Gao Dong, Guo Liwen, Wang Fusheng, Zhang Zhiming
North China University of Science and Technology, Tangshan, Hebei Province 063210, China.
Mining Development and Safety Technology Key Laboratory of Hebei Province, Tangshan, Hebei Province 063009, China.
ACS Omega. 2021 Mar 5;6(10):6736-6746. doi: 10.1021/acsomega.0c05736. eCollection 2021 Mar 16.
The correlation between the spontaneous combustion tendency of coal and its properties are of great importance for safety issues, environmental concerns, and economic problems. In this study, the relationship between multiple parameters, different from the previous single parameter, and the spontaneous combustion tendency was analyzed. The comprehensive judgment index (CJI), which indicates the tendency of coal spontaneous combustion, was obtained for samples collected from different mines. The CJI was measured by the cross-point temperature and had a negative correlation with the spontaneous combustion tendency. Physical pore structures and chemical functional groups were characterized based on cryogenic nitrogen adsorption and Fourier transform infrared spectroscopy measurements, respectively. For analyzing the effect of coal properties on the spontaneous combustion tendency, the grey relational grade was determined by the grey relational analysis between the CJI and the pore structures and functional groups of coal. The grey relational grade of the benzene substituent with CJI had a maximum of 0.8642, and the macropores had the minimum, 0.4169. The higher the gray relational grade was, the more relevant the spontaneous combustion tendency was, indicating that the benzene substituent was the most relevant. To better predict the spontaneous combustion tendency, the average pore diameter, hydroxyl, methyl, methylene, and benzene substituent with a high grey relational grade were selected. Finally, the multiple regression prediction model of CJI was established. The squared coefficient, significance level, -distribution, -distribution, collinearity diagnosis, and residual distribution of the model met the requirements. In addition, two coal samples were selected to verify the spontaneous combustion tendency model. The relative errors between the predicted CJI value and the experimental CJI value were 1.42 and 4.25%, respectively. These small relative errors verified the reasonableness and validity of the prediction model.
煤的自燃倾向性与其性质之间的相关性对于安全问题、环境问题和经济问题都非常重要。在本研究中，分析了多个参数（不同于以往的单一参数）与自燃倾向性之间的关系。针对从不同煤矿采集的样品，获得了表示煤自燃倾向的综合判断指标（CJI）。CJI通过交叉点温度测量，与自燃倾向性呈负相关。分别基于低温氮吸附和傅里叶变换红外光谱测量对物理孔隙结构和化学官能团进行了表征。为了分析煤性质对自燃倾向性的影响，通过CJI与煤的孔隙结构和官能团之间的灰色关联分析确定了灰色关联度。苯取代基与CJI的灰色关联度最大，为0.8642，大孔的灰色关联度最小，为0.4169。灰色关联度越高，与自燃倾向性的相关性越强，表明苯取代基相关性最强。为了更好地预测自燃倾向性，选择了平均孔径、羟基、甲基、亚甲基和灰色关联度高的苯取代基。最后，建立了CJI的多元回归预测模型。模型的平方系数、显著性水平、F分布、t分布、共线性诊断和残差分布均满足要求。此外，选择了两个煤样对自燃倾向模型进行验证。预测的CJI值与实验CJI值之间的相对误差分别为1.42%和4.25%。这些较小的相对误差验证了预测模型的合理性和有效性。
