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Damage detection and diagnosis for offshore wind foundations

Author
Puruncajas, B.; Vidal, Y.; Tutivén, C.
Type of activity
Presentation of work at congresses
Name of edition
ICINCO - 17th International Conference on Informatics in Control, Automation and Robotics
Date of publication
2020
Presentation's date
2020-07
Book of congress proceedings
ICINCO 2020 - Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics
First page
181
Last page
187
Project funding
Development and validation of intelligent monitoring systems, pitch and structural damping control strategies for floating offshore wind turbines
Repository
http://hdl.handle.net/2117/329860 Open in new window
URL
https://www.insticc.org/node/TechnicalProgram/icinco/2020/presentationDetails/98861 Open in new window
Abstract
Structural health monitoring for wind turbines (WT) in remote locations, as offshore, is crucial (Presencia and Shafiee, 2018). Offshore wind farms are increasingly realized in water depths beyond 30 meters, where lattice foundations (as jacket-type) are a highly competitive substructure type (Moulas et al., 2017). In this work, a methodology for the diagnosis of structural damage in jacket-type foundations is stated by means of a small-scale structure -an experimental laboratory tower modeling ...
Citation
Puruncajas, B.; Vidal, Y.; Tutivén, C. Damage detection and diagnosis for offshore wind foundations. A: ICINCO - International Conference on Informatics in Control, Automation and Robotics. "ICINCO 2020 - Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics". 2020, p. 181-187. ISBN 978-989-758-442-8.
Keywords
Convolutional neural network, Data-driven, Offshore wind turbine, Structural health monitoring, Structural vibration
Group of research
CoDAlab - Control, Dynamics and Applications

Participants