Print Email Facebook Twitter Gaussian Process Latent Force Models for Virtual Sensing in a Monopile-Based Offshore Wind Turbine Title Gaussian Process Latent Force Models for Virtual Sensing in a Monopile-Based Offshore Wind Turbine Author Zou, J. (TU Delft Offshore Engineering) Cicirello, A. (TU Delft Mechanics and Physics of Structures) Iliopoulos, Alexandros (Siemens) Lourens, E. (TU Delft Dynamics of Structures; TU Delft Offshore Engineering) Contributor Rizzo, Piervincenzo (editor) Milazzo, Alberto (editor) Date 2022 Abstract Fatigue assessment in offshore wind turbine support structures requires the monitoring of strains below the mudline, where the highest bending moments occur. However, direct measurement of these strains is generally impractical. This paper presents the validation of a virtual sensing technique based on the Gaussian process latent force model for dynamic strain monitoring. The dataset, taken from an operating near-shore turbine in the Westermeerwind Park in the Netherlands, provides a unique opportunity for validation of strain estimates at locations below the mudline using strain gauges embedded within the monopile foundation. Subject Bayesian inferenceGaussian processOffshore wind turbinesVirtual sensing To reference this document use: http://resolver.tudelft.nl/uuid:9244f01e-ca70-4595-83c8-7e6cfd6800d3 DOI https://doi.org/10.1007/978-3-031-07254-3_29 Publisher Springer Embargo date 2022-06-19 ISBN 978-303107253-6 Source European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 1 Event 10th European Workshop on Structural Health Monitoring, EWSHM 2022, 2022-07-04 → 2022-07-07, Palermo, Italy Series Lecture Notes in Civil Engineering, 2366-2557, 253 LNCE Part of collection Institutional Repository Document type conference paper Rights © 2022 J. Zou, A. Cicirello, Alexandros Iliopoulos, E. Lourens Files PDF EWSHM_2022_Paper_Final_AC.pdf 1.12 MB Close viewer /islandora/object/uuid:9244f01e-ca70-4595-83c8-7e6cfd6800d3/datastream/OBJ/view