Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-1303-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-1303-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Towards accurate and practical drone-based wind measurements with an ultrasonic anemometer
William Thielicke
CORRESPONDING AUTHOR
OPTOLUTION Messtechnik GmbH, Gewerbestr. 18, 79539 Lörrach, Germany
Waldemar Hübert
OPTOLUTION Messtechnik GmbH, Gewerbestr. 18, 79539 Lörrach, Germany
Ulrich Müller
OPTOLUTION Messtechnik GmbH, Gewerbestr. 18, 79539 Lörrach, Germany
Michael Eggert
Physikalisch-Technische Bundesanstalt, Bundesallee 100, 38116 Braunschweig, Germany
Paul Wilhelm
Physikalisch-Technische Bundesanstalt, Bundesallee 100, 38116 Braunschweig, Germany
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Cited
34 citations as recorded by crossref.
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- Spatially distributed and simultaneous wind measurements with a fleet of small quadrotor UAS T. Wetz & N. Wildmann 10.1088/1742-6596/2265/2/022086
- Distributed wind measurements with multiple quadrotor unmanned aerial vehicles in the atmospheric boundary layer T. Wetz et al. 10.5194/amt-14-3795-2021
- Framework for UAV-based river flow velocity determination employing optical recognition A. Kriščiūnas et al. 10.1016/j.jag.2024.104154
- Wind Estimation by Multirotor Drone State Using Machine Learning with Data Rotation and Reduction S. Zimmerman et al. 10.2139/ssrn.4089510
- Validation of wind measurements from a multirotor RPAS-mounted ultrasonic wind sensor using a ground-based LiDAR system L. Scicluna et al. 10.1139/dsa-2022-0034
- A New Methodology for High Spatiotemporal Resolution Measurements of Air Volatile Organic Compounds: From Sampling to Data Deconvolution Y. Yang et al. 10.1021/acs.est.4c05669
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- UAV-based in situ measurements of CO2 and CH4 fluxes over complex natural ecosystems A. Bolek et al. 10.5194/amt-17-5619-2024
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
- Experimental Characterization of Propeller-Induced Flow (PIF) below a Multi-Rotor UAV A. Flem et al. 10.3390/atmos15030242
- Development and flight-test verification of two-dimensional rotational low-airspeed sensor for small helicopters D. Fujiwara & T. Tonoike 10.1186/s40648-024-00274-2
- Rotary-wing drone-induced flow – comparison of simulations with lidar measurements L. Jin et al. 10.5194/amt-17-2721-2024
- Unmanned Aerial Vehicle Communications for Civil Applications: A Review M. Ghamari et al. 10.1109/ACCESS.2022.3208571
- Multi-point in situ measurements of turbulent flow in a wind turbine wake and inflow with a fleet of uncrewed aerial systems T. Wetz & N. Wildmann 10.5194/wes-8-515-2023
- Evaluation of an Automatic Meteorological Drone Based on a 6-Month Measurement Campaign M. Hervo et al. 10.3390/atmos14091382
- Wind estimation by multirotor drone state using machine learning with data rotation and reduction S. Zimmerman et al. 10.1016/j.measurement.2022.111491
- Flow Structure around a Multicopter Drone: A Computational Fluid Dynamics Analysis for Sensor Placement Considerations M. Ghirardelli et al. 10.3390/drones7070467
- Towards vertical wind and turbulent flux estimation with multicopter uncrewed aircraft systems N. Wildmann & T. Wetz 10.5194/amt-15-5465-2022
- Progress in monitoring methane emissions from landfills using drones: an overview of the last ten years D. Fosco et al. 10.1016/j.scitotenv.2024.173981
- Experience of Studying the Turbulent Structure of the Atmospheric Boundary Layer Using an Unmanned Aerial Vehicle D. Chechin et al. 10.1134/S0001433821050042
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- Design and Optimization of Resonant Cavity Piezoelectric Cantilever Sensor for Wind Velocity and Direction Measurement J. Hu et al. 10.1109/TIM.2022.3178490
- Uncertainty in the Mobile Observation of Wind E. Leibensperger et al. 10.3390/atmos14050765
- Lessons learned from a UAV survey and methane emissions calculation at a UK landfill H. Yong et al. 10.1016/j.wasman.2024.03.025
- Flight Experiments and Numerical Simulations for Investigating Multicopter Flow Field and Structure Deformation F. Pätzold et al. 10.3390/atmos14091336
- A Feedforward Quadrotor Disturbance Rejection Method for Visually Identified Gust Sources Based on Transfer Reinforcement Learning F. Song et al. 10.1109/TAES.2023.3275937
- An evaluation of different measurement strategies to measure wind turbine near wake flow with small multicopter UAS N. Wildmann & J. Kistner 10.1088/1742-6596/2767/4/042004
- Wind Source Localization System Based on a Palm-Sized Quadcopter K. Yokota et al. 10.3390/app14156425
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- Measurements and modelling of the three-dimensional near-field dispersion of particulate matter emitted from passenger ships in a port environment M. Haugen et al. 10.1016/j.atmosenv.2022.119384
- Seed Dispersal Models for Natural Regeneration: A Review and Prospects M. Kim et al. 10.3390/f13050659
- How accurate are ultrasonic anemometers, calibrated in a laminar wind tunnel, under turbulent conditions? G. Glabeke et al. 10.1088/1742-6596/2767/4/042023
33 citations as recorded by crossref.
- Advanced Leak Detection and Quantification of Methane Emissions Using sUAS D. Hollenbeck et al. 10.3390/drones5040117
- Spatially distributed and simultaneous wind measurements with a fleet of small quadrotor UAS T. Wetz & N. Wildmann 10.1088/1742-6596/2265/2/022086
- Distributed wind measurements with multiple quadrotor unmanned aerial vehicles in the atmospheric boundary layer T. Wetz et al. 10.5194/amt-14-3795-2021
- Framework for UAV-based river flow velocity determination employing optical recognition A. Kriščiūnas et al. 10.1016/j.jag.2024.104154
- Wind Estimation by Multirotor Drone State Using Machine Learning with Data Rotation and Reduction S. Zimmerman et al. 10.2139/ssrn.4089510
- Validation of wind measurements from a multirotor RPAS-mounted ultrasonic wind sensor using a ground-based LiDAR system L. Scicluna et al. 10.1139/dsa-2022-0034
- A New Methodology for High Spatiotemporal Resolution Measurements of Air Volatile Organic Compounds: From Sampling to Data Deconvolution Y. Yang et al. 10.1021/acs.est.4c05669
- An assembled hot wire anemometer design X. Yao et al. 10.21595/jme.2023.23637
- UAV-based in situ measurements of CO2 and CH4 fluxes over complex natural ecosystems A. Bolek et al. 10.5194/amt-17-5619-2024
- A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes M. Amiri et al. 10.1016/j.rser.2024.114279
- Experimental Characterization of Propeller-Induced Flow (PIF) below a Multi-Rotor UAV A. Flem et al. 10.3390/atmos15030242
- Development and flight-test verification of two-dimensional rotational low-airspeed sensor for small helicopters D. Fujiwara & T. Tonoike 10.1186/s40648-024-00274-2
- Rotary-wing drone-induced flow – comparison of simulations with lidar measurements L. Jin et al. 10.5194/amt-17-2721-2024
- Unmanned Aerial Vehicle Communications for Civil Applications: A Review M. Ghamari et al. 10.1109/ACCESS.2022.3208571
- Multi-point in situ measurements of turbulent flow in a wind turbine wake and inflow with a fleet of uncrewed aerial systems T. Wetz & N. Wildmann 10.5194/wes-8-515-2023
- Evaluation of an Automatic Meteorological Drone Based on a 6-Month Measurement Campaign M. Hervo et al. 10.3390/atmos14091382
- Wind estimation by multirotor drone state using machine learning with data rotation and reduction S. Zimmerman et al. 10.1016/j.measurement.2022.111491
- Flow Structure around a Multicopter Drone: A Computational Fluid Dynamics Analysis for Sensor Placement Considerations M. Ghirardelli et al. 10.3390/drones7070467
- Towards vertical wind and turbulent flux estimation with multicopter uncrewed aircraft systems N. Wildmann & T. Wetz 10.5194/amt-15-5465-2022
- Progress in monitoring methane emissions from landfills using drones: an overview of the last ten years D. Fosco et al. 10.1016/j.scitotenv.2024.173981
- Experience of Studying the Turbulent Structure of the Atmospheric Boundary Layer Using an Unmanned Aerial Vehicle D. Chechin et al. 10.1134/S0001433821050042
- Maritime Emission Monitoring: Development and Testing of a UAV-Based Real-Time Wind Sensing Mission Planner Module T. Karachalios et al. 10.3390/s24030950
- Enhancing wildfire propagation model predictions using aerial swarm-based real-time wind measurements: A conceptual framework M. Tavakol Sadrabadi & M. Innocente 10.1016/j.apm.2024.03.012
- Design and Optimization of Resonant Cavity Piezoelectric Cantilever Sensor for Wind Velocity and Direction Measurement J. Hu et al. 10.1109/TIM.2022.3178490
- Uncertainty in the Mobile Observation of Wind E. Leibensperger et al. 10.3390/atmos14050765
- Lessons learned from a UAV survey and methane emissions calculation at a UK landfill H. Yong et al. 10.1016/j.wasman.2024.03.025
- Flight Experiments and Numerical Simulations for Investigating Multicopter Flow Field and Structure Deformation F. Pätzold et al. 10.3390/atmos14091336
- A Feedforward Quadrotor Disturbance Rejection Method for Visually Identified Gust Sources Based on Transfer Reinforcement Learning F. Song et al. 10.1109/TAES.2023.3275937
- An evaluation of different measurement strategies to measure wind turbine near wake flow with small multicopter UAS N. Wildmann & J. Kistner 10.1088/1742-6596/2767/4/042004
- Wind Source Localization System Based on a Palm-Sized Quadcopter K. Yokota et al. 10.3390/app14156425
- High-resolution wind speed measurements with quadcopter uncrewed aerial systems: calibration and verification in a wind tunnel with an active grid J. Kistner et al. 10.5194/amt-17-4941-2024
- Measurements and modelling of the three-dimensional near-field dispersion of particulate matter emitted from passenger ships in a port environment M. Haugen et al. 10.1016/j.atmosenv.2022.119384
- Seed Dispersal Models for Natural Regeneration: A Review and Prospects M. Kim et al. 10.3390/f13050659
Latest update: 06 Oct 2024
Short summary
We developed a wind-measuring drone with exceptional measuring accuracy and a very long flight time. Measurements are extensively validated at different levels. A comparison with a bistatic lidar reveals very small bias and RMSEs. We also present a demonstration measurement in the wake of a wind turbine. We think that our solution is a significant enhancement to existing designs, and other researchers can benefit from the details that we are giving in the paper.
We developed a wind-measuring drone with exceptional measuring accuracy and a very long flight...