Articles | Volume 7, issue 1
https://doi.org/10.5194/wes-7-299-2022
https://doi.org/10.5194/wes-7-299-2022
Research article
 | 
08 Feb 2022
Research article |  | 08 Feb 2022

Data-driven farm-wide fatigue estimation on jacket-foundation OWTs for multiple SHM setups

Francisco d N Santos, Nymfa Noppe, Wout Weijtjens, and Christof Devriendt

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Cited articles

Anguita, D., Ghelardoni, L., Ghio, A., Oneto, L., and Ridella, S.: The `K' in K-fold Cross Validation, in: ESANN, 441–446, https://www.esann.org/sites/default/files/proceedings/legacy/es2012-62.pdf (last access: 7 February 2022), 2012. a
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Short summary
The estimation of fatigue in offshore wind turbine is highly relevant, as it can help extend the lifetime of these assets. This article attempts to answer this issue by developing a methodology based on artificial intelligence and data collected by sensors installed in real-world turbines. Good results are obtained, and this methodology is further used to learn the value of eight different sensor setups and employed in a real-world wind farm with 48 wind turbines.
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