TY - JOUR A1 - Simon, Patrick A1 - Helmrich, M. A1 - Herrmann, Ralf A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Lorelli, S. A1 - Morgenthal, G. T1 - Maintalbrücke Gemünden: Bauwerksmonitoring und -identifikation aus einem Guss T1 - Maintalbrücke Gemünden – Integrated structural health monitoring and UAS diagnostics N2 - Die Infrastruktursysteme der Industriestaaten erfordern heute und in Zukunft ein effizientes Management bei alternder Bausubstanz, steigenden Lasten und gleichbleibend hohem Sicherheitsniveau. Digitale Technologien bieten ein großes Potenzial zur Bewältigung der aktuellen und künftigen Herausforderungen im Infrastrukturmanagement. Im BMBF-geförderten Projekt Bewertung alternder Infrastrukturbauwerke mit digitalen Technologien (AISTEC) wird untersucht, wie unterschiedliche Technologien und deren Verknüpfung gewinnbringend eingesetzt werden können. Am Beispiel der Maintalbrücke Gemünden werden ein sensorbasiertes Bauwerksmonitoring, bildbasierte Inspektion mit durch Kameras ausgestatteten Drohnen (UAS) und die Verknüpfung digitaler Bauwerksmodelle umgesetzt. Die aufgenommenen Bilder dienen u. a. als Grundlage für spätere visuelle Anomaliedetektionen und eine 3D-Rekonstruktion, welche wiederum für die Kalibrierung und Aktualisierung digitaler Tragwerksmodelle genutzt werden. Kontinuierlich erfasste Sensordaten werden ebenfalls zur Kalibrierung und Aktualisierung der Tragwerksmodelle herangezogen. Diese Modelle werden als Grundlage für Anomaliedetektionen und perspektivisch zur Umsetzung von Konzepten der prädiktiven Instandhaltung verwendet. Belastungsfahrten und historische Daten dienen in diesem Beitrag der Validierung von kalibrierten Tragwerksmodellen. N2 - Infrastructure systems of industrialised countries today and in the future require efficient management with an ageing stock, increasing loads while simultaneously maintaining a high level of safety. Digital technologies offer great potential for the current and future challenges in infrastructure management. The BMBF-funded project AISTEC is investigating how the individual technologies and their interconnection can be used beneficially. With the Maintalbrücke in Gemünden as an exemplary application, sensor-based structural monitoring, image-based inspection using unmanned aircraft systems (UAS) equipped with cameras and the integration of digital structural models are being implemented. The recorded images serve, among others, as basis for subsequent anomaly detection and a 3D reconstruction, which in turn are used for updating digital structural models. Continuously recorded sensor data is used to update the parameters of the structural models, which in turn provide the basis for predictive maintenance. Load tests are used to validate the models. KW - Bauwerksüberwachung KW - Strukturmonitoring KW - Structural Health Monitoring KW - Modell-Update KW - UAS KW - Belastungstest KW - Structural system identification KW - Structural health monitoring KW - Model update KW - UAS KW - Load tests PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-554924 DO - https://doi.org/10.1002/bate.202100102 SN - 0932-8351 VL - 99 IS - 3 SP - 163 EP - 172 PB - Ernst & Sohn CY - Berlin AN - OPUS4-55492 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Farhan, Muhammad A1 - Schneider, Ronald A1 - Thöns, Sebastian A1 - Gündel, M. T1 - Probabilistic cost modeling as a basis for optimizing inspection and maintenance of turbine support structures in offshore wind farms N2 - The operational management of offshore wind farms includes inspection and maintenance (I&M) of the wind turbine support structures. These activities are complex and influenced by numerous uncertain factors that affect their costs. The uncertainty in the I&M costs should be considered in decision value analyses performed to optimize I&M strategies for the turbine support structures. In this paper, we formulate a probabilistic parametric model to describe I&M costs for the common case in which a wind farm is serviced and maintained using a workboat-based strategy. The model is developed based on (a) interviews with a wind farm operator, engineering consultants, and operation and maintenance engineers, as well as (b) scientific literature. Our methodology involves deriving the probabilistic models of the cost model parameters based on intervals representing a subjective expert opinion on the foreseeable ranges of the parameter values. The probabilistic cost model is applied to evaluate the total I&M costs, and a sensitivity analysis is conducted to identify the main cost drivers. The model can be utilized to optimize I&M strategies at the component, structural system, and wind farm level. To illustrate its potential use, we apply it in a numerical study in which we optimize I&M strategies at the structural system level and identify and demonstrate a simplified approach of capturing uncertain I&M costs in the optimization. The simplified approach is generalized and made available for maintenance cost optimization of offshore wind turbine structures. KW - Inspection KW - Maintenance KW - Turbine support structures KW - Offshore wind KW - Costs PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-626144 DO - https://doi.org/10.5194/wes-10-461-2025 SN - 2366-7443 SN - 2366-7451 VL - 10 IS - 2 SP - 461 EP - 481 PB - Copernicus Publications CY - Göttingen AN - OPUS4-62614 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -