TY - CONF A1 - Herrmann, Ralf T1 - SHM system integration and experiments at a high speed railway bridge N2 - The long-term preservation of our infrastructure requires not only intelligent sensor technology and highly developed monitoring procedures, but also innovative digital tools for analyzing, evaluating and utilizing the results. This includes mathematical and, in particular, probabilistic methods for damage detection and tracking as well as for calculating service life and maintenance cycles and data management. The example project Maintal Bridge Gemuenden as part of the AISTEC project shows the workflow for the implementation of structural health monitoring and experimental tests with a train of Deutsche Bahn. The influence lines, as one possible way for damage detection, were measured with a highly accurate GNSS System to locate the trains position when crossing the bridge. The results were compared to measurements from 1987 just before the bridge went in operation. T2 - Structural Health Monitoring Using Statistical Pattern Recognition CY - Berlin, Germany DA - 20.03.2023 KW - SHM KW - Maintal Bridge Gemuenden KW - Load Test KW - Damage Detection KW - Railway PY - 2023 AN - OPUS4-57242 LA - eng 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 - Baeßler, Matthias T1 - On potentials and challenges of physics-informed SHM for civil engineering structures N2 - Physics-informed structural health monitoring, which incorporates realistic physical models of material behavior, structural response, damage mechanisms, and aging processes, offers a promising framework to enhance monitoring capabilities and inform operation and maintenance planning. Nevertheless, the technical challenges and model requirements associated with this approach are highly context-dependent and can vary significantly across different applications. The presentation focusses on two case studies that highlight challenges and progress in Physics informed SHM. T2 - SHMII-13 CY - Graz, Austria DA - 01.09.2025 KW - SHM KW - Physics informed KW - Hydrogen Stress Corrosion Cracking PY - 2025 AN - OPUS4-64326 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Herrmann, Ralf A1 - Ramasetti, Eshwar Kumar A1 - Ponnam, Poojitha A1 - Degener, Sebastian ED - Briffaut, Matthieu ED - Torrenti, Jean Michel T1 - Characterization of Smart Acceleration Sensors for Traffic Recognition using AI at the Nibelungen Bridge Worms N2 - The integration of digital sensors into Structural Health Monitoring (SHM) systems presents both significant opportunities and challenges, particularly in terms of sensor data management, bandwidth optimization, and system performance enhancement. This study examines the use of smart digital acceleration sensors, specifically MEMS accelerometers with CAN bus interfaces, deployed on the Nibelungen Bridge in Worms, Germany. The research evaluates the sensors' performance and calibration through laboratory and in-situ measurements, focusing on traffic load detection for vehicle recognition using Artificial Intelligence (AI) techniques. Additionally, the potential of AI, particularly autoencoders, in mitigating measurement uncertainties for traffic load detection is explored. T2 - 2025 fib International Symposium CY - Antibes, France DA - 16.06.2025 KW - SHM KW - Transfer Learning KW - SPP100+ KW - Nibelungen Bridge KW - Calibration KW - MEMS PY - 2025 UR - https://shop.fib-international.org/publications/fib-proceedings/1046-21th-fib-Symposium-Proceedings-in-Antibes-2025-France SN - 978-2-940643-29-5 SN - 2617-4820 SP - 3207 EP - 3816 CY - Antibes AN - OPUS4-64848 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kang, Chongjie A1 - Herrmann, Ralf A1 - Eisermann, Cedric A1 - Marx, Steffen ED - Chang, Fu-Kuo ED - Guemes, Alfredo T1 - Collaborative Structural Health Monitoring for Bridge Digital Twins N2 - Structural Health Monitoring (SHM) is an effective tool that not only reduces reliance on periodic inspections but also enhances them by analyzing the current state of a structure based on the latest structural data. Collaborative SHM, which integrates various SHM systems within the scope of bridge digital twins (BDTs), enhances infrastructure resilience and maintenance strategies. However, it faces challenges in integrating distributed sensor networks and requires interdisciplinary collaboration. In this work, various aspects of enhancing collaborative SHM with BDTs are presented. As a pilot project, the Nibelungen Bridge in Worms (NBW), Germany, is introduced. Based on specific stakeholder and project requirements, various SHM systems havebeen installed on this bridge. To address these challenges, goal-oriented solutions have been developed and elaborated. Finally, conclusions and future outlooks are presented. T2 - 15th International Workshop on Structural Health Monitoring CY - Stanford, CA, USA DA - 09.09.2025 KW - SHM KW - Collaborative Sensing KW - Nibelungen Bridge KW - SPP100+ PY - 2025 SN - 978-1-60595-699-2 DO - https://doi.org/10.12783/shm2025/37546 SP - 2305 EP - 2312 PB - DEStech Publications CY - Lancaster, PA, USA AN - OPUS4-64851 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -