The platform is composed of five modules, including module of coal seam and fault, module of laneway aided design and analysis, module of general ground surface situation and working condition, module of auxiliary view and layer managements, and module of dynamic visualization (an independent system). Download : Download fullsize image;
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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 ...
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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.
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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 ...
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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 ...
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This paper focuses on the size distribution measurement of coal fragments by digital imaging processing. The fast and precise measurement of coal fragments, which is important to understand...
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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. ).
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Table 1 lists the physical parameters of the pulverized coal and air which are required for numerical calculation (The temperature is set as 71 °C which is just consistent with that of pipe flow during inline experiments). In this calculation, the range of the pulverized coal size is 1200 μm, and the volume fraction is from % to 1%. Therefore, ultrasonic frequencies of 40 kHz and 200 ...
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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 ...
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The particle sizes of coal and gangue are all distributed in the range of 13150 mm. To study the difference between coal and gangue with different particle sizes, coal and gangue are divided into two types according to their grain sizes, one is 1325 mm, and the other is 25150 mm. Some images are shown in figure 2.
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As a re sult, it is possible to create online noncontact, fully automated machine vision systems for particle size measurement, which facilitates the evaluation and optimization of particle mining and processing processes. ∗ Corresponding author. Tel.: +; Email address: [email protected] © 2022 The Authors ...
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open access Abstract An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of Keywords Pulverized coal Image segmentation Deep learning Particle size analysis 1. Introduction Air pollution caused by coal combustion has caused widespread concern.
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Coal is heterogeneous in nature, and thus the characterization of coal is essential before its use for a specific purpose. Thus, the current study aims to develop a machine vision system for automated coal characterizations. The model was calibrated using 80 image samples that are captured for different coal samples in different angles. All the images were captured in RGB color space and ...
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Coal Based on Image Processing and SEM Technology Mingyue Jia 1, Wenhui Huang 1,2, * and Yuan Li 1 1 Key Laboratory for Marine Reservoir Evolut ion and Hydrocarbon Abundance Mechanism,
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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.
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Experimental results show that the combined high speed imaging and image processing technique has provided an effective means for measuring and quantifying the characteristics of single coal ...
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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
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A direct bubble size measurement technique which employs a device to collect and expose bubbles has been revived. ... settings resulted in a field of view of m by m for image collection and a square of m side for image processing. 430 F. Chen et at. To illustrate the results two Figures are included: Figure 3 compares bubble ...
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Online intelligent recognition of coal and gangue is an important aspect of coal mine intelligent development. Current research focuses more on improving recognition accuracy through optimizing image processing algorithms, but there is limited research on the characteristics of coal gangue materials themselves, particularly the comparative analysis of their appearance in images under different ...
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Particle size is an important physicochemical parameter of coal. The accurate measurement of particle size distribution (PSD) of coal samples is significant to both scientific research and engineering, such as coal combustion [15], coal chemical industry [69], adsorption and desorption [1012], and coal and gas outburst [13, 14].
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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. •
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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, ...
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Image processing Particle size distribution Diffusion coefficient Laser particle analyzer Coal particles 1. Introduction Coal particles are mixed by various particle sizes after crushing massive coal. Coal particle is widely applied in the physical property test.
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8 mm 10% 3 mm 90% 8 mm ... Another method used to determine the degree of moisture in a material is image processing. The literature presents applications of vision methods to assess the...
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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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Yang et al. introduced a procedure to measure the size distribution of coal fragments using digital image processing [8] by analyzing still images of coal, and the obtained results were closer to the experimental results than those obtained by the size estimation method known as the fractal model.
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DOI: / Corpus ID: ; Size distribution measurement of coal fragments using digital imaging processing article{Yang2020SizeDM, title={Size distribution measurement of coal fragments using digital imaging processing}, author={Xiaohan Yang and Tingxiang Ren and Lihai Tan}, journal={Measurement}, year={2020}, volume={160}, pages={107867}, url={https://api ...
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To test our object_ script, just issue the following command: python object_ image images/example_ width Your output should look something like the following: Figure 2: Measuring the size of objects in an image using OpenCV, Python, and computer vision + image processing techniques.
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A material supplier from Belgium would like to produce limestone powder for his custome...
India is rich in various mineral resources and it is an important mineral processing market
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