E3S Web Conf.
Volume 8, 2016Mineral Engineering Conference MEC2016
|Number of page(s)||10|
|Published online||16 September 2016|
Multidimensional statistical and visualization methods in description of grained materials
1 AGH - University of Science and Technology, Faculty of Mining and Geoengineering, Department of Environmental Engineering and Mineral Processing Cracow, Poland
2 AGH – University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Computer Science
a Corresponding author: firstname.lastname@example.org
As far as coal is concerned, the data are usually considered to be independent variables, and such an approach is not always appropriate. Therefore, the paper focuses on the multidimensional analysis, which allows to conduct the comparisons of the coal types and to determine the relationship between their specific characteristics. The paper presents an analysis of variance and an observational tunnels method, which enabled to examine the differences between three types of coals: 31, 34.2 and 35. In order to achieve the experimental aim, a number of laboratory analyses of coal were carried out. Such parameters as combustion heat, ash contents, sulfur contents, volatile parts contents and analytical moisture were determined for samples, including the mass and density of these fractions, so seven various features were specified for each coal. The results of the observational tunnels method and the ANOVA application confirmed that the accepted parameters were sufficient for the proper identification of the coal sample origin and their size fractions. As a result of ANOVA, the volatile matter content was determined as the feature on which identification of the coal types can be based, regardless of size fraction. However, the remaining parameters affect the study groups randomly. While applying the methods of multidimensional analysis, some limitations were encountered that indicated the complex structure of the grained material.
© Owned by the authors, published by EDP Sciences, 2016
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