煤自燃预测定量指标的数学统计分析

Mathematical statistical analysis of quantitative indicatorsfor coal spontaneous combustion prediction

为了提高煤早期自燃预测预报的准确度,选取8家矿井煤样进行程序升温—气相色谱实验,通过分析煤自燃氧化过程的气体产物与温度之间的关系,准确得到煤自燃临界温度,找出适合煤自燃各阶段的指标气体。在此基础上,综合运用灰色关联度理论和斯皮尔曼相关性理论对煤自燃指标气体进行优选。结果发现,运用灰色关联度和斯皮尔曼方法对获取的定量预测指标进行相关性分析时,Graham指数各氧化阶段相关性最高,其次是CO_(2)/CO,对精准预测煤自然发火有较大的应用价值。

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 CO_(2)/CO,which has great application value for accurate prediction of coal spontaneous combustion.