大同矿区煤的导热系数灰色关联分析及预测

Grey relational analysis and prediction on thermal conductivity of coal in Datong mining area

为分析煤质指标及密度对导热系数的影响作用,选取了山西大同矿区的不同煤质煤样,进行导热系数测定实验,应用灰色系统理论对导热系数与影响因素进行灰色关联分析,建立导热系数与主要影响因素的GM(1,4)灰色预测模型,进行导热系数预测。结果表明:固定碳、密度和水分是影响煤导热系数的主要因素;根据得出的主要影响因素建立的GM(1,4)预测模型平均相对误差为4.5%,预测精度较高,能够用于导热系数的预测。

In order to analyze the influence of coal quality indexes and density on thermal conductivity, the measurement ex- periments of thermal conductivity were conducted by selecting the coal samples with different coal quality from Shanxi Datong mining area. The gray system theory was applied to conduct grey relational analysis on thermal conductivity and influential factors. A GM （1,4） grey prediction model of thermal conductivity and the primary influential factors was established to predict the thermal conductivity. The results showed that the primary influential factors of coal thermal conductivity were fixed carbon, density and moisture. The average relative error of the GM（ 1,4） grey prediction model based on the primary influential factors was 4.5%. The prediction accuracy was higher, and it can be applied in the prediction of thermal conductivity.