Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "Niedoba, T." wg kryterium: Autor


Wyświetlanie 1-5 z 5
Tytuł:
Statistical analysis of the relationship between particle size and particle density of raw coal
Autorzy:
Niedoba, T.
Powiązania:
https://bibliotekanauki.pl/articles/951860.pdf
Data publikacji:
2013
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
approximation
coal
multidimensional analysis
statistical tests
particle size
density
Opis:
The paper presents a multidimensional analysis of mineral processing feeds consisting of different amounts of different size and density fractions. The considered feed was coal which was screened into size fractions which were subsequently separated into density fractions and their weights determined. The feed material was characterized with commonly used size and density frequency and cumulative distribution plots and next approximated with the Weibull (size) and logistic (density) mathe-matical functions. Having the contribution of each particle size and density fraction in the feed a two–dimensional analysis of the feed size/density properties was performed using two methods. The first one is based on the best chosen cumulative frequency function for two random variables and the second uses the so–called Morgenstern family functions. In the paper the undependability of the particles size and density was investigated using statistical approach based on the so–called Χ2 test, and the correlation between these parameters using the so–called F–Snedecor statistical test. In both cases it was found that particles size and density of the investigated coal particles were dependent what means that with growth of particle size its density grew too and there was correlation between them regardless of significance level assumed for the analysis.
Źródło:
Physicochemical Problems of Mineral Processing; 2013, 49, 1; 175-188
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-parameter data visualization by means of principal component analysis (PCA) in qualitative evaluation of various coal types
Autorzy:
Niedoba, T.
Powiązania:
https://bibliotekanauki.pl/articles/109595.pdf
Data publikacji:
2014
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
principal component analysis
PCA
multi-parameter data visualization
coal
identification of data
covariance matrix
pattern recognition
Opis:
Multi-parameter data visualization methods are a modern tool allowing to classify some analyzed objects. When it comes to grained materials, e.g. coal, many characteristics have an influence on the material quality. Besides the most obvious features like particle size, particle density or ash contents, coal has many other qualities which show significant differences between the studied types of material. The paper presents the possibility of applying visualization techniques for coal type identification and determination of significant differences between various types of coal. The Principal Component Analysis was applied to achieve this purpose. Three types of coal 31, 34.2 and 35 (according to Polish classification of coal types) were investigated, which were initially screened on sieves and subsequently divided into density fractions. Next, each size-density fraction was analyzed chemically to obtain other characteristics. It was pointed out that the applied methodology allowed to identify certain coal types efficiently, which makes it useful as a qualitative criterion for grained materials. However, it was impossible to provide such identification based on contrastive comparisons of all three types of coal. The presented methodology is a new way of analyzing data concerning widely understood mineral processing.
Źródło:
Physicochemical Problems of Mineral Processing; 2014, 50, 2; 575-589
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of the observational tunnels method to select a set of features sufficient to identify a type of coal
Autorzy:
Jamroz, D.
Niedoba, T.
Powiązania:
https://bibliotekanauki.pl/articles/109317.pdf
Data publikacji:
2014
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
multidimensional statistical analysis
observational tunnels method
coal
image visualization
energetic materials
Opis:
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.
Źródło:
Physicochemical Problems of Mineral Processing; 2014, 50, 1; 185-202
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparison of selected methods of multi-parameter data visualization used for classification of coals
Autorzy:
Jamroz, D.
Niedoba, T.
Powiązania:
https://bibliotekanauki.pl/articles/110329.pdf
Data publikacji:
2015
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
multidimensional visualization
observational tunnels method
multidimensional scaling
MDS
principal component analysis
PCA
relevance maps
autoassociative neural networks
Kohonen maps
parallel coordinates method
grained material
coal
Opis:
Methods of multi-parameter data visualization through the transformation of multidimensional space into two-dimensional one allow to present multidimensional data on computer screen, thus making it possible to conduct a qualitative analysis of this data in the most natural way for human – by a sense of sight. In the paper a comparison was made to show the efficiency of selected seven methods of multidimensional visualization and further, to analyze data describing various coal type samples. Each of the methods was verified by checking how precisely a coal type can be classified when a given method is applied. For this purpose, a special criterion was designed to allow an evaluation of the results obtained by means of each of these methods. Detailed information included presentation of methods, elaborated algorithms, accepted parameters for best results as well the results. The framework for the comparison of the analyzed multi-parameter visualization methods includes: observational tunnels method multidimensional scaling MDS, principal component analysis PCA, relevance maps, autoassociative neural networks, Kohonen maps and parallel coordinates method.
Źródło:
Physicochemical Problems of Mineral Processing; 2015, 51, 2; 769-784
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Accuracy of separation parameters resulting from errors of chemical analysis, experimental results and data approximation
Autorzy:
Foszcz, D.
Duchnowska, M.
Niedoba, T.
Tumidajski, T.
Powiązania:
https://bibliotekanauki.pl/articles/109371.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
upgrading curve
approximation
copper ore
flotation
selectivity
Opis:
Accuracy of determination of different separation parameters and selectivity indicators depends on the error of chemical analysis of feed and separation products as well as experimental and approximation errors. In this paper different selectivity parameters were considered which formulae was based on the content of useful component in the feed, concentrate and tailing. It was shown that the impact of chemical analysis on the selectivity parameters was small and the error determined by means of partial derivative approach for a copper ore upgraded by flotation was negligible. Also experimental errors were found to be insignificant. The largest errors occurred for approximation of the upgrading data with inadequately selected selectivity indicators.
Źródło:
Physicochemical Problems of Mineral Processing; 2016, 52, 1; 98-111
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies