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A framework for data and structural integrity management for support structures in offshore wind farms based on building information modelling

  • 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 theSupport 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.zeige mehrzeige weniger

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Autor*innen:Lukas Eichner, Paul Gerards, Ralf HerrmannORCiD, Ronald SchneiderORCiD, Falk Hille, Matthias Baeßler
Dokumenttyp:Beitrag zu einem Tagungsband
Veröffentlichungsform:Graue Literatur
Sprache:Deutsch
Titel des übergeordneten Werkes (Deutsch):Proc. of the 8th Intl. Symp. on Reliability Engineering and Risk Management (ISRERM 2022)
Jahr der Erstveröffentlichung:2022
Organisationseinheit der BAM:7 Bauwerkssicherheit
7 Bauwerkssicherheit / 7.2 Ingenieurbau
Herausgeber (Institution):ISRERM Organizers
Verlag:Research Publishing
Verlagsort:Singapore
Erste Seite:111
Letzte Seite:117
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Angewandte Physik
Freie Schlagwörter:Offshore wind energy; building information modelling; structural health monitoring; structural integrity management; support structures
Themenfelder/Aktivitätsfelder der BAM:Energie
Veranstaltung:8th International Symposium on Reliability Engineering and Risk Management
Veranstaltungsort:Hannover, Germany
Beginndatum der Veranstaltung:04.09.2022
Enddatum der Veranstaltung:07.09.2022
DOI:10.3850/978-981-18-5184-1_MS-04-161-cd
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:12.09.2022
Referierte Publikation:Nein
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