Multidimensional Labyrinth – Multidimensional Virtual Reality

Coal as energetic raw material features by many parameters determining its quality. In classification of coal types there are many of them with typical division of energetic, semi-coking and coking coal. The data concerning coal are usually treated as independent values while this kind of approach is not always right. Authors proposed new solutions in this aspect and performed the multidimensional analysis of three selected types of coal featuring by various properties which originated from three various hard coal mines located in Upper Silesia Region. The object of the research was so-called raw coal which was not processed before. For each type of coal the detailed statistical analysis of seven chosen properties of coal was performed. To perform adequate and complete statistical analysis it is necessary to analyze the chosen properties of coal together in multidimensional way. It was decided to apply new and modern visualizing methods of multidimensional data which were observational tunnels method and parallel coordinates method. The applied methods allowed to obtain visualization of seven-dimensional data describing coal. By means of these visualizations it was possible to observe the significant division of the features space between researched types of coal. These methods allowed to look at the investigated data from various perspectives and make possible to determine significant differences between researched materials. For the investigated coals such differences were determined clearly what proved that by means of these methods it is possible to successfully identify type of coal as well to analyze in details its individual properties and identify, for example, particle size fraction etc. The obtained results are innovative and are the basis for more detailed researches taking into consideration also other coal properties, including its structure and texture. This methodology can be also applied successfully for other types of raw materials, like ores.

Section: General Principles Of Visualization Of Multidimensional Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

unclassified

See 1 more Smart Citation

Visualization of Multidimensional Data in Purpose of Qualitative Classification of Various Types of Coal / Wizualizacja Wielowymiarowych Danych W Celu Klasyfikacji Jakościowej Różnych Typów Węgla

Niedoba¹,

Jamroz²

2013

“…Among many methods, the following ones can be selected: grand-tour method (Asimov, 1985;Cook et al, 1995), the method of principal component analysis (Li et al, 2000), use of neural networks for data visualization (Aldrich, 1998;Jain & Mao, 1992;Kraaijveld et al, 1995;Tadeusiewicz, 1993), parallel coordinates method (Chatterjee et al, 1993;Chou et al, 1999;Gennings et al, 1999;Inselberg, 1985), star graph method (Sobol & Klein, 1989), multidimensional scaling (Kim et al, 2000), scatter-plot matrices method (Cleveland, 1984), relevance maps method (Assa et al, 1999). Visualization of multidimensional solids is also possible (Jamróz, 2009). The observational tunnels method (Jamróz, 2001) makes it possible to achieve an external view of the observed multidimensional sets of points using tunnel radius, introduced by the author (Jamróz, 2014a;b;c;Jamróz & Niedoba, 2013;2014;Niedoba, 2013).…”

Section: Introductionmentioning

confidence: 99%

Application of Multidimensional Data Visualization by Means of Self-Organizing Kohonen Maps to Evaluate Classification Possibilities of Various Coal Types / Zastosowanie Wizualizacji Wielowymiarowych Danych Za Pomocą Sieci Kohonena Do Oceny Możliwości Klasyfikacji Różnych Typów Węgla

Jamroz¹,

Niedoba²

2015

Multidimensional data visualization methods are a modern tool allowing to classify some analysed objects. In the case of grained materials e.g. coal, many characteristics have an influence on the material quality. The paper presents the possibility of applying visualization techniques for coal type identification and determination of significant differences between various types of coal. To achieve this purpose, the method of Kohonen maps was applied by means of which three types of coal -31, 34.2 and 35 (according to Polish classification of coal types) were investigated. It was stated that the applied methodology allows to identify certain coal types efficiently and can be used as a qualitative criterion for grained materials.Keywords: Kohonen maps, grained material analysis, coal, multidimensional data, multidimensional visualization methods Metody wizualizacji wielowymiarowych danych są nowoczesnym narzędziem umożliwającym klasyfikację analizowanych obiektów, którymi mogą być różnego typu dane opisujące wybrane zjawisko lub materiał. W przypadku materiałów uziarnionych, jakim jest np. węgiel, wiele cech ma wpływ na jakość materiału, tj. np. gęstość, wielkość ziaren, ciepło spalania, zawartość popiołu, zawartość siarki itp. Na potrzeby artykułu przeprowadzono rozdział węgli z trzech wybranych kopalni węgla kamiennego, zlokalizowanych w Górnośląskim Okręgu Przemysłowym. Każda z tych kopalni pracuje na innego typu węglu. W tym przypadku były to węgle o typach 31, 34.2 oraz 35 (według polskiej klasyfikacji typów węgla). Najpierw, materiał został podzielony na klasy ziarnowe a następnie za pomocą rozdziale w cieczy ciężkiej (roztwór chlorku cynku) na frakcje gęstościowe. Dla tak przygotowanego materiału przeprowadzono następnie analizy chemiczne mające na celu określenie takich parametrów, jak zawartość siarki, zawartość popiołu, zawartość części lotnych, ciepło spalania oraz wilgotność analityczną. W ten sposób, dla każdej klaso-frakcji uzyskano bogate charakterystyki badanego materiału. Nasuwa się więc pytanie, czy możliwa jest identyfikacja typu węgla za pomocą dostępnych danych. W tym celu zastosowano

“…Evaluation of the suitability of coal for gasification should therefore be carried out on a multidimensional basis using multidimensional distribution features and statistics (Jamróz, 2009;2014;Jamróz & Niedoba, 2014;Niedoba & Jamróz, 2013;Niedoba, 2013;2014;Tumidajski, 1997). It is only natural that the analysis of multidimensional features and statistics begins with an analysis of the densitometry composition of grinded coal and is extended further based on the coal characteristics, especially the contents of the components and reactions to the processing stages.…”

Section: Introductionmentioning

confidence: 99%

Multi-Criteria Evaluation of Coal Properties in Terms of Gasification

Marciniak-Kowalska¹,

Niedoba²,

Surowiak³

et al. 2014

This paper presents a comparative analysis of two types of coal taken from the ZG Janina and ZG Wieczorek coalmines. The aim of this study has been to analyze the suitability of the coal in the context of the gasification process. The types of coal vary considerably in terms of their characteristics. Each of them was subjected to treatment in a ten-ringed annular jig. A particle size of 0-18 mm constituted the feed. The separated coal was divided into five layers, each of them containing material from two additional annular jigs. Analysis of their characteristics was carried out for each of the five layers and for both types of coal obtained, taking into account both their physicochemical properties as well as chemical ones. Each of these characteristics was then presented in three-dimensional surface diagrams, where the ordinate (or Y-axis) and abscissa (X-axis) was the particle size and height in which the material ended up in the jig (expressed as a percentage of the total height of the device). On the basis of observations, it was found that the types of coal have different potential for gasification, although both types are within the limits specified on the basis of previous studies. A correlation analysis between particle size and remaining characteristics of coal was carried out for each of the layers, allowing to determine which of the studied characteristics induced changes significant from the point of view of the coal gasification process. The entire research and observation was supported by conclusions and findings, which shall form the basis for further, in-depth analysis of coal.