Heming Hu, Yutaka Kaizu, Jingjing Huang, Kenichi Furuhashi, Hongduo Zhang, Xu Xiao, Ming Li, Kenji Imou. Design and performance test of a novel UAV air-assisted electrostatic centrifugal spraying system[J]. International Journal of Agricultural and Biological Engineering, 2022, 15(5): 34-40. DOI: 10.25165/j.ijabe.20221505.6891
Citation: Heming Hu, Yutaka Kaizu, Jingjing Huang, Kenichi Furuhashi, Hongduo Zhang, Xu Xiao, Ming Li, Kenji Imou. Design and performance test of a novel UAV air-assisted electrostatic centrifugal spraying system[J]. International Journal of Agricultural and Biological Engineering, 2022, 15(5): 34-40. DOI: 10.25165/j.ijabe.20221505.6891

Design and performance test of a novel UAV air-assisted electrostatic centrifugal spraying system

  • In order to improve the deposition and uniformity of the pesticide sprayed by the agricultural spraying drone, this study designed a novel spraying system, combining air-assisted spraying system with electrostatic technology. First, an air-assisted electrostatic centrifugal spray system was designed for agricultural spraying drones, including a shell, a diversion shell, and an electrostatic ring. Then, experiments were conducted to optimize the setting of the main parameters that affect the charge-to-mass ratio, and outdoor spraying experiments were carried out on the spraying effect of the air-assisted electrostatic centrifugal spray system. The results showed the optimum parameters were that the centrifugal rotation speed was 10 000 r/min, the spray pressure was 0.3 MPa, the fan rotation speed was 14 000 r/min, and the electrostatic generator voltage was 9 kV; The optimum charge-to-mass ratio of the spray system was 2.59 mC/kg. The average deposition density of droplets on the collecting platform was 366.1 particles/cm2 on the upper layer, 345.1 particles/cm2 on the middle layer, and 322.5 particles/cm2 on the lower layer. Compared to the results of uncharged droplets on the upper, middle, and lower layers, the average deposition density was increased by 34.9%, 30.4%, and 30.2%, respectively, and the uniformity of the distribution of the droplets at different collection points was better.
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