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Development of sensor system for real-time measurement of droplet deposition of agricultural sprayers

文献类型： 外文期刊

作者： Li, Longlong 1 ; Zhang, Ruirui 1 ; Chen, Liping 2 ; Yi, Tongchuan 2 ; Xu, Gang 1 ; Xue, Daxuan 5 ; Tang, Qing 2 ; Zhang, 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

2.Natl Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

3.Natl Ctr Int Res Agr Aerial Applicat Technol, Beijing 100097, Peoples R China

4.Beijing Acad Agr & Forestry Sci, Beijing Key Lab Intelligent Equipment Technol Agr, Beijing 100097, Peoples R China

5.Capital Normal Univ, Coll Informat Engn, Beijing 100048, Peoples R China

6.Univ Queensland, Ctr Pesticide Applicat & Safety, St Lucia, Qld 4072, Australia

7.Univ Nottingham Ningbo China, Fac Sci & Engn, Ningbo 315100, Peoples R China

关键词： deposition measurement; agricultural sprayer; droplets; intelligent sensor

期刊名称：INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING （ 影响因子：2.032； 五年影响因子：2.137 ）

ISSN： 1934-6344

年卷期： 2021 年 14 卷 5 期

页码：

收录情况： SCI

摘要： During the chemical application process, droplet deposition on a target is an important reference indicator for evaluating the spraying technique and its performance. In order to quickly obtain deposition results in the field, this study proposed a novel system based on surface humidity sensors. The basic principle is to convert the measured physical quantity change into a capacitance change, thereby realizing the physical quantity to electrical signal conversion. An Android application for mobile terminal and corresponding coordinator were developed, which allowed operators to control multiple sensors simultaneously through the Bluetooth. The soluble tracer detected by spectrophotometer was used to calibrate the system. The obtained results indicated a good correlation between deposition volume and voltage increment output from the newly system (R-2 of the six nozzles with D-v0.5 ranging from 107.28 mu m to 396.20 mu m were 0.8674-0.9729), and a power regression model based on the least squares technique (R-2 =0.8022) was developed. In the field test, the system exhibited an optimal performance in predicting the deposition volume. Compared with the conventional method of measuring tracer concentration, the deviation was less than 10%. In addition, the system exhibited good fitting curve of the deposition distribution with droplet number results measured by the water sensitive paper method.

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