Damage Detection and Diagnosis for Offshore Wind Foundations

Bryan Puruncajas, Yolanda Vidal, Christian Tutivén

2020

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 an offshore-fixed jacket-type WT. In the literature, a lot of methodologies for damage detection can be found (Li et al., 2015). Among them, the vibration-based methods are one of the most prolific ones. However, they are, primarily, focused on the case of measurable input excitation and vibration response signals, with only few recent studies focused on the vibration–response–only case, the importance of which stems from the fact that in some applications the excitation cannot be imposed and often is not measurable. This work aims to contribute in this area, as the vibration excitation is given by the wind and analyzed by a convolutional neural network (CNN), with a classification accuracy result of 93 %.

Paper Citation

in Harvard Style

Puruncajas B., Vidal Y. and Tutivén C. (2020). Damage Detection and Diagnosis for Offshore Wind Foundations.In Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-442-8, pages 181-187. DOI: 10.5220/0009886101810187

in Bibtex Style

@conference{icinco20,
author={Bryan Puruncajas and Yolanda Vidal and Christian Tutivén},
title={Damage Detection and Diagnosis for Offshore Wind Foundations},
booktitle={Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2020},
pages={181-187},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009886101810187},
isbn={978-989-758-442-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Damage Detection and Diagnosis for Offshore Wind Foundations
SN - 978-989-758-442-8
AU - Puruncajas B.
AU - Vidal Y.
AU - Tutivén C.
PY - 2020
SP - 181
EP - 187
DO - 10.5220/0009886101810187