Development of Method of Rapid Analysis of Particle Size Distribution of the Coal Charge Based on Digital Image Processing

2015 ◽  
Vol 770 ◽  
pp. 512-517 ◽  
Author(s):  
O.V. Tailakov ◽  
M.P. Makeev ◽  
A.N. Kormin ◽  
A.I. Smyslov
Keyword(s):  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image Processing ◽  
Fractional Composition ◽  
Rapid Analysis ◽  
Optical Images ◽  
Coal Charge ◽  
Filtration Properties

Therein algorithms of application of digital models for evaluation of porosity and fractional composition of coals based on analysis of their optical images are offered. The models allow allocating significant informational objects and estimation of structural and filtration properties of coals. The results of algorithms application on recognition of the optical images of coals are presented, the particle size distribution of coal charge and porosity of coal is defined.

scholarly journals Identifying morphological characteristics of solid particles based on digital image analysis

Vestnik IGEU ◽  
2020 ◽  
pp. 64-70
Author(s):  
A.V. Ogurtzov ◽  
Yu.V. Khokhlova ◽  
V.E. Mizonov ◽  
V.A. Ogurtzov
Keyword(s):  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image Processing ◽  
Digital Image ◽  
Bulk Material ◽  
Morphological Characteristics ◽  
Solid Particles ◽  
Coal Particles

Enriched coal as an energy source has a number of undeniable environmental and economic advantages, and has a higher calorific value. Important characteristics that affect the technological process of coal flotation are the particle size distribution, the shape of the coal particles and their surface texture. Screen analysis is the most common method for determining the granulometric composition of granular media. However, it is not sensitive to the shape of the particles and the nature of their surface. With the sieve method of analysis, there is no direct measurement of any axes of the particle, except the case when the particle is ball-shaped. In this case, its size coincides with the edge length of the square mesh of the sieve. Thus, two particles of completely different shapes can pass through the same sieve opening. Our task was to develop a simple technique that allows identifying the shape and texture parameters of particles of the bulk material. To solve the problem in question, the algorithm implemented in MATLAB (Image Processing Toolbox) and the concept of fractals are used. A method for estimating the shape and texture of bulk material particles based on digital image processing has been proposed. The particle size distribution curves are constructed, obtained by sieving method and image processing method. It was found that these curves are in good agreement with each other. Digital image processing is an alternative to identifying the important quality characteristics of bulk materials.

Study on Soil Particle Size Distribution by Digital Image Processing

2013 ◽  
Vol 788 ◽  
pp. 627-630
Author(s):  
Jian Shu Hou
Keyword(s):  
Mechanical Property ◽  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image ◽  
Traditional Method ◽  
Processing Method ◽  
Distribution Analysis ◽  
Processing Technologies

The particle size distribution of soil is very importantto its physical and mechanical property. The ordinary method of the particlesize distribution analysis is based on shaking the soil through a set of sieves.But it will be difficult to use the method while there have particles largerthan the biggest aperture of the size sieves. Then the digital image processingwas used to solve the problem here. The processing technologies, such as imageanalysis and enhancement, deblurring, edge detection were studied to analyzethe image of soil particles. Then the image processing method was used to getthe particle size distribution accurately. Though some promotions need to becarried out in the further study, it is can be found that the image processingmethod is more efficiently than the traditional method.

Particle size distribution in oil-water dispersions using image processing

1987 ◽  
Vol 11 (4) ◽  
pp. 435-439 ◽  
Author(s):  
A.H. Kamel ◽  
S.A. Akashah ◽  
F.A. Leeri ◽  
M.A. Fahim
Keyword(s):  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Oil Water
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