Articles | Volume 11, issue 11
https://doi.org/10.5194/wes-11-4205-2026
https://doi.org/10.5194/wes-11-4205-2026
Research article
 | 
11 Nov 2026
Research article |  | 11 Nov 2026

Machine learning framework for scour detection across multiple offshore wind farms

Mahmoud Abdelhak, Luke J. Prendergast, Jacques Tott-Buswell, Ramin Ghiasi, and Abdollah Malekjafarian

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Cited articles

Abdelhak, M., Tott-Buswell, J., Prendergast, L. J., Ghiasi, R., and Malekjafarian, A.: Scour identification around offshore wind turbine monopile foundations using an unsupervised anomaly detection approach, Ocean Eng., 340, 122365, https://doi.org/10.1016/j.oceaneng.2025.122365, 2025. 
Abdelhak, M., Prendergast, L. J., Tott-Buswell, J., Ghiasi, R., and Malekjafarian, A.: A transfer learning-based framework for scour detection around monopile-supported offshore wind turbines with limited data, Ocean Eng., 365, 127315, https://doi.org/10.1016/j.oceaneng.2026.127315, 2026a. 
Abdelhak, M., Prendergast, L. J., Tott-Buswell, J., Ghiasi, R., and Malekjafarian, A.: Wind farm-level scour detection around offshore monopile foundations using unsupervised domain adaptation, Mech. Syst. Signal Pr., 251, 114186, https://doi.org/10.1016/j.ymssp.2026.114186, 2026b. 
Arany, L. S., Bhattacharya, S., Macdonald, J. H. G., and Hogan, S. J.: Design of monopiles for offshore wind turbines in 10 steps, Soil Dyn. Earthq. Eng., 92, 126–152, https://doi.org/10.1016/j.soildyn.2016.09.024, 2017. 
Byrne, B., Mcadam, R., Burd, H., Houlsby, G., Martin, C., Zdravkovic, L., Taborda, D. M. G., Potts, D., Jardine, R., Sideri, M., Schroeder, F., Gavin, K., Doherty, P., Igoe, D., Wood, A., Kallehave, D., and Gretlund, J.: New design methods for large diameter piles under lateral loading for offshore wind applications, Proceedings of the Third International Symposium on Frontiers in Offshore Geotechnics, ISFOG 2015, Oslo, Norway, 2015. 
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This study proposes a method to detect seabed erosion around offshore wind turbines at the inter-farm level using acceleration data from a single tower sensor. Tested with simulations across different turbines and sites, it reliably identifies erosion even for unseen turbines, helping to reduce inspection costs and improve maintenance.
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