TY - JOUR A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias T1 - Bestandteile Digitaler Zwillinge im Erhaltungsmanagement von Verkehrsbrücken T1 - Components of digital twins in the operation and maintenance management of traffic bridges N2 - Digitale Zwillinge werden zukünftig ein integraler Bestandteil des Erhaltungsmanagements von Verkehrsbrücken sein. In diesem Beitrag wird argumentiert, dass sie nicht nur als digitale Abbilder physikalischer Bauwerke verstanden werden sollten, sondern als eine umfassende digitale Methode, die durch die Integration von Datenerfassung, Erhaltungsmaßnahmen, Datenmanagement, Bauwerksbewertung und Entscheidungsunterstützung die Bauwerksüberwachung und ‐erhaltung verbessert. In diesem Zusammenhang wird betont, dass der Übergang von der reaktiven zur prädiktiven Erhaltung durch den Einsatz von Digitalen Zwillingen nur dann realisierbar ist, wenn neben den erforderlichen diagnostischen und prognostischen Zustandsanalysen auch Methoden zur Optimierung von Entscheidungen über Datenerfassung und Erhaltungsmaßnahmen implementiert werden. Zur Veranschaulichung der Diskussion werden in diesem Beitrag exemplarisch zwei Bestandteile eines Digitalen Zwillings für das Erhaltungsmanagement von Verkehrsbrücken am Beispiel einer Eisenbahnbrücke demonstriert. Dabei wird zum einen gezeigt, wie Monitoringdaten mittels eines Datenmanagementsystems strukturiert verwaltet und für angeknüpfte Analysen bereitgestellt werden. Zum anderen erfolgt im Rahmen einer bauwerksspezifischen Einwirkungsermittlung eine Zugidentifikation anhand von gemessenen Schwellenschwingungen. N2 - Digital twins will become an integral part of the operation and maintenance management of traffic bridges in the future. This paper argues that they should not only be understood as digital representations of physical structures but as a digital methodology that enhances the operation and maintenance of bridges through the integration of data collection, maintenance actions, data management, structural assessment, and decision support. In this context, it is emphasized that the transition from reactive to predictive maintenance using digital twins can only be achieved if, in addition to the necessary diagnostic and prognostic condition analyses, methods for optimizing decisions on data collection and maintenance actions are also implemented. To illustrate this discussion, two key components of a digital twin for the operation and maintenance management of traffic bridges are demonstrated using a railway bridge as an example. First, it is shown how monitoring data can be systematically managed and made available for subsequent analyses through a data management system. Second, train identification based on measured sleeper vibrations is conducted as part of an object-specific load assessment. KW - Digitale Zwillinge KW - Erhaltung KW - Inspektion KW - Monitoring KW - Brücken PY - 2025 DO - https://doi.org/10.1002/bate.202400101 SN - 1437-0999 SP - 1 EP - 11 PB - Ernst & Sohn CY - Berlin AN - OPUS4-62837 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Hille, Falk A1 - Herrmann, Ralf A1 - Baeßler, Matthias T1 - Vibration-based system identification of a large steel box girder bridge N2 - The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model. T2 - XII International Conference on Structural Dynamics (EURODYN 2023) CY - Delft, The Netherlands DA - 02.07.2023 KW - Verkehrsinfrastukturen KW - SHM KW - Model updating KW - System identification KW - Operational modal analysis PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-605041 DO - https://doi.org/10.1088/1742-6596/2647/18/182039 SN - 1742-6596 VL - 2647 IS - 18 SP - 1 EP - 9 PB - IOP Publishing CY - Bristol AN - OPUS4-60504 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Herrmann, Ralf A1 - Ramasetti, Eshwar Kumar A1 - Degener, Sebastian A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A living lab for Structural Health Monitoring at the Nibelungen Bridge Worms for Transfer Learning of Structural Dynamics N2 - The Nibelungen Bridge in Worms, Germany has been selected as a national demonstration structure for advanced non-destructive testing (NDT) and structural health monitoring concepts to extend the lifetime of civil structures and to optimize O&M actions. Parts of the research that involves this bridge as a demonstrator belong to the focus area program SPP100+. In this program, the bridges SHM System has been extended and combined with an additional setup of vibration sensors. The used digital smart sensor with pre-processing functions, the arrangement of the sensors at the structure and additional edge computing capability allows the investigation of transfer learning and other methods directly into the real structure. The living lab with seven triaxial accelerometers can be reconfigured in real-time and adjusted to the needs of AI models for classification. The comparison with the existing conventional SHM sensors has been made possible by hardware synchronization to the existing SHM System and collocating sensors at similar positions, so that a hardware exchange can be an investigated use-case for the transfer learning. During idle times, the system collects vibration data like a conventional SHM system. T2 - 10th European Workshop on Structural Health Monitoring (EWSHM 2024) CY - Potsdam DA - 10.06.2024 KW - Nibelungen Bridge KW - Living Lab KW - Transfer Learning KW - Transfer Structures KW - Modal Analysis PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-612810 UR - https://www.ndt.net/search/docs.php3?id=29853 DO - https://doi.org/10.58286/29853 SN - 1435-4934 VL - 29 IS - 7 SP - 1 EP - 8 PB - NDT.net GmbH & Co. KG CY - Mayen AN - OPUS4-61281 LA - eng 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 DO - 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 - Herrmann, Ralf A1 - Hille, Falk A1 - Said, Samir A1 - Sterthaus, Jens A1 - Müller, Karsten A1 - Quercetti, Thomas A1 - Wille, Frank A1 - Paffenholz, J.-A. A1 - Baeßler, Matthias ED - Papadrakakis, M. ED - Fragiadakis, M. ED - Papadimitriou, C. T1 - Implementing a Structural Health Monitoring system using digital models of the BAM large drop test facility in Horstwalde N2 - 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. T2 - XI International Conference on Structural Dynamics (EuroDyn 2020) CY - Online meeting DA - 23.11.2020 KW - Structural Health Monitoring KW - Drop Tests KW - System Identification KW - Digital Models KW - BIM PY - 2020 UR - https://generalconferencefiles.s3-eu-west-1.amazonaws.com/eurodyn_2020_ebook_procedings_vol1.pdf SN - 978-618-85072-0-3 VL - 1 SP - 1293 EP - 1304 PB - Institute of Structural Analysis and Antiseismic Research CY - Athen AN - OPUS4-51592 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Hille, Falk ED - Powers, N. ED - Frangopol, D. T1 - A study on diverse strategies for discriminating environmental from damage based variations in monitoring data N2 - 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. T2 - IABMAS CY - Melbourne, Australia DA - 09.07.2018 KW - SHM KW - Environmental changes KW - temperature PY - 2018 SN - 978-1-138-73045-8 SP - 1557 EP - 1564 PB - CRC Press AN - OPUS4-46059 LA - eng 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 DO - 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 DO - 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 - Hille, Falk A1 - Said, Samir ED - Baeßler, Matthias ED - Rogge, Andreas ED - Möller, Gerd ED - Schiefelbein, Norbert T1 - Bauwerksüberwachung von Brücken im Kontext saisonaler Einflüsse N2 - 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. T2 - Messen Im Bauwesen CY - BAM, Berlin, Germany DA - 08.11.2016 KW - Bauwerksüberwachung KW - SHM KW - Temperatureinfluss PY - 2016 SN - 978-3-9817853-6-4 VL - 2016 SP - 89 EP - 102 PB - Eigenverlag BAM AN - OPUS4-39354 LA - deu 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 - JOUR A1 - Eichner, Lukas A1 - Gerards-Wünsche, Paul A1 - Happel, Karina A1 - Weise, Sigurd A1 - Haake, Gerrit A1 - Sieber, Lars A1 - Flederer, Holger A1 - Schneider, Ronald A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Baeßler, Matthias A1 - Huhn, Holger A1 - Küchler, Andreas T1 - Digitales Datenmanagement für die Instandhaltung von Offshore-Windparks T1 - Digital data management for maintenance in offshore wind farms N2 - Im Forschungsprojekt DiMoWind-Inspect wurde untersucht, welche Grundvoraussetzungen geschaffen werden müssen, um digitale Methoden für die Instandhaltung von Offshore-Windenergieanlagen einsetzen zu können. Daten aus allen Lebensphasen der Anlagen werden derzeit nur selten effizient dafür genutzt, um die sinnvollsten Instandhaltungsmaßnahmen am richtigen Ort, zum richtigen Zeitpunkt und mit den geringsten Kosten durchzuführen. Eine im Vorhaben entwickelte einheitliche Strukturierung der bisher häufig unstrukturierten Bau- und Instandhaltungsdaten ermöglicht ihre übergreifende, anwenderspezifische Verfügbarkeit. Hierfür werden Prinzipien des Referenzkennzeichnungssystems RDS-PP adaptiert. Es wird aufgezeigt, wie neben Bauteilen auch zusätzliche Informationen wie Instandhaltungsmaßnahmen oder Mängel strukturiert werden können. Dem Ansatz des Building Information Modeling folgend werden die Bauwerkskomponenten direkt mit den Informationen aus Inspektionen und weiteren Instandhaltungsmaßnahmen verknüpft. So können Informationen aus dem Betrieb über den Zustand der Struktur verarbeitet und für die maßgebenden Berechnungen und Nachweise zur Verfügung gestellt werden. Als Anwendungsfall wird ein zweistufiges Konzept vorgestellt, das zur Bewertung der Ermüdungslebensdauer eines korrosionsgeschädigten Konstruktionsdetails der Gründungsstruktur einer Offshore-Windenergieanlage mit Informationen aus der Instandhaltung eingesetzt wird. N2 - The DiMoWind-Inspect research project explored the essential requirements for implementing digital methods in the maintenance of offshore wind turbines. Currently, data from all stages of the turbines' lifecycles are underutilized, leading to suboptimal maintenance actions being taken in terms of location, timing, and cost. A consistent structuring of previously often unstructured construction and maintenance data developed in the project enables their cross-disciplinary, user-specific availability. To accomplish this, the principles of the Reference Designation System for Power Plants RDS-PP are applied. In this way, additional information, such as maintenance measures or defects, can be structured alongside components. The components of the structures are directly linked with information from inspections and other maintenance activities, following the Building Information Modeling approach. This allows for processing operational information about the condition of the structure and providing it for relevant calculations and assessments. As a use case, a two-stage concept is presented, utilizing maintenance information to assess the fatigue life of a corrosion-damaged structural detail in the support structure of an offshore wind turbine. KW - Building Information Modeling KW - Datenmanagement KW - Instandhaltung KW - Offshore-Windenergie KW - Referenzkennzeichnungssystem PY - 2024 DO - https://doi.org/10.1002/bate.202400026 VL - 101 IS - 10 SP - 558 EP - 567 PB - Ernst & Sohn CY - Berlin AN - OPUS4-60765 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gerards-Wünsche, Paul A1 - Ratkovac, Mirjana A1 - Schneider, Ronald A1 - Hille, Falk A1 - Baeßler, Matthias T1 - A framework for assessing the reliability of crack luminescence – an automated fatigue crack detection system N2 - 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. T2 - SPIE Conference Smart Structures + Nondestructive Evaluation 2023 CY - Long Beach, CA, USA DA - 24.03.2023 KW - Structural Health Monitoring KW - Non-Destructive Evaluation KW - Probability of Detection KW - Reliability KW - Artificial Intelligence KW - Computer Vision KW - Crack Luminescence KW - Wind PY - 2023 SN - 978-1-5106-6086-1 DO - https://doi.org/10.1117/12.2658390 SP - 1 EP - 15 AN - OPUS4-57244 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Eichner, Lukas A1 - Thiele, Marc A1 - Hille, Falk A1 - Baeßler, Matthias T1 - Digitale Modellierungsprozesse in der wiederkehrenden Prüfung von Windenergieanlagen - DiMoWind-Inspect - Abschlusstreffen N2 - Dieses Dokument enthält die Präsentationsfolien des BAM-Teams beim Abschlusstreffen des Forschungsprojekts DiMoWind-Inspect. Es wurden die Arbeitspakete Datenmanagement, Referenzkennzeichnungssystem, Grundlagen der Schadensbewertung, Risikobasierte Inspektions- und Instandhaltungsplanung und Schadensdetektion mittels Risslumineszenz sowie eine abschließende Bewertung des Projekts vorgestellt. T2 - DiMoWind-Inspect - Abschlusstreffen CY - Berlin, Germany DA - 12.09.2024 KW - Building Information Modeling (BIM) KW - Referenzkennzeichnungssystem KW - Risslumineszenz (Riluminati) KW - Risikobasierte Inspektionsplanung (RBI) PY - 2024 AN - OPUS4-61054 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Ebell, Gino A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Schneider, Ronald ED - Lienhart, Werner ED - Krüger, Markus T1 - On potentials and challenges of physics-informed SHM for civil engineering structures N2 - Physics-informed structural health monitoring, which integrates realistic physical models of material behavior, structural response, damage mechanisms, and aging processes, offers a promising approach to improve monitoring capabilities and inform operation and maintenance planning. However, the associated technical challenges and model requirements are context-specific and vary widely across applications. To illustrate the relevance and potential of the topic, two application examples are presented. The first focuses on monitoring the modal characteristics of a prestressed road bridge, where strong sensitivity to temperature variations limits the diagnostic capabilities of conventional vibration-based global monitoring. The discussion highlights how environmental influences can obscure structural changes, and emphasizes that purely data-based approaches are inherently limited to detecting anomalies and do not enable comprehensive condition diagnostics. The second example explores a physics-informed monitoring approach for prestressed concrete bridges affected by hydrogen-induced stress corrosion cracking. T2 - SHMII-13 CY - Graz, Austria DA - 01.09.2025 KW - Hydrogen Stress Corrosion Cracking KW - SHM KW - Physics informed PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-643271 SN - 978-3-99161-057-1 DO - https://doi.org/10.3217/978-3-99161-057-1-039 SP - 245 EP - 251 PB - Verlag der Technischen Universität Graz CY - Graz, Austria AN - OPUS4-64327 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Schneider, Ronald A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Baeßler, Matthias ED - Döhler, Michael ED - Mélot, Adrien ED - Aenlle Lopez, Manuel T1 - System identification and model calibration of a steel road bridge N2 - The Bundesanstalt für Materialforschung und -prüfung (BAM), in cooperation with the Netherlands Organization for Applied Scientific Research (TNO), is working on a framework for integrating frequently updated structural models into an asset management process for bridge structures. A multi-span steel road bridge was selected as a test case for the development of this framework. In order for the structural model to represent the real behavior of the bridge with sufficient accuracy, model calibration is required. In this case, we have planned to calibrate the model based on the dynamic response of the bridge. To determine its dynamic properties, a multi-setup operational modal analysis was performed on one of the bridge spans. In parallel, a structural model of the span was developed based on the available design and service life information. Both eigenfrequencies and mode shapes were used as reference parameters to calibrate the model. A sensitivity analysis was performed to identify the most influential design parameters. Subsequently, a genetic algorithm was applied for minimizing the difference between measured and simulated characteristic responses. In the proposed paper, we summarize the measurements as well as the determination of the modal response of the bridge and describe the process of calibration of the structural model using the identified dynamic response. T2 - 11th International Operational Modal Analysis Conference (IOMAC 2025) CY - Rennes, France DA - 20.05.2025 KW - Bridge structure KW - Operational modal analysis KW - Model calibration PY - 2025 SN - 978-84-09-75120-4 SP - 114 EP - 121 PB - International Group of Operational Modal Analysis CY - Gijón, Spain AN - OPUS4-64416 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Baeßler, Matthias A1 - Bhuyan, Delwar A1 - Hille, Falk A1 - Viefhues, Eva A1 - Döhler, M. A1 - Mevel, L. ED - Zingoni, Alphose T1 - Impact of environmental based effects on SHM strategies N2 - 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. T2 - SEMC 2019 CY - Cape Town, South Africa DA - 02.09.2019 KW - SHM environmental bridges PY - 2019 SN - 978-1-138-38696-9 SN - 978-0-429-42650-6 DO - https://doi.org/10.1201/9780429426506 SP - Paper 324, 1 EP - Paper 324, 6 PB - CRC Press CY - Boca Raton AN - OPUS4-49167 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -