High-speed camera thermometry of laser droplet generation

Bizjan, Benjamin; Kuznetsov, Alexander; Jeromen, Andrej; Govekar, Edvard; Širok, Brane

doi:10.1016/j.applthermaleng.2016.08.182

Cited by 7 publications

(2 citation statements)

References 16 publications

(38 reference statements)

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“…Rapidly and accurately measuring droplets parameters and mastering the droplets deposition law are indispensable preconditions for the development, test, production, and use of plant protection machinery, and they are of great significance for better understanding and controlling the spraying process. Common quantitative analysis approaches such as high-speed photography [ 8 ], laser holography [ 9 ], laser imaging [ 10 ], and fluorescent tracer [ 11 , 12 , 13 ] could directly measure droplets size and distribution law, but the sampling data of these methods have a poor continuity, complicated handling mode, and high operation difficulty, so they aren’t applicable to the large-scale rapid detection of droplets in the field.…”

Section: Related Workmentioning

confidence: 99%

An Intelligent Vision Based Sensing Approach for Spraying Droplets Deposition Detection

Wang

Yue

Liu

et al. 2019

Sensors

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The rapid development of vision sensor based on artificial intelligence (AI) is reforming industries and making our world smarter. Among these trends, it is of great significance to adapt AI technologies into the intelligent agricultural management. In smart agricultural aviation spraying, the droplets’ distribution and deposition are important indexes for estimating effectiveness in plant protection process. However, conventional approaches are problematic, they lack adaptivity to environmental changes, and consumes non-reusable test materials. One example is that the machine vision algorithms they employ can’t guarantee that the division of adhesive droplets thereby disabling the accurate measurement of critical parameters. To alleviate these problems, we put forward an intelligent visual droplet detection node which can adapt to the environment illumination change. Then, we propose a modified marker controllable watershed segmentation algorithm to segment those adhesive droplets, and calculate their characteristic parameters on the basis of the segmentation results, including number, coverage, coverage density, etc. Finally, we use the intelligent node to detect droplets, and then expound the situation that the droplet region is effectively segmented and marked. The intelligent node has better adaptability and robustness even under the condition of illumination changing. The large-scale distributed detection result indicates that our approach has good consistency with the non-recyclable water-sensitive paper approach. Our approach provides an intelligent and environmental friendly way of tests for spraying techniques, especially for plant protection with Unmanned Aerial Vehicles.

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Section: Related Workmentioning

confidence: 99%

An Intelligent Vision Based Sensing Approach for Spraying Droplets Deposition Detection

Wang

Yue

Liu

et al. 2019

Sensors

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show abstract

“…Due to the presence of multiple flow phases and the high temperatures of the molten alloy (often above 1500 C), only non-contact methods can be used to measure the temperature. Pyrometers and infrared cameras are the most common non-contact temperature measurement devices [27]. However, on the one hand, pyrometers are only capable of single-point temperature measurements.…”

Section: Temperature Measurementmentioning

confidence: 99%

Magnetic Materials by Melt Spinning Method, Structural Characterization, and Numerical Modeling

Pagnola¹,

Vivero²,

G.Marrugo³

2018

New Uses of Micro and Nanomaterials

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Chill block melt spinning is used in industrial processes for the production of metallic glasses. It is a rapid solidification process whereby a liquid metal is ejected at high pressure and temperature via a nozzle onto a rotating wheel solidifying in the form of a ribbon. In this work, starting from an alloy with the composition of Fe 78 Si 9 B 13 (% at.) reproduces the melt spinning technique to get the amorphous magnetic material. A CFD3D model based on the finite volume method (FVM) is proposed. For this purpose, the OpenFoam® open source code is used. In the ribbon production stage, it has been observed that the turbulence involved in the first reported transient lasts a few milliseconds, enough time to study the process with high-speed cameras. We measure the ejection speed by using optical flow on the melt contour. This enables us to check defects in the ribbons, which are predicted with the computational model, such as the case of cracks caused by irregularities in the first formation of the solid layer. The temperature measurement method relies on the fact that the digital camera is sensitive to electromagnetic radiation between 400 and 1000 nm in wavelength and the fact that the image gray level, which is proportional to the temperature T, provided the background illumination level is negligible.

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Formation of a single drop of molten steel following bursting of liquid film in a vertical steel plate illuminated by a high energy laser

et al. 2021

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High-speed camera thermometry of laser droplet generation

Abstract: High-speed camera thermometry of laser droplet generation,

Cited by 7 publications

References 16 publications

An Intelligent Vision Based Sensing Approach for Spraying Droplets Deposition Detection

An Intelligent Vision Based Sensing Approach for Spraying Droplets Deposition Detection

Magnetic Materials by Melt Spinning Method, Structural Characterization, and Numerical Modeling

Formation of a single drop of molten steel following bursting of liquid film in a vertical steel plate illuminated by a high energy laser

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