The noncontact digital image processing technology determines the deformation of the sample according to the deformation amount of the image taken when the coal deforms. Using computer to collect and process data is a noncontact and noninterfering deformation measurement technology that does not interfere with the deformation of the sample.
Abstract nearest neighbour algorithm, and convex shell method to achieve preliminary segmentation, merge small pieces with large pieces, and split adhered particles, respectively. Comparing the automated segmentation using this method with manual segmentation, it is found that the results are comparable.
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.
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.
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 ...
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.
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.
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 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 ...
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.
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 ...
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 ...
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 ...
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 ...
The whole pipeline of LIST consists of three processes: (1) morphology recognition; (2) size measurement; and (3) scalebar and text recognition for scale conversion. The first process is to determine the morphology of the nanoparticles in the input SEM image. We then perform a size measurement process, depending on the input morphology type.
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, ...
Coal is a black or brownishblack sedimentary rock that can be burned for fuel and used to generate is composed mostly of carbon and hydrocarbons, which contain energy that can be released through combustion (burning). Coal is the largest source of energy for generating electricity in the world, and the most abundant fossil fuel in the United States.
Two hundred images of coal piles comprised of coal sized above 3 mm were captured. Over 100 kg of coal were sampled and sieved manually into five size fractions: 36, 613, 1325, 2550, and 50100 mm. The size of the image was 1024 × 768 pixels and the imaged area was 18 × cm.
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 ...
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.
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 ...
Besides analyzing the coal, a coal quality manager system should automatically calculate: Heating Value (kcal/kg, kJ/kg or BTU/lb) Lbs SO2 per million BTU. Volatile Matter. Fixed Carbon. Ash Fusion Temperature (based on customer specific empirical relations) Knowing these measurements in realtime enables coal producers to control sorting and ...
By image processing, Yang [12] measured the particle size distribution of lump coal with a size range of ∼ 20 mm, and compared the statistical distribution with fractal distribution function and artificial sieving results, providing a novel and effective method for the particle size distribution measurement in the study of coal failure ...
Introduction In the coal preparation process, particle size distribution (PSD) is very important for determining the load of the classification equipment and the separation effects of particles with extensive classes (Liu et al., 2014).
Abstract We developed an imaging technique for inspecting the inside of coalfired boilers during operation by using a visiblelight camera, which has a higher spatial resolution and depth of field than midinfrared image sensor camera systems commonly used for imaging the inside of boilers. Two main problems are associated with the use of a visiblelight camera: the low light transmittance of ...
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.
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 ...
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 ...
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
Laser particle analyzer and image analysis were used to measure the particle size distribution of 6 coal samples with the size range of 1 ∼ 2 mm. Based on obtaining the size distribution, the average diameter was calculated. Then the diffusion coefficient was calculated by using the average diameter obtained by different methods.
Two image processing procedures were developed to ... respirable coal mine dust; particle size; mineral composition 1. Introduction In the coal mining industry, respirable coal mine dust (RCMD) is generated during ... Two 6 26 mm pieces were cut from each sample. One piece was cut from the edge, and the other piece was from near the center of ...
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 ...
Large foreign object transporting by coal mine conveyor belt may lead to production safety hazards. To reduce safety accidents during coal mining, a large foreign object detection method based on machine vision is proposed in this paper. An adaptive weighted multiscale Retinex (MSR) image enhancement algorithm is proposed to improve the captured image quality of the belt conveyor line. An ...
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 ...
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 ...
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