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Abstract
Agricultural spray characteristics determine the efficiency of a pesticide application because size and velocity affect droplet trajectory and impact behavior. At present, the relevance of different characterization techniques remains controversial since discrepancies may be significant between measurements performed in different laboratories.
A digital image acquisition technique and analysis algorithm is proposed for droplet size and velocimetry measurements as an alternative to well-established techniques such as the Phase Doppler Particle Analyzer (PDPA) or laser diffraction spectrometry (LDS). The algorithm requires double exposed shadow images acquired in a back-lighted arrangement with a Particle Image Velocimetry (PIV) camera and a pulsed light emitting diode (LED). Spatial illumination heterogeneities are corrected by subtracting from each image a mean background acquired on several images without any particle. The algorithm accuracy is ensured by the rejection of out-of-focus particles using a focus parameter depending on gradient intensity at the particle edges. Thresholds for focus particle selection were determined by studying the evolution of the focus parameter and the error on particle size measurements from images containing droplets with uniform size at various distance of the object plane. Selected droplets were identified on both pairs of images to determine their size and velocity. Droplet size distributions were corrected to
account for the uneven sampling probability caused by the volumetric method.
Droplet size distributions of a set of reference nozzle/pressure combinations defined in the ISO/DIS 25358 were measured. The image technique was able to distinguish each of the reference sprays well. Comparison with PDPA measurements showed that the imaging technique tends to measure an equivalent Dv50, a lower Dv10 and a higher Dv90 leading therefore to a higher relative span factor. Velocity measurements showed good agreement between both techniques except for one nozzle/pressure combination.
A digital image acquisition technique and analysis algorithm is proposed for droplet size and velocimetry measurements as an alternative to well-established techniques such as the Phase Doppler Particle Analyzer (PDPA) or laser diffraction spectrometry (LDS). The algorithm requires double exposed shadow images acquired in a back-lighted arrangement with a Particle Image Velocimetry (PIV) camera and a pulsed light emitting diode (LED). Spatial illumination heterogeneities are corrected by subtracting from each image a mean background acquired on several images without any particle. The algorithm accuracy is ensured by the rejection of out-of-focus particles using a focus parameter depending on gradient intensity at the particle edges. Thresholds for focus particle selection were determined by studying the evolution of the focus parameter and the error on particle size measurements from images containing droplets with uniform size at various distance of the object plane. Selected droplets were identified on both pairs of images to determine their size and velocity. Droplet size distributions were corrected to
account for the uneven sampling probability caused by the volumetric method.
Droplet size distributions of a set of reference nozzle/pressure combinations defined in the ISO/DIS 25358 were measured. The image technique was able to distinguish each of the reference sprays well. Comparison with PDPA measurements showed that the imaging technique tends to measure an equivalent Dv50, a lower Dv10 and a higher Dv90 leading therefore to a higher relative span factor. Velocity measurements showed good agreement between both techniques except for one nozzle/pressure combination.
| Original language | English |
|---|---|
| Journal | Crop Protection |
| Volume | 89 |
| Pages (from-to) | 105-115 |
| ISSN | 0261-2194 |
| Publication status | Published - 2016 |
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Dive into the research topics of 'Measurements of reference ISO nozzles by high-speed imaging'. Together they form a unique fingerprint.Projects
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CAMERASPRAY: Integration of imaging techniques for the quantitative characterization of pesticide sprays
Nuyttens, D. (Project Manager) & Vulgarakis Minov, S. (Former Researcher)
1/03/11 → 28/02/15
Project: Research
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