The existing and urgent problem to be solved is the low accuracy and efficiency of coal/gangue recognition. Image processing method is the most promising approach for automatic coal/gangue recognition [6], [7], [8]. However, because gangue is the blackgray solid wastes that mixed in coal, the main existing problems for imaging recognition is ...
In this paper, we aim at demonstrating the feasibility of measurement of coal fragments size distribution by using imaging processing technic. The image analysis is achieved by application of MATLAB. The image acquisition and analysis procedures are described in Section 2. In Section 3, the statistical size distribution of coal fragments ...
To estimate the density and sulfur content level of highsulfur coal, a novel approach based on image processing and the support vector machine optimized by Grey wolf optimization (GWOSVM) was ...
Size distribution measurement of coal fragments using digital imaging processing Xiaohan Yang a b, Ting Ren a b, Lihai Tan a Add to Mendeley https://// Get rights and content • Accurate and fast measurement of coal fragments generated by uniaxial compression tests using digital imaging processing. •
The available realtime ash content measurement techniques include radiometry, photoelectric measurement, and image processing [3,4,5]. Among these techniques, radiometry is used most widely in coal industry, which can be divided into two categories,, sourcebased radiometry, and passive radiometry.
Comparison of Coal Particle Size Measurement Results of. Di ... probability of any piece in any step is constant when coals are. ... analysis of coarse aggregate using digital image processing, ...
The belt speed was m/s during the shooting, and the line frequency of the camera was set to 2000. The particle size of the coal or gangue was between 50 mm and 350 mm. The gangue is black and has an attached coal slurry. Download : Download highres image (189KB) Download : Download fullsize image; Fig. 6. Image acquisition platform.
Cleat geometry Image processing Coal properties CT scans 1. Introduction Coal cleat networks Coal is characterised by its unique microstructure of a low permeable porous matrix intersected by a network of face and butt cleats. Cleats are natural openingmode fractures within coal beds.
The measurement accuracy of the particle size of coal determined by using he image acquisition and analysis system described in Section was verified by randomly selecting five particles in each size interval and measuring their sizes by the method outlined in Fig. 8.
Traditional grain size determination in materials characterization involves microscopy images and a laborious process requiring significant manual input and human expertise. In recent years, the development of computer vision (CV) has provided an alternative approach to microstructural characterization with preliminary implementations greatly simplifying the grain size determination process ...
This review is based on how to measure particle sizes with different image processing techniques. In addition to this, particle size significantly affects the mechanical properties of the...
Full size image. Fig. 3. ... Using binarization processing and contour fitting, ... are the coal and gangue particles measurement and scanning data files, are the coal and ...
To validate the feasibility of simultaneously measuring the size and velocity of coal powder by trajectory imaging, about 2000 coal particles with a size range of 100125 μm were recorded under the exposure time of 2 ms, and imaging magnification β= The obtained size and velocity were compared with that using the shadow image method ...
The stability of a pulverized coal flame has been measured continuously and quantitatively based on the digital imaging and image processing techniques. Results obtained on a 600 MWth coalfired supercritical unit have demonstrated that, in a routine boiler "turning off" process, the flame stability is well characterized using the numerical ...
Machine vision technology [12,13] is widely used in coal gangue image processing [14], target region segmentation [15], and other fields for its economic, efficient, safe, and reliable ...
To obtain the geometrical statistics of the coal cleat network at the core scale, quantitative image analysis methods on the segmented microCT images have been developed. BossieCodreanu et al. (2004) and ( Mazumder et al., 2006) measured cleat density, spacing, orientations and aperture sizes using microCT scanning.
DOI: / Corpus ID: ; Estimation of coal particle size distribution by image segmentation article{Zhang2012EstimationOC, title={Estimation of coal particle size distribution by image segmentation}, author={Zelin Zhang and Jianguo Yang and Lihua Ding and Yuemin Zhao}, journal={International journal of mining science and technology}, year={2012}, volume={22 ...
The pore structure parameters of coal have an important influence on the exploration and development of coalbed methane. In this study, a series of pore structure parameters, including porosity, pore radius, pore throat radius, pore coordination number, pore throat ratio, and specific surface area, are identified, extracted, and calculated in the scanning electron microscopy (SEM) images of ...
Respirable coal mine dust represents a serious health hazard for miners. Monitoring methods are needed that enable fractionation of dust into its primary components, and that do so in real time. Near the production face, a simple capability to monitor the coal versus mineral dust fractions would be highly valuable for tracking changes in dust sources—and supporting timely responses in terms ...
Abstract: A new method of surface roughness detection based on image processing technique is proposed in this paper. The developed vision system uses a CCD camera for scanning grayscale images from an area of the machined workpiece. This images were analysed with digital image processing system. Some new optical
Cartoon coal ore, black charcoal, graphite lump, rock stone isolated vector set. Fossil or mineral resources piles, bunch and cut pieces, ui or gui game asset, mining production, quarry or mine items. Five pieces of charcoal on a white background. Five pieces of charcoal on a white background with copy space.
Digital image processing techniques could be used to analyze coal particle size and promise a quick, inexpensive, noncontact solution for the determination of the size distribution in a coal pile.
Digital imaging technique provides an accurate measurement of particle size by processing the particle's projected area in the image and counting the digital pixels with a preset of scanning resolution [20, 2326]. The images can be taken either by a scanner or by a scanning electron microscope (Fig. ).
A quantitative analysis of the porosity, pore size distribution, and fractal dimensions of pores is significant for studying the pore structure characteristics of coal. This study utilized 12 anthracite coal samples from the Sihe mining area to explore the pore structure characteristics of the coal therein. Hundred randomly selected points on each sliced coal sample were imaged via scanning ...
Measured particle area (A) from image analysis is converted to an equivalent particle diameter (D e, D e = 2 × √ A∕ ), which is then used to calculate sphere volumes and determine their mass ...
Currently, there is little research on realtime monitoring methods for coal dry screening. Liao [] developed a new online automatic optical inspection system (OAOIS) applying digital image processing to measure the coarse particle size [] demonstrated the inconsistencies of lengthbased separation by mechanical sieving using standard sieves and developed a user ...
Full size image. Grayscale processing of coal and gangue images. ... The experimental results show that 9 × 9 Gaussian filter is the most suitable for processing the image of coal.
In this paper, an image analysis method using MATLAB is proposed to measure fragment size distribution of coal fragments. The acquisition setup, analysis step and coding process for fragment size distribution measurement by digital imaging processing are introduced in detail.
Image Binarization . To extract and obtain the pore information and distribution in the image, we first binarized the SEM images of the coal sample and transformed them into a binary image,
Top coal caving simulation test: put 300 mm crushed coal in the funnel, and then tiled 500 mm crushed gangues, the detector height was reduced to 200 mm from the platform bottom plate, the ...
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