Articles | Volume 11, issue 9
https://doi.org/10.5194/wes-11-3359-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-3359-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Virtual sensing for strain estimation in wind turbine support structures based on a biaxial accelerometer
Jonathan Thurn
CORRESPONDING AUTHOR
Leibniz University Hannover/ForWind, Institute of Structural Analysis, Appelstraße 9A, 30167 Hanover, Germany
Clemens Jonscher
Leibniz University Hannover/ForWind, Institute of Structural Analysis, Appelstraße 9A, 30167 Hanover, Germany
Benedikt Hofmeister
Photonics and Terahertz Technology, Ruhr-University Bochum, Germany, Universitätsstraße 150, 44801 Bochum, Germany
Gianluca Zorzi
RWE Offshore Wind GmbH, Drehbahn 47–49, 20354 Hamburg, Germany
Raimund Rolfes
Leibniz University Hannover/ForWind, Institute of Structural Analysis, Appelstraße 9A, 30167 Hanover, Germany
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Wind Energ. Sci., 11, 1771–1789, https://doi.org/10.5194/wes-11-1771-2026, https://doi.org/10.5194/wes-11-1771-2026, 2026
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This study investigates how finite-element (FE) models of different fidelity affect the damage identification in a 31 m wind turbine rotor blade tested under edgewise fatigue loading. Different design variable configurations are compared, whereby the FE model updating is based on modal parameters identified from measured vibration data.
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Revised manuscript accepted for WES
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A lifetime reassessment of an offshore wind turbine using Kriging meta-models is performed. This method is compared to a full lifetime reassessment using aeroelastic simulations considering all actually occurred combinations of environmental parameters and to the approach according to IEC 61400-3. By using the meta-models, the computing time can be significantly reduced compared to the other two methods, while ensuring a high approximation quality in the prediction of the lifetime fatigue loads.
Franziska Schmidt, Clemens Hübler, and Raimund Rolfes
Wind Energ. Sci., 10, 3069–3089, https://doi.org/10.5194/wes-10-3069-2025, https://doi.org/10.5194/wes-10-3069-2025, 2025
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In this work, a Kriging meta-model of an idling offshore wind turbine is analysed in detail for the first time. It becomes clear that the findings regarding meta-modelling of the idling wind turbine are generally similar to the findings regarding meta-modelling of the same wind turbine in normal operation. However, for the approximation of the rotor blade root bending moments, two additional input parameters have to be included compared to the same wind turbine in operation.
Clemens Jonscher, Paula Helming, David Märtins, Andreas Fischer, David Bonilla, Benedikt Hofmeister, Tanja Grießmann, and Raimund Rolfes
Wind Energ. Sci., 10, 193–205, https://doi.org/10.5194/wes-10-193-2025, https://doi.org/10.5194/wes-10-193-2025, 2025
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This study investigates dynamic displacement estimation using double-time-integrated acceleration signals for future application in load monitoring based on accelerometers. To estimate displacements without amplitude distortion, a tilt error compensation method for low-frequency vibrations of tower structures using the static bending line without the need for additional sensors is presented. The method is validated using a full-scale onshore wind turbine tower and a terrestrial laser scanner.
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Wind Energ. Sci., 8, 639–659, https://doi.org/10.5194/wes-8-639-2023, https://doi.org/10.5194/wes-8-639-2023, 2023
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Extensive measurements in the area of wind turbines were performed in order to validate a sound propagation model. The measurements were carried out under various environmental conditions and included the acquisition of acoustical, meteorological and wind turbine performance data. By processing and analysing the measurement data, validation cases and input parameters for the propagation model were derived. Comparing measured and modelled propagation losses, generally good agreement is observed.
Clemens Hübler and Raimund Rolfes
Wind Energ. Sci., 7, 1919–1940, https://doi.org/10.5194/wes-7-1919-2022, https://doi.org/10.5194/wes-7-1919-2022, 2022
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Offshore wind turbines are beginning to reach their design lifetimes. Hence, lifetime extensions are becoming relevant. To make well-founded decisions on possible lifetime extensions, fatigue damage predictions are required. Measurement-based assessments instead of simulation-based analyses have rarely been conducted so far, since data are limited. Therefore, this work focuses on the temporal extrapolation of measurement data. It is shown that fatigue damage can be extrapolated accurately.
Clemens Jonscher, Benedikt Hofmeister, Tanja Grießmann, and Raimund Rolfes
Wind Energ. Sci., 7, 1053–1067, https://doi.org/10.5194/wes-7-1053-2022, https://doi.org/10.5194/wes-7-1053-2022, 2022
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This work presents a method to use low-noise IEPE sensors in the low-frequency range down to 0.05 Hz. In order to achieve phase and amplitude accuracy with this type of sensor in the low-frequency range, a new calibration procedure for this frequency range was developed. The calibration enables the use of the low-noise IEPE sensors for large structures, such as wind turbines. The calibrated sensors can be used for wind turbine monitoring, such as fatigue monitoring.
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Short summary
Load monitoring for wind turbine support structures is essential as turbines approach the end of their design life. Typically, load monitoring involves estimating strain from vibrational measurements. This paper introduces an approach that uses a biaxial and DC-capable acceleration sensor to estimate strains across all fatigue-relevant excitation frequencies on the entire support structure, enabled by compensating for gravity-induced biases in acceleration measurements.
Load monitoring for wind turbine support structures is essential as turbines approach the end of...
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