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基于煤质工业分析指标的煤尘云最低着火温度预测模型构建

Modeling the Prediction of Minimum Ignition Temperature of Coal Dust Cloud Based on the Analysis Index of Coal Quality Industry

  • 摘要: 为探究利用煤质工业分析指标预测煤尘云最低着火温度的可行性,开展了煤的工业分析指标测定与煤尘云最低着火温度试验。应用主成分回归方法分析了22种煤样的工业分析指标与煤尘云最低着火温度之间的关系,结果显示:不同煤质工业分析指标与煤尘云最低着火温度之间均存在高度的相关性,提取出三大主成分因子分别为固定碳因子、水分因子、挥发分因子,并构建出回归预测模型。该预测模型的预测结果与试验所测数据相比,误差小于5%,同时由挥发分因子前的系数为负数可知,挥发分越高对应的煤尘云最低着火温度就越低,这与实际情况一致,证实了所建模型的可靠性。

     

    Abstract: In order to explore the feasibility of using the industrial analysis index to predict the minimum ignition temperature of coal dust cloud, the determination of industrial analysis index of coal and minimum ignition temperature test of coal dust cloud were carried out. This paper analyzed the relationship between the industrial analysis index of 22 kinds of coal samples and the minimum ignition temperature of coal dust cloud by using principal component regression method. The results showed that: the industrial analysis index of different coal and the minimum ignition temperature of coal dust cloud are highly correlated. The extracted three main components are "fixed carbon factor", "water factor" and "volatile factor", and the regression prediction model is constructed. Comparing the prediction results of this model with the test data, the error is less than 5%. Meanwhile, as the coefficient before the volatile factor is negative, it can be seen that the higher the volatility, the lower the minimum ignition temperature. It is consistent with the actual situation, and proves the reliability of the built model.

     

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