It offers a considerable number of machine learning models such as support vector machines for classification and regression, hidden Markov models, multiple kernel learning, linear discriminant ...
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A fuzzy method for selecting underground coal mining method considering mechanization criteria. Kemal Özfırat. 2012, Journal of Mining Science.
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coal classification, any of various ways in which coal is grouped. Most classifications are based on the results of chemical analyses and physical tests, but some are more empirical in nature. Coal classifications are important because they provide valuable information to commercial users (, for power generation and coke manufacturing) and to researchers studying the origin of coal.
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Coalfired boilers are used in many industrial plants to provide and direct heat and steam sources to the machines that need to be used. Coal fired boilers are commonly used in industries such as textile, garment, food, soft drinks, alcohol, seafood, fish sauce, soy sauce, etc.
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Coal cutting machines are used for providing an undercut, or overcut or shear cut in a. coal seam. A coal cutting machine were used to make a groove (also called cut) 1m to 2,5 m in. depth and 125 mm to 175 mm in height at a coal face. The cut was made across the. whole width of a gallery in the case of bord and pillar headways and across the ...
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1. Introduction. In coal production, the raw coal mined directly from coal mines contains a lot of gangue, which contains a lot of heavy metals, and affects the calorific value of coal, causing serious pollution to the environment [].Therefore, it is essential to separate coal and gangue to make them play their respective roles [2,3].As an important part of the coal industry, coal gangue ...
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Only a slope stability coefficient of can guarantee to maximize the recovered retained coal resources while maintaining safety. Substituting FS = into Eq. ( 12) yields m as the ...
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Download scientific diagram | a Cutting action of continuous miner machine; b gradual wear of conical picks; c 14 CM series continuous miner machine (courtesy: joyglobal) from publication ...
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The classification of rock and coal on ribs has been applied for shearer horizon control at longwall mining face. It provides the information for the shearer to adjust the cutting drums. An automated shearer will cut the coal and stay inseam without the need for human intervention . Besides knowing the shearer's location, direction, and ...
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Fully mechanized LTCC mining method is a good recovery for ultrathick coal seams especially seams above 7 m. Developing technologies increases the recovery rate for LTCC more than working in slice panels (Wang et al. 2015).Different drawing alternatives effect the recovery rate of the top coal as also outlined by Wang et al. (), and it proposed that one cutting and one drawing working ...
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Efficient and accurate classification of the microseismic data obtained in coal mine production is of great significance for the guidance of coal mine production safety, disaster prevention and early warning. In the early stage, the classification of microseismic events relies on human experiences, which is not only inefficient but also often causes some misclassifications. In recent years ...
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1. Column and knee type milling machines. Column and knee type mill is a common type of milling machine for general purpose. Column, spindle, cutter, table, knee, base are the basic parts of the vertical and horizontal type mills. On column and knee type milling machines, a vertical column is attached to the bed that contains all gear drives ...
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Identification of coal and gangue is one of the important problems in the coal industry. To improve the accuracy of coal gangue identification in the coal mining process, a coal gangue identification method based on histogram of oriented gradient (HOG) combined with local binary pattern (LBP) features and improved support vector machine (SVM) was proposed. First, according to the actual ...
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worked by a coalcutting machine. Sekula et al. (1991) and Krupa et al. (1993a,b, 1994) ... In this paper the development of a new rippability classification system for coal measure rock based on ...
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To solve the problem of difficult to sort coal and gangue quickly and accurately caused by the fast running speed of belt, the different shapes and sizes of gangue and so on, an online flexible ...
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The machine cut 150 m 2 in six months, at about three times the cost of conventional mining. This was viewed as an important first step in hard rock cutting, particularly as it enabled separate mining of a narrow reef band and waste, allowing for waste to be sorted and moved into the back area instead of incurring the costs of being transported ...
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The first working face in the southwest wing of the first panel area of the Jinjitan Coal Mine is 122up108. The coal seam's thickness ranges from to m, with an average of m. The coal seam's burial depth ranges from 200 to 305 m, and its average mining depth is 246 m.
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The extraction of coal results from the interaction between the cutting tool and the coal Many studies have been conducted to understand the mechanism of For maximum productivity and ecocoal for a better tool design (1,2,3,4,5). which it has to operate. nomy the coal extraction machine must be designed to suit the conditions under This leads to ...
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Least squares vector machine has a strong ability to classify, so the use of least squares vector machine to achieve coal gangue identification, and build coal gangue identification model.
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The toplevel architecture of 5G+ intelligent coal mine systems combines intelligent applications such as autonomous intelligent mining, humanmachine collaborative rapid tunneling, unmanned auxiliary transportation, closedloop safety control, lean collaborative operation, and intelligent ecology.
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Among them, clustering models can cluster coal samples into several clusterings only by coal spectra; classification models can classify coal with labels into different categories; and the regression model can give quantitative prediction results for proximate analysis indicators.
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The reason why machine learning can handle these variations and classify them as one group is because of their generalisation capability (Kawaguchi et al., 2017). Machine learning aims to abstract the training samples in a statistical manner to incorporate the dynamic changes of these statistical features.
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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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