An experimental system to acquire aeroacoustic properties on wind turbine blades
Open accessAbstract
Wind turbine noise is a key issue preventing the successful exploitation of the full potential of wind energy throughout the world, especially in urban areas. To better assess and predict wind turbine noise, several aeroacoustic simulations and models have been developed over the past. Many semi-empirical models for noise emission and propagation rely on aeroacoustic properties at the blade level, including the pressure gradient, the spectrum of the pressure fluctuations, the convection velocity and the coherence lengths. Field measurements of these local quantities on operating wind turbines are valuable to improve the accuracy of the models. In the Aerosense project, a cost-effective smart measurement system is being developed that is thin, easy to install without damaging the blade, low power, self-sustaining and wirelessly transmitting. This measurement system uses MEMS sensors, which require some calibrations and corrections to obtain sufficiently accurate data. This paper describes the experimental system and its workflow, which has been developed within the Aerosense project to obtain sufficiently accurate measurements for semi-empirical noise emission and propagation models. The experimental system and its workflow are then validated in an anechoic wind tunnel on a NACA63-418 airfoil. The results show that this experimental system is able to acquire relevant aeroacoustic properties on operating wind turbines.
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From data between 2014 and 2018, the harvestable solar power amounts to P median = 207 μW/cm2 and P95% = 27.5 μW/cm2 for all but the 5% worst days in winter.
“From the data between 2014 and 2018, the harvestable solar power amounts to P median = 207 µW/cm 2 and P 95% = 27.5 µW/cm 2 for all but the 5% worst days in winter.”
From Aerosense: A Self-Sustainable and Long-Range Bluetooth Wireless Sensor Node for Aerodynamic and Aeroacoustic Monitoring on Wind Turbines (2023) · cites this paper as [26]
The Introduction and section 2 describe a wind-turbine pressure and acoustic measurement system, not a solar-power analysis. Searches for the 2014–2018 period, the 207 and 27.5 µW/cm² figures, and winter solar harvesting found no passage addressing the claim. (LLM, conf=0.78)
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Research works printed but not linked: 9
- Barlas E, Zhu W J, Shen W Z, Dag K O and Moriarty P 2017 The Journal of the Acoustical Society of America 142 3297-3310
- Bertagnolio F, Madsen H A, Fischer A and Bak C 2017 Journal of Sound and Vibration 387 127-162
- Rozenberg Y, Robert G and Moreau S 2012 AIAA Journal 50 2168-2179
- Schepers J G and Schreck S J 2019 Wiley Interdisciplinary Reviews: Energy and Environment 8 e320
- Fischer R, Mueller H, Polonelli T, Benini L and Magno M 2021 Windnode: A long-lasting and long- range bluetooth wireless sensor node for pressure and acoustic monitoring on wind turbines 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS)
- Madgwick S, Harrison A and Vaidyanathan R 2011 Estimation of imu and marg orientation using a gradient descent algorithm 2011 IEEE international conference on rehabilitation robotics (IEEE) pp 1-7
- Salze E, Bailly C, Marsden O, Jondeau E and Juve D 2014 An experimental characterisation of wall pressure wavevector-frequency spectra in the presence of pressure gradients 20th AIAA/CEAS Aeroacoustics Conference
- Van de Wyer N, Zapata A, Nogueira D and Schram C F 2018 Development of a test rig for the measurement of turbulent boundary layer wall pressure statistics 2018 AIAA/CEAS Aeroacoustics Conference
- Corcos G M 1964 Journal of Fluid Mechanics 18 353-378
Cited by
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Polonelli, T., Muller, H., Kong, W., Fischer, R., Benini, L., & Magno, M. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3224307 · Cited by 35 · see citing works
Self-citation
- Authors
- Deparday, J., Müller, H., Polonelli, T., & Barber, S.
- Affiliations
- OST - Ostschweizer Fachhochschule (CH)
- ETH Zurich (CH)
- Corresponding author
- Deparday, J
- Venue
- Journal of Physics: Conference Series
- Publisher
- IOP Publishing
- Published
- 2022-05-01
- Volume
- 2265
- Issue
- 2
- Pages
- 022089
- ISSN
- 1742-6588 (ISSN-L)
- 1742-6596
- OpenAlex
- W4281713956
- Cited by
- 8
- References
- 0
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 3 · 2022: 1
- FWCI
- 3.50
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Journal of Physics Conference Series (publishedVersion, cc-by)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
- ETH Zürich Research Collection
- Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (187087)
- Innosuisse - Schweizerische Agentur für Innovationsförderung
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Wind Energy Research and Development
- Physical Sciences › Engineering › Aerospace Engineering › Aerodynamics and Acoustics in Jet Flows
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Wind Turbine Control Systems
- Keywords
- wind turbine noise, aeroacoustics, wind turbine blades, MEMS sensors, pressure fluctuations, pressure gradient, noise propagation model, anechoic wind tunnel, wireless data transmission
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