Your browser doesn't support javascript.
loading
Selection of longwall shearers based on the results of research on the mechanical properties of coal.
Bialy, Witold; Prostanski, Dariusz; Boloz, Lukasz.
Afiliação
  • Bialy W; KOMAG Institute of Mining Technology, Pszczynska 37, 44-101, Gliwice, Poland.
  • Prostanski D; KOMAG Institute of Mining Technology, Pszczynska 37, 44-101, Gliwice, Poland.
  • Boloz L; AGH University of Krakow, A. Mickiewicza Av. 30, 30-059, Krakow, Poland. boloz@agh.edu.pl.
Sci Rep ; 14(1): 18606, 2024 Aug 10.
Article em En | MEDLINE | ID: mdl-39127759
ABSTRACT
The proper selection of cutting longwall winning machines for specific mining and geological conditions requires the development of an appropriate algorithm. The appropriate selection of a machine (shearer) is closely related to acquiring a high concentration of exploitation from the given longwall. That is indispensable, especially taking into consideration the growing cost of mining, as well as the depth of coal seams. In this article, an algorithm showing the selection of longwall winning machines has been presented. The algorithm has been created based on results of research on the processed coal's mechanical properties. Analysis of the mining process, especially in difficult conditions, shows that in order to define a drum longwall shearer's range of usage, the coal's properties which have a significant impact on the mining process must be determined. The above also influences the technique, technology and effectiveness of mining-they impact the effectiveness of the winning machines. In connection to this, the cutting heads should be chosen and designed based on those factors, as well as any performance forecasts. As representative values the following have been chosen workability index (WUB), resistance to unidirectional compression (Rc), and energy consumption of the mining process (TE).
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article