Posters - WindEurope Annual Event 2024

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We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics, and will give delegates an opportunity to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please join us at the conference and take advantage of this opportunity to learn and engage with your peers in the academic community. We look forward to seeing you there!

PO017: FOWT mooring lines monitoring system based on machine learning strategy and floating substructure motions

Jaime Fernández, CTO, Inalia


The design of floating platforms for the new generation of offshore wind turbines involves many challenges, not only regarding the design and manufacturing of these, but also their operation and maintenance (O&M). One of the key components are the mooring lines, to which structural integrity and continuous monitoring present many challenges. Being able to do a continuous monitoring of the health and fatigue of these lines during the whole turbine's life is currently very difficult, as the manufacturers of force sensors cannot guarantee the durability of them for the whole lifetime of the wind turbine and the replacement is a very expensive and difficult task. However, having a measurement campaign with those sensors for one or two years is feasible, so integrating this data with hydrodynamic simulations, floating substructure motions and machine learning algorithms can scale into a continuous structural health monitoring (SHM) systems, independently of the expected floating offshore wind turbine (FOWT) lifetime or possible future life extension plans. The present paper focuses on the development of the machine learning strategy that predicts from floating substructure motions and wind&meteo-oceanic operating conditions the magnitude of loads on the FOWT mooring lines. While the availability of real data is very limited, the works have been carried out with synthetic data generated from hydrodynamic simulations with Orcaflex which have provided a good correlation degree between predicted and "real" data. It is expected to increase its accuracy once the data from real sensors is added to the system. This procedure opens up a very interesting journey that is worth exploring in order to reduce the level of sensorization and improve the scalability of SHM systems, among other advantages.

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