Mathematical statistical analysis of quantitative indicators for coal spontaneous combustion prediction
Liang Cangchuan1, Li Ying2，3, Sang Mingming2
1. Shicaocun Coal Mine, Ningxia Coal Industry Company, National Energy Group, Ningxia 751400, China; 2. School of Mining and Engineering, North China University of Science and Technology, Tangshan 063210, China; 3, Hebei Energy Vocational and Technical College, Tangshan, Tangshan 063004, China
Abstract： In order to improve the accuracy of prediction and prediction of early spontaneous combustion of coal, 8 coal samples were selected for temperature programmed gas chromatography experiment. By analyzing the relationship between gas products and temperature in the oxidation process of coal spontaneous combustion, the critical temperature of coal spontaneous combustion was accurately obtained, and the index gas suitable for each stage of coal spontaneous combustion was found. On this basis, the grey correlation theory and Spearman correlation theory are used to optimize the coal spontaneous combustion index gas. The results show that when the grey correlation degree and Spearman method are used to analyze the correlation of the obtained quantitative prediction indexes, the correlation of Graham index at each oxidation stage is the highest, followed by CO2/CO, which has great application value for accurate prediction of coal spontaneous combustion.
