Wind Pressure Orthogonal Decomposition Anemometer: A Wind Measurement Device for Multi-Rotor UAVs

Wind speed and direction are critical meteorological elements. Multi-rotor unmanned aerial vehicles UAVs are widely used as a premium payload platform in meteorological monitoring. The meteorological UAV is able to improve the spatial and temporal resolution of the elements collected. However, durin...

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Bibliographic Details
Published in:Drones (Basel) 2023-06, Vol.7 (6), p.366
Main Authors: Hou, Tianhao, Xing, Hongyan, Gu, Wei, Liang, Xinyi, Li, Haoqi, Zhang, Huaizhou
Format: Article
Language:English
Subjects:
Accuracy
Aircraft
Airframes
Algorithms
anemometer
Anemometers
Artificial intelligence
Atmospheric boundary layer
Aviation
Decomposition
Doppler radar
Drone aircraft
Hovering
Measurement
Measurement methods
Rotors
Sensors
Speed
Temporal resolution
Turbulence
UAV
Unmanned aerial vehicles
Velocity
Wind measurement
Wind pressure
Wind speed
Winds
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Summary:Wind speed and direction are critical meteorological elements. Multi-rotor unmanned aerial vehicles UAVs are widely used as a premium payload platform in meteorological monitoring. The meteorological UAV is able to improve the spatial and temporal resolution of the elements collected. However, during wind measurement missions, the installed anemometers are susceptible to interference caused by rotor turbulence. This paper puts forward a wind pressure orthogonal decomposition (WPOD) strategy to overcome this limitation in three ways: the location of the sensors, a new wind measurement method, and supporting equipment. A weak turbulence zone (WTZ) is found around the airframe, where the turbulence strength decays rapidly and is more suitable for installing wind measurement sensors. For the sensors to match the spatial structure of this area, a WPOD wind measurement method is proposed. An anemometer based on this principle was mounted on a quadrotor UAV to build a wind measurement system. Compared with a standard anemometer, this system has satisfactory performance. Analysis of the resulting data indicates that the error of the system is ±0.3 m/s and ±2° under hovering conditions and ±0.7 m/s and ±5° under moving conditions. In summary, WPOD points to a new orientation for wind measurement under a small spatial–temporal scale.
ISSN:2504-446X
2504-446X
DOI:10.3390/drones7060366