures in offshore wind farms based on building information modelling N2 - 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. T2 - 8th International Symposium on Reliability Engineering and Risk Management CY - Hannover, Germany DA - 04.09.2022 KW - Offshore wind energy KW - support structures KW - structural health monitoring KW - building information modelling KW - structural integrity management PY - 2022 U6 - https://doi.org/10.3850/978-981-18-5184-1_MS-04-161-cd SP - 111 EP - 117 PB - Research Publishing CY - Singapore AN - OPUS4-55656 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Wille, Frank T1 - Dynamisches Verhalten und Überwachung des Großen Fallturms der BAM in Horstwalde N2 - 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. N2 - Drop test towers are structures subjected to very specific dynamic loadings. At the drop test tower at the Test Site Technical Safety (TTS) of BAM routine inspections revealed a decline of structural integrity in form of loss of pretension in bolts of structural steel connections. To get an understanding about the underlying damage mechanisms as well as to assure the structural safety in operation, a multifaceted Structural Health Monitoring (SHM) system was planned and installed at the structure with the help of digital models. For planning the monitoring system but especially for supporting the investigation of the damaging process finite element models are deployed. Though, to ensure the capability of the FE model to reproduce the real structural behavior in sufficient accuracy, it needs to be calibrated in respect to measured responses of the structure. The present contribution describes experimental and numerical investigations to identify the structural system of the steel tube lattice tower in preparation of the monitoring campaign. An ambient vibration test allowed the identification of the natural frequencies of several global vibrational modes of the drop test tower. For model updating first a sensitivity analysis is applied to identify the most influencing parameter. In succession a genetic algorithm was applied for optimization in the sense of minimization of the difference between measured and simulated characteristic responses. The updated model is finally validated on the dynamic response of the tower structure to a real drop test induced impact loading. The results showed a good agreement between numerical and experimental results though the robustness of the simulation should be improved by more sophisticated numerical modelling. T2 - 7. VDI-Fachtagung Baudynamik CY - Würzburg, Germany DA - 27.04.2022 KW - Großer Fallturm Horstwalde KW - Structural Health Monitoring KW - Belastungsversuch KW - Modalanalyse KW - Schwingungsdynamik KW - Finite Elemente Simulation PY - 2022 SN - 978-3-18-092379-6 SN - 978-3-18-102379-2 U6 - https://doi.org/10.51202/9783181023792-265 SN - 0083-5560 VL - 2379 SP - 265 EP - 284 PB - VDI-Verlag CY - Düsseldorf AN - OPUS4-55472 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Nerger, Deborah A1 - Moosavi, Robabeh A1 - Grunwald, Marcel T1 - Discussion on data evaluation of tomographic and numerical results N2 - 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. T2 - 26th International Conference on Structural Mechanics in Reactor Technology CY - Potsdam, Germany DA - 10.07.2022 KW - Impact damage on reinforced concrete KW - Tomographic damage evaluation KW - Numerical damage simulation PY - 2022 SP - 1 EP - 8 AN - OPUS4-55474 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Nerger, Deborah A1 - Moosavi, Robabeh A1 - Grunwald, Marcel T1 - Discussion on data evaluation of tomographic and numerical results N2 - 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. T2 - 26th International Conference on Structural Mechanics in Reactor Technology CY - Potsdam, Germany DA - 10.07.2022 KW - Impact damage of reinforced concrete KW - Tomographic damage evaluation KW - Numerical simulation of impact damage PY - 2022 AN - OPUS4-55476 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Herrmann, Ralf A1 - Said, Samir A1 - Ziegler, Fred A1 - Baeßler, Matthias A1 - Wille, Frank A1 - Quercetti, Thomas A1 - Minack, Mathias A1 - Sterthaus, Jens T1 - Structural Health Monitoring am Großen Fallturm der BAM N2 - In diesem Beitrag wird die Structural Health Monitoring Kampagne am Großen Fallturm der BAM vorgestellt. T2 - Seminar "Zerstörungsfreie Prüfung" CY - Online meeting DA - 13.01.2022 KW - Belastungsversuch KW - Großer Fallturm Horstwalde KW - Schwingungsdynamik KW - Modalanalyse PY - 2022 AN - OPUS4-55478 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Mendler, A. A1 - Döhler, M. A1 - Hille, Falk T1 - Detecting changes in boundary conditions based on sensitivity-based statistical tests N2 - Structural health monitoring is a promising technology to automatically detect structural changes based on permanently installed sensors. Vibration-based methods that evaluate the global system response to ambient excitation are suited to diagnose changes in boundary conditions, i.e., changes in member prestress or imposed displacements. In this paper, these changes are evaluated based on sensitivity-based statistical tests, which are capable of detecting and localizing parametric structural changes. The main contribution is the analytical calculation of sensitivity vectors for changes in boundary conditions (i.e., changes in prestress or support conditions) based on stress stiffening, and the combination with a numerically efficient algorithm, i.e., Nelson’s method. One of the main advantages of the employed damage diagnosis algorithm is that, although it uses physical models for damage detection, it considers the uncertainty in the data-driven features, which enables a reliabilitybased approach to determine the probability of detection. Moreover, the algorithm can be trained and the probability of detecting future damages can be predicted based on data and a model from the undamaged structure, in an unsupervised learning mode, making it particularly relevant for unique structures, where no data from the damaged state is available. For proof of concept, a numerical case study is presented. The study assesses the loss of prestress in a two-span reinforced concrete beam and showcases suitable validation approaches for the sensitivity calculation. T2 - International Symposium on Non-Destructive Testing in Civil Engineering (NDT-CE 2022) CY - Zurich, Switzerland DA - 16.08.2022 KW - Nelson’s method KW - Global ambient vibrations KW - Asymptotic local approach KW - Sensitivity vectors KW - Probability of detection KW - Stress stiffening PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-566632 UR - https://www.ndt.net/?id=27311 SN - 1435-4934 VL - 27 IS - 9 SP - 1 EP - 13 PB - NDT.net CY - Kirchwald AN - OPUS4-56663 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Herrmann, Ralf A1 - Ziegler, Fred A1 - Said, Samir A1 - Baeßler, Matthias A1 - Wille, Frank A1 - Quercetti, Thomas A1 - Minack, Mathias A1 - Sterthaus, Jens T1 - Structural Health Monitoring am Großen Fallturm der BAM N2 - 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. T2 - Seminar "Zerstörungsfreie Prüfung" am Lehrstuhl für Zerstörungsfreie Prüfung ,Technische Universität München CY - Online meeting DA - 13.01.2022 KW - Structural Health Monitoring KW - Schadensüberwachung KW - Schwingungsmonitoring PY - 2022 AN - OPUS4-56667 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -