Mooring force estimation for floating offshore wind turbines with augmented Kalman Filter: a step towards digital twin

Research output: Chapter in Book/Report/Conference proceedingConference contribution book


During the recent research studies Digital Twin (DT) simulation models for Structural Health Monitoring (SHM) based on data-driven mode have been developed, which can provide accurate simulation and prediction of mooring forces of Floating Offshore Wind Turbines (FOWTs). However, the performance of this kind modelling is highly affected by the quantity of real data training set and it is limited to some specific configuration and the recorded environmental conditions. More importantly, the data-driven DT cannot interpret the physical meaning of structural dynamic interactions.

Therefore, a new Physics-Based estimator is proposed in this work. The fully coupled FOWT simulations are carried out in QBlade Ocean and the simulation results are used to prepare the Reduced-Order Model by system identification for different sea states. The proposed estimator is based on the Augmented Kalman Filter in which the unknown mooring force is augmented as a state. The prediction of state is adjusted with the measurable platform motion data. It demonstrates the ability of filtering the noise in measurements and capturing the dynamic behaviour of FOWT with acceptable low computational cost. This real-time state estimator also provides the foundation of developing the DT modelling framework of FOWT and enables us to scale-up FOWTs in the next stage.
Original languageEnglish
Title of host publicationProceedings of ASME 2023 5th International Offshore Wind Technical Conference, IOWTC 2023
Place of PublicationNew York, NY
Number of pages9
ISBN (Electronic)9780791887578
Publication statusPublished - 26 Jan 2024
Event5th International Offshore Wind Technical Conference - Exeter University, Exeter, United Kingdom
Duration: 18 Dec 202319 Dec 2023


Conference5th International Offshore Wind Technical Conference
Abbreviated titleIOWTC2023
Country/TerritoryUnited Kingdom


  • digital twin
  • floating offshore wind turbine (FOWT)
  • mooring


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