Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1383-2022
© 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-7-1383-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jul 2022
Research article |
| 08 Jul 2022
| 08 Jul 2022
Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades
Institute for Energy Technology, Eastern Switzerland University of Applied Sciences, Oberseestrasse 10, 8640 Rapperswil-Jona, Switzerland
Julien Deparday
Institute for Energy Technology, Eastern Switzerland University of Applied Sciences, Oberseestrasse 10, 8640 Rapperswil-Jona, Switzerland
Yuriy Marykovskiy
Institute for Energy Technology, Eastern Switzerland University of Applied Sciences, Oberseestrasse 10, 8640 Rapperswil-Jona, Switzerland
Eleni Chatzi
Chair of Structural Mechanics and Monitoring (CSMM), ETH Zurich (ETHZ), 8093 Zurich, Switzerland
Chair of Structural Mechanics and Monitoring (CSMM), ETH Zurich (ETHZ), 8093 Zurich, Switzerland
Gregory Duthé
Chair of Structural Mechanics and Monitoring (CSMM), ETH Zurich (ETHZ), 8093 Zurich, Switzerland
Michele Magno
D-ITET, Center for Project-Based Learning (PBL), ETH Zurich (ETHZ), 8092 Zurich, Switzerland
Tommaso Polonelli
D-ITET, Center for Project-Based Learning (PBL), ETH Zurich (ETHZ), 8092 Zurich, Switzerland
Raphael Fischer
D-ITET, Center for Project-Based Learning (PBL), ETH Zurich (ETHZ), 8092 Zurich, Switzerland
Hanna Müller
D-ITET, Center for Project-Based Learning (PBL), ETH Zurich (ETHZ), 8092 Zurich, Switzerland
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Cited
12 citations as recorded by crossref.
- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
- Data-Driven wind turbine performance assessment and quantification using SCADA data and field measurements Y. Ding et al. 10.3389/fenrg.2022.1050342
- Acoustic-Signal-Based Damage Detection of Wind Turbine Blades—A Review S. Ding et al. 10.3390/s23114987
- A Self-Sustainable and Micro-Second Time Synchronized Multi-Node Wireless System for Aerodynamic Monitoring on Wind Turbines T. Polonelli et al. 10.1109/ACCESS.2023.3327422
- Instrumentation and Measurement Systems: Aerosense: A Wireless, Non-Intrusive, Flexible, and MEMS-Based Aerodynamic and Acoustic Measurement System for Operating Wind Turbines T. Polonelli et al. 10.1109/MIM.2023.10146566
- Spiking Neural Networks for Energy-Efficient Acoustic Emission-Based Monitoring F. Zonzini et al. 10.1109/OJIM.2024.3485618
- Architecting a digital twin for wind turbine rotor blade aerodynamic monitoring Y. Marykovskiy et al. 10.3389/fenrg.2024.1428387
- Enabling Co-Innovation for a Successful Digital Transformation in Wind Energy Using a New Digital Ecosystem and a Fault Detection Case Study S. Barber et al. 10.3390/en15155638
- Analysis of the performance of GNSS receiver in monitoring the behaviour of the wind turbine nacelle C. Xue et al. 10.1016/j.engstruct.2024.118633
- Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning G. Duthé et al. 10.1017/dce.2024.35
- The Impacts of Terrestrial Wind Turbine’s Operation on Telecommunication Services U. Abubakar et al. 10.3390/en16010371
- Hybrid Model for Inflow Conditions Inference on Airfoils Under Uncertainty Y. Marykovskiy et al. 10.2514/1.J063108
12 citations as recorded by crossref.
- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
- Data-Driven wind turbine performance assessment and quantification using SCADA data and field measurements Y. Ding et al. 10.3389/fenrg.2022.1050342
- Acoustic-Signal-Based Damage Detection of Wind Turbine Blades—A Review S. Ding et al. 10.3390/s23114987
- A Self-Sustainable and Micro-Second Time Synchronized Multi-Node Wireless System for Aerodynamic Monitoring on Wind Turbines T. Polonelli et al. 10.1109/ACCESS.2023.3327422
- Instrumentation and Measurement Systems: Aerosense: A Wireless, Non-Intrusive, Flexible, and MEMS-Based Aerodynamic and Acoustic Measurement System for Operating Wind Turbines T. Polonelli et al. 10.1109/MIM.2023.10146566
- Spiking Neural Networks for Energy-Efficient Acoustic Emission-Based Monitoring F. Zonzini et al. 10.1109/OJIM.2024.3485618
- Architecting a digital twin for wind turbine rotor blade aerodynamic monitoring Y. Marykovskiy et al. 10.3389/fenrg.2024.1428387
- Enabling Co-Innovation for a Successful Digital Transformation in Wind Energy Using a New Digital Ecosystem and a Fault Detection Case Study S. Barber et al. 10.3390/en15155638
- Analysis of the performance of GNSS receiver in monitoring the behaviour of the wind turbine nacelle C. Xue et al. 10.1016/j.engstruct.2024.118633
- Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning G. Duthé et al. 10.1017/dce.2024.35
- The Impacts of Terrestrial Wind Turbine’s Operation on Telecommunication Services U. Abubakar et al. 10.3390/en16010371
- Hybrid Model for Inflow Conditions Inference on Airfoils Under Uncertainty Y. Marykovskiy et al. 10.2514/1.J063108
Latest update: 25 Dec 2024
Short summary
Aerodynamic and acoustic field measurements on operating large-scale wind turbines are key for the further reduction in the costs of wind energy. In this work, a novel cost-effective MEMS (micro-electromechanical systems)-based aerodynamic and acoustic wireless measurement system that is thin, non-intrusive, easy to install, low power and self-sustaining is designed and tested.
Aerodynamic and acoustic field measurements on operating large-scale wind turbines are key for...
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