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一种基于立体视觉技术用于测量颗粒肥料撒播机撒播模式的开发。

Development of a Stereovision-Based Technique to Measure the Spread Patterns of Granular Fertilizer Spreaders.

作者信息

Cool Simon R, Pieters Jan G, Seatovic Dejan, Mertens Koen C, Nuyttens David, Van De Gucht Tim C, Vangeyte Jürgen

机构信息

Department of Biosystems Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium.

Fisheries and Food Research, Institute of Agricultural, Burg. Van Gansberghelaan 115, 9820 Merelbeke, Belgium.

出版信息

Sensors (Basel). 2017 Jun 15;17(6):1396. doi: 10.3390/s17061396.

DOI:10.3390/s17061396
PMID:28617339
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5492561/
Abstract

Centrifugal fertilizer spreaders are by far the most commonly used granular fertilizer spreader type in Europe. Their spread pattern however is error-prone, potentially leading to an undesired distribution of particles in the field and losses out of the field, which is often caused by poor calibration of the spreader for the specific fertilizer used. Due to the large environmental impact of fertilizer use, it is important to optimize the spreading process and minimize these errors. Spreader calibrations can be performed by using collection trays to determine the (field) spread pattern, but this is very time-consuming and expensive for the farmer and hence not common practice. Therefore, we developed an innovative multi-camera system to predict the spread pattern in a fast and accurate way, independent of the spreader configuration. Using high-speed stereovision, ejection parameters of particles leaving the spreader vanes were determined relative to a coordinate system associated with the spreader. The landing positions and subsequent spread patterns were determined using a ballistic model incorporating the effect of tractor motion and wind. Experiments were conducted with a commercial spreader and showed a high repeatability. The results were transformed to one spatial dimension to enable comparison with transverse spread patterns determined in the field and showed similar results.

摘要

离心式施肥机是目前欧洲使用最普遍的颗粒肥料撒播机类型。然而,其撒播模式容易出错,可能导致田间颗粒分布不理想以及肥料损失到田间外,这通常是由于撒播机针对所使用的特定肥料校准不当造成的。由于肥料使用对环境影响巨大,优化撒播过程并尽量减少这些误差非常重要。可以通过使用收集托盘来确定(田间)撒播模式进行撒播机校准,但这对农民来说非常耗时且成本高昂,因此并非常见做法。因此,我们开发了一种创新的多摄像头系统,以快速、准确地预测撒播模式,且与撒播机配置无关。利用高速立体视觉,相对于与撒播机相关联的坐标系确定离开撒播机叶片的颗粒的喷射参数。使用结合了拖拉机运动和风的影响的弹道模型确定着陆位置和随后的撒播模式。使用商用撒播机进行了实验,结果显示出高重复性。将结果转换到一个空间维度,以便与在田间确定的横向撒播模式进行比较,结果显示相似。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/57686b18157d/sensors-17-01396-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/29f1db500c85/sensors-17-01396-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/7e8e156ccfd3/sensors-17-01396-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/3a2c2b437614/sensors-17-01396-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/e02a5851168f/sensors-17-01396-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/0a40941c35da/sensors-17-01396-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/6ff78fe282e0/sensors-17-01396-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/b071239eaf7b/sensors-17-01396-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/deeaf0c5225e/sensors-17-01396-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/4eaf7b24997f/sensors-17-01396-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/46efbc00b1fc/sensors-17-01396-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/69e19e84b592/sensors-17-01396-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/57686b18157d/sensors-17-01396-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/29f1db500c85/sensors-17-01396-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/7e8e156ccfd3/sensors-17-01396-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/3a2c2b437614/sensors-17-01396-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/e02a5851168f/sensors-17-01396-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/0a40941c35da/sensors-17-01396-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/6ff78fe282e0/sensors-17-01396-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/b071239eaf7b/sensors-17-01396-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/deeaf0c5225e/sensors-17-01396-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/4eaf7b24997f/sensors-17-01396-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/46efbc00b1fc/sensors-17-01396-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/69e19e84b592/sensors-17-01396-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99fd/5492561/57686b18157d/sensors-17-01396-g012.jpg

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本文引用的文献

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Managing nitrogen for sustainable development.管理氮素以实现可持续发展。
Nature. 2015 Dec 3;528(7580):51-9. doi: 10.1038/nature15743. Epub 2015 Nov 23.
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Development of a High Irradiance LED Configuration for Small Field of View Motion Estimation of Fertilizer Particles.用于肥料颗粒小视野运动估计的高辐照度发光二极管配置的开发
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4
High speed stereovision setup for position and motion estimation of fertilizer particles leaving a centrifugal spreader.用于离心式撒肥机排出肥料颗粒位置和运动估计的高速立体视觉装置
Sensors (Basel). 2014 Nov 13;14(11):21466-82. doi: 10.3390/s141121466.