Application of the observational tunnels method to select a set of features sufficient to identify a type of coal
 
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AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering
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AGH University of Science and Technology, Faculty of Mining and Geoengineering
CORRESPONDING AUTHOR
Dariusz Jamroz   

AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Computer Science, al. Mickiewicza 30, 30-059 Krakow, Poland
Tomasz Niedoba   

AGH University of Science and Technology, Faculty of Mining and Geoengineering, Department of Environmental Engineering and Mineral Processing, al. Mickiewicza 30, 30-059 Krakow
Publication date: 2014-01-01
 
Physicochem. Probl. Miner. Process. 2014;50(1):185–202
 
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ABSTRACT
Coal is a material which has many features deciding about its quality. Among them, the decisive ones are mainly ash contents, sulfur contents and combustion heat. The paper presents the investigation of coal characteristics of three selected coal types in the context of their energetic value. For this purpose samples were collected from three different Polish mines: coal types 31, 34.2 and 35 (Polish classification of coals). Each of these materials was separated into particle size fractions (9 fractions) and then into 8 density fractions by separation in heavy liquids. For each size-density fractions obtained in this way, chemical analyses were performed which allowed for determination of such features as combustion heat, sulfur contents, ash contents, volatile parts contents and analytical moisture. Altogether, seven dimensions of grained material characteristics were obtained. The data prepared in this way was subsequently analyzed for correlation with the purpose of determining significant relations between investigated features. It was stated that the most correlated coal features are density, combustion heat, ash contents and volatile parts contents. For multidimensional analysis and identification of coal type, the modern image visualization technique, the Observational Tunnels Method, was applied. After performing seven-dimensional analysis aimed at the proper recognition of coal type, it was decided to determine the minimum amount of random variables, which describe a particular material in order to identify its type. It was stated that the crucial coal identification parameter is “analytical moisture”. Due to existing correlation between individual features, three of them were selected for testing: analytical moisture, sulfur contents and volatile parts contents. On the basis of the obtained images, it was stated that it was possible to obtain a view with the data concerning each type of coal being located in other part of the space. Subsequently, it was checked if a similar result is possible when the parameter “volatile parts contents” is replaced with highly correlated parameters “combustion heat” and “ash contents”. In both cases the exchange of these variables did not produce good enough results. This can be explained by a different scale of empirical data making it impossible to obtain a clear multidimensional image for which all three types of coal would be located in other parts of space. However, it was proved that the modern graphical and computer methods can be successfully applied to identify the types of particulate materials.
eISSN:2084-4735
ISSN:1643-1049