Articles | Volume 9, issue 4
https://doi.org/10.5194/wes-9-1005-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.Experimental validation of a short-term damping estimation method for wind turbines in nonstationary operating conditions
Related subject area
Thematic area: Dynamics and control | Topic: Dynamics and aeroservoelasticity
Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison
The rotor as a sensor – observing shear and veer from the operational data of a large wind turbine
Investigating the interactions between wakes and floating wind turbines using FAST.Farm
A digital twin solution for floating offshore wind turbines validated using a full-scale prototype
Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm
Wind Energ. Sci., 9, 1747–1763,
2024Wind Energ. Sci., 9, 1419–1429,
2024Wind Energ. Sci. Discuss.,
2024Revised manuscript accepted for WES
Wind Energ. Sci., 9, 1–24,
2024Wind Energ. Sci., 8, 1387–1402,
2023Cited articles
Au, S.-K.: Operational Modal Analysis: Modeling, Bayesian Inference, Uncertainty Laws, Springer, Singapore, ISBN 9789811041181, https://doi.org/10.1007/978-981-10-4118-1, 2017. a
Avendaño-Valencia, L. D. and Chatzi, E. N.: Multivariate GP-VAR models for robust structural identification under operational variability, Probabil. Eng. Mech., 60, 103035, https://doi.org/10.1016/j.probengmech.2020.103035, 2020. a
Avendaño-Valencia, L. D. and Fassois, S. D.: Stationary and non-stationary random vibration modelling and analysis for an operating wind turbine, Mech. Syst. Signal Process., 47, 263–285, 2014. a
Avendaño-Valencia, L. D., Chatzi, E. N., and Tcherniak, D.: Gaussian process models for mitigation of operational variability in the structural health monitoring of wind turbines, Mech. Syst. Signal Process., 142, 106686, https://doi.org/10.1016/j.ymssp.2020.106686, 2020. a