Downwash airflow distribution pattern of hexa-copter unmanned aerial vehicles

• Published in: International journal of agricultural and biological engineering 2024-08, Vol.17 (4), p.24-34
• Main Authors: Dengeru, Yallappa, Ramasamy, Kavitha, Allimuthu, Surendrakumar, Kannan, Balaji, Balakrishnan, Suthakar, Kumar Ayyasamy Paramasivam, Mohan, Yathendranaik, Ravi, Narayananaik, Ashoka, Kumar, Kavan
• Format: Article
• Language: English
• Subjects: Accuracy; Air flow; Cereal crops; Chemical pest control; Configurations; Crop dusting; Deposition; Downwash; Drones; Droplets; Flight; Flow velocity; Fluid dynamics; Investigations; Landing behavior; Measurement techniques; Parameters; Pattern analysis; Pesticides; Pests; Programming languages; Python; Rotors; Simulation; Spray nozzles; Sprayers; Spraying; Sprays; Turbulence models; Unmanned aerial vehicles; Vehicles; Velocity; Vertical distribution; Vertical takeoff; Wind effects; Wind measurement; Wind speed
• ISSN: 1934-6344; 1934-6352
• DOI: 10.25165/j.ijabe.20241704.7754

In recent times, the use of vertical take-off and landing (VTOL) multi-rotor Unmanned Aerial Vehicle (UAVs) for spraying chemical pesticides against weeds and pests has recently become popular. The current aerial spray application research is primarily focused on examining the influence of UAV spraying parameters such as flight height, travel speed, rotor configuration, droplet size, payload and wind velocity. The downwash airflow velocity generated by the UAV rotor propeller has a significant impact on the droplet deposition process. A test rig was developed to measure the downwash airflow pattern generated by the rotor propeller of a UAV. In this investigation, a six-rotor electric autonomous UAV sprayer was used to investigate the parameters and distribution laws of downwash airflow velocity. The downwash airflow velocity was measured using portable anemometers mounted on the test rig at radial positions viz., 0 m, 0.5 m, 1 m, 1.5 m and 2 m, perpendicular to (A) and parallel to the UAV's flight direction (У). The experiment was conducted at three levels of hover height, viz., 1 m, 2 m and 3 m (Z) and three levels of payload, viz., 0 kg, 5 kg, and 10 kg. The special downwash airflow distribution pattern was analysed using the Python programming language (Version 3.7). Results show that the downwash airflow velocity generated by the radial position of the UAV rotor is evenly distributed on the rotating loop and the standard deviation of the downwash airflow velocity is less than 0.5 m/s. The maximum downwash airflow velocity of 13.8 m/s was observed below the rotor at 10 kg payload capacity, 1 m hover height (Z), and 0.5 m in the A-direction. The minimum downwash wind field of 0.3 m/s was observed at 0 kg pay load capacity, 1 m height, and 2 m in the A-direction. The downwash airflow velocity along each position in the radial direction of the rotor increases initially and then decreases. This downwash airflow distribution results helps in mounting of spray nozzle configuration to drone sprayer which helps to understanding spray liquid distribution and other spray operational parameters. The influence of downwash airflow distribution combined with the spray operational parameters of the UAV sprayer viz., flight height, travel speed, rotor configuration, payload and wind velocity on spray volume distribution was studied. A field experiment was conducted to study the effect of UAV sprayer downwash airflow distribution on spray droplet deposition characterist