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

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 s...

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Autores principales: Ni, Ming, Wang, Hongjie, Liu, Xudong, Liao, Yilin, Fu, Lin, Wu, Qianqian, Mu, Jiong, Chen, Xiaoyan, Li, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831310/
https://www.ncbi.nlm.nih.gov/pubmed/33477600
http://dx.doi.org/10.3390/s21020638
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author Ni, Ming
Wang, Hongjie
Liu, Xudong
Liao, Yilin
Fu, Lin
Wu, Qianqian
Mu, Jiong
Chen, Xiaoyan
Li, Jun
author_facet Ni, Ming
Wang, Hongjie
Liu, Xudong
Liao, Yilin
Fu, Lin
Wu, Qianqian
Mu, Jiong
Chen, Xiaoyan
Li, Jun
author_sort Ni, Ming
collection PubMed
description 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.
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spelling pubmed-78313102021-01-26 Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis Ni, Ming Wang, Hongjie Liu, Xudong Liao, Yilin Fu, Lin Wu, Qianqian Mu, Jiong Chen, Xiaoyan Li, Jun Sensors (Basel) Article 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. MDPI 2021-01-18 /pmc/articles/PMC7831310/ /pubmed/33477600 http://dx.doi.org/10.3390/s21020638 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ni, Ming
Wang, Hongjie
Liu, Xudong
Liao, Yilin
Fu, Lin
Wu, Qianqian
Mu, Jiong
Chen, Xiaoyan
Li, Jun
Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis
title Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis
title_full Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis
title_fullStr Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis
title_full_unstemmed Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis
title_short Design of Variable Spray System for Plant Protection UAV Based on CFD Simulation and Regression Analysis
title_sort design of variable spray system for plant protection uav based on cfd simulation and regression analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831310/
https://www.ncbi.nlm.nih.gov/pubmed/33477600
http://dx.doi.org/10.3390/s21020638
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