Literature DB >> 33477600

Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis.

Ming Ni1,2, Hongjie Wang1, Xudong Liu3, Yilin Liao1, Lin Fu1, Qianqian Wu1,2, Jiong Mu1,2, Xiaoyan Chen1,2, Jun Li1,2.   

Abstract

Multi-rotor unmanned aerial vehicles (UAVs) for plant protection are widely used in China's agricultural production. However, spray droplets often drift and distribute nonuniformly, thereby harming its utilization and the environment. A variable spray system is designed, discussed, and verified to solve this problem. The distribution characteristics of droplet deposition under different spray states (flight state, environment state, nozzle state) are obtained through computational fluid dynamics simulation. In the verification experiment, the wind velocity error of most sample points is less than 1 m/s, and the deposition ratio error is less than 10%, indicating that the simulation is reliable. A simulation data set is used to train support vector regression and back propagation neural network with multiple parameters. An optimal regression model with the root mean square error of 6.5% is selected. The UAV offset and nozzle flow of the variable spray system can be obtained in accordance with the current spray state by multi-sensor fusion and the predicted deposition distribution characteristics. The farmland experiment shows that the deposition volume error between the prediction and experiment is within 30%, thereby proving the effectiveness of the system. This article provides a reference for the improvement of UAV intelligent spray system.

Entities:  

Keywords:  aviation plant protection; back propagation neural network; deposition distribution characteristic; downwash wind field; farmland experiment; support vector regression

Mesh:

Year:  2021        PMID: 33477600      PMCID: PMC7831310          DOI: 10.3390/s21020638

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  9 in total

Review 1.  Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture.

Authors:  Wouter H Maes; Kathy Steppe
Journal:  Trends Plant Sci       Date:  2018-12-15       Impact factor: 18.313

2.  A systematic study of the class imbalance problem in convolutional neural networks.

Authors:  Mateusz Buda; Atsuto Maki; Maciej A Mazurowski
Journal:  Neural Netw       Date:  2018-07-29

3.  Swath pattern analysis from a multi-rotor unmanned aerial vehicle configured for pesticide application.

Authors:  Brian Richardson; Carol A Rolando; Chanatda Somchit; Christina Dunker; Tara M Strand; Mark O Kimberley
Journal:  Pest Manag Sci       Date:  2019-11-26       Impact factor: 4.845

4.  Qualitative and quantitative diagnosis of nitrogen nutrition of tea plants under field condition using hyperspectral imaging coupled with chemometrics.

Authors:  Yu-Jie Wang; Tie-Han Li; Ge Jin; Yu-Ming Wei; Lu-Qing Li; Yusef K Kalkhajeh; Jing-Ming Ning; Zheng-Zhu Zhang
Journal:  J Sci Food Agric       Date:  2019-10-08       Impact factor: 3.638

5.  Field evaluation of spray drift and environmental impact using an agricultural unmanned aerial vehicle (UAV) sprayer.

Authors:  Guobin Wang; Yuxing Han; Xuan Li; John Andaloro; Pengchao Chen; W Clint Hoffmann; Xiaoqiang Han; Shengde Chen; Yubin Lan
Journal:  Sci Total Environ       Date:  2020-05-29       Impact factor: 7.963

6.  Design of Plant Protection UAV Variable Spray System Based on Neural Networks.

Authors:  Sheng Wen; Quanyong Zhang; Xuanchun Yin; Yubin Lan; Jiantao Zhang; Yufeng Ge
Journal:  Sensors (Basel)       Date:  2019-03-05       Impact factor: 3.576

7.  Distribution characteristics on droplet deposition of wind field vortex formed by multi-rotor UAV.

Authors:  Shuang Guo; Jiyu Li; Weixiang Yao; Yilong Zhan; Yifan Li; Yeyin Shi
Journal:  PLoS One       Date:  2019-07-22       Impact factor: 3.240

8.  Integration of remote-weed mapping and an autonomous spraying unmanned aerial vehicle for site-specific weed management.

Authors:  Joseph E Hunter; Travis W Gannon; Robert J Richardson; Fred H Yelverton; Ramon G Leon
Journal:  Pest Manag Sci       Date:  2019-11-12       Impact factor: 4.845

  9 in total
  1 in total

1.  Droplet distribution in cotton canopy using single-rotor and four-rotor unmanned aerial vehicles.

Authors:  Yanhua Meng; Yan Ma; Zhiguo Wang; Hongyan Hu
Journal:  PeerJ       Date:  2022-06-14       Impact factor: 3.061

  1 in total

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