Coal and CBM Test Institute of Xinjiang Uyger Autonomous Region

煤灰熔融性是决定锅炉或气化炉顺利运行的重要指标之一,其与煤灰化学成分具有很强的相关性,因而建立三塘湖煤田的煤灰熔融性温度预测模型对实现特定矿区煤灰熔融性温度控制与煤炭清洁高效利用具有重要意义。以三塘湖煤田70个煤样的煤灰成分及煤灰熔融性数据为基础,利用多元线性回归分析法,分别建立以煤灰成分、硅铝比、酸碱比为自变量以及煤灰流动性温度为因变量的四变量预测模型、十变量预测模型以及十二变量预测模型,采用逐步回归分析法对预测模型进行优化后可得到最优回归方程。随着自变量数量的增加,预测模型的相关系数逐渐提高;对最优回归方程预测模型进行回归方程可用性检验以及数值检验,表明回归方程具有较好的置信度;模型的煤灰流动性温度预测值与实验值偏差较小,表明该预测模型可起到较好的预测效果。

The fusibility of coal ash is one of the important indexes to determine the smooth operation of boiler or gas⁃ifier, and it has a strong correlation with the chemical composition of coal ash. Therefore, the establishment of thefusibility temperature prediction model of coal ash in Santanghu coalfield is of great significance to realize the tempera⁃ture control of coal ash fusibility and clean and efficient utilization of coal in specific mining areas. Based on the coalash composition and fusibility data of 70 coal samples from Santanghu coalfield, a four⁃variable prediction model, aten⁃variable prediction model and a twelve⁃variable prediction model were established by using multiple linear regres⁃sion analysis, which took coal ash composition, Si⁃Al ratio, acid⁃base ratio as independent variables and coal ashfluidity temperature as dependent variable. The stepwise regression analysis method was used to optimize the predic⁃tion model and the optimal regression equation was obtained. With the increase of the number of independent varia⁃bles, the correlation coefficient of the model increases gradually. The optimal regression equation prediction modelwas tested for usability and numerical value, and the regression equation had good confidence. The predicted value ofcoal ash fluidity temperature in the model had a small deviation from the experimental value, indicating that the pre⁃diction model could perform well in prediction.

朱金刚. 三塘湖煤田煤灰熔融性温度预测模型研究 [J]. 煤质技术, 2024, 39 (1): 74-78.

ZHU Jingang. Research on prediction model of coal ash fusibility temperature in Santanghu coalfield [ J]. CoalQuality Technology, 2024, 39 (1): 74-78.