Focusing on the precise prediction of coal spontaneous combustion (CSC), temperature-programmed experiment was conducted to identify the coal spontaneous combustion indexes. Based on a conception that there should be no significant difference between the coal temperatures determined by different coal spontaneous combustion indexes with sufficient accuracy, an approach for evaluating the coal spontaneous combustion index by statistical analysis was developed. After mining data screening by the coefficient of variation (Cv), the arrays of coal temperature determined by different indexes were calculated with the curve fitting. The Kruskal-Wallis test was employed to analyze the differences between the arrays of coal temperature. Finally, the weighted grey relational analysis method was used to optimize the coal spontaneous combustion indexes. The results show that the production of gaseous compounds is positively correlated with coal temperature. In this case, O2/CO2 and CO2/CO were selected as the primary indexes, and CO/CH4 was used as the alternative index of coal at low-temperature stage (≤ 80 °C). The detecting of C2H4 and C2H6 were the confirmation indexes when the coal temperature reaches 90 °C ~ 100 °C. It could provide a reference to the determination of grading index of coal spontaneous combustion during mining and utilization.
Keywords: Coal spontaneous combustion; Coefficient of variation; Index; Kruskal–Wallis test; Weighted grey relational analysis.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.