Articles | Volume 7, issue 3
https://doi.org/10.5194/wes-7-1053-2022
© Author(s) 2022. 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-7-1053-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 May 2022
Research article |
| 24 May 2022
| 24 May 2022
Very low frequency IEPE accelerometer calibration and application to a wind energy structure
Clemens Jonscher
CORRESPONDING AUTHOR
Institute of Structural Analysis, Leibniz University Hannover/ForWind, Appelstraße 9A, 30167 Hanover, Germany
Benedikt Hofmeister
Institute of Structural Analysis, Leibniz University Hannover/ForWind, Appelstraße 9A, 30167 Hanover, Germany
Tanja Grießmann
Institute of Structural Analysis, Leibniz University Hannover/ForWind, Appelstraße 9A, 30167 Hanover, Germany
Raimund Rolfes
Institute of Structural Analysis, Leibniz University Hannover/ForWind, Appelstraße 9A, 30167 Hanover, Germany
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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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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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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.
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To reduce the levelized costs of offshore wind energy, capital expenses of substructures have to be decreased significantly. Therefore, structural optimization approaches have been proposed in the recent past, mainly to improve the design of jackets. This work proposes a holistic approach to jacket optimization, which addresses some problems arising from methods that were presented in the literature.
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Short summary
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.
This work presents a method to use low-noise IEPE sensors in the low-frequency range down to...
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