Author
Listed:
- Xiaojie Xu
(College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology, South China Agricultural University, Guangzhou 510642, China)
- Shengde Chen
(College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology, South China Agricultural University, Guangzhou 510642, China)
- Zhihong Li
(College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology, South China Agricultural University, Guangzhou 510642, China)
- Zehong Wu
(College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology, South China Agricultural University, Guangzhou 510642, China)
- Yuxiang Tan
(College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology, South China Agricultural University, Guangzhou 510642, China)
- Shimin Huang
(College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology, South China Agricultural University, Guangzhou 510642, China)
- Yubin Lan
(College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology, South China Agricultural University, Guangzhou 510642, China)
Abstract
The rotor airflow intensity and distribution characteristics of plant protection UAVs vary significantly with spatial positions below the rotor. Consequently, changes in the rotor–nozzle distance directly affect droplet motion and deposition patterns. To optimize the spraying effect of UAVs, this study combined a numerical simulation of rotor airflow and droplet deposition at different vertical distances between rotor and nozzle with field validation tests. The simulation results revealed that airflow intensity initially increases and then decreases with greater rotor–nozzle distance, peaking at 300–400 mm below the rotor with a maximum airflow velocity of 8.1 m/s. At 360 mm, the droplet swarm achieved its highest average velocity, corresponding to optimal deposition effect. Field tests confirmed a non-linear relationship between rotor–nozzle distance and droplet deposition. Droplet deposition first increased but declined sharply beyond the optimal range. When the distance was 360 mm, the target area exhibited the highest droplet deposition of 0.766 μL·cm −2 and the lowest drift rate of 23.31%. Although a certain deviation existed between numerical simulation results and field test values, both methods consistently identified 360 mm as the ideal distance for balancing deposition efficiency and drift control. These findings provide actionable insights for field trial design and advance precision spraying strategies for plant protection UAVs.
Suggested Citation
Xiaojie Xu & Shengde Chen & Zhihong Li & Zehong Wu & Yuxiang Tan & Shimin Huang & Yubin Lan, 2025.
"Distribution Characteristics of Rotor Airflow and Droplet Deposition of Plant Protection UAVs Under Varying Rotor–Nozzle Distances,"
Agriculture, MDPI, vol. 15(19), pages 1-18, September.
Handle:
RePEc:gam:jagris:v:15:y:2025:i:19:p:1995-:d:1756506
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:15:y:2025:i:19:p:1995-:d:1756506. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.