摘要
矿井自然发火是影响矿井安全生产的重大危险源之一。当出现自然发火征兆时,对遗煤自然发火程度进行精准辨识,有助于及时采取科学有效的防灭火措施,确保矿井安全生产。首先采集煤样进行程序升温实验,对实验的结果进行标准化处理,消除量纲的影响;然后使用相关性分析的方法分析各气体与温度之间、以及各气体之间的相关性;最后综合使用主成分分析和主成分回归的方法构建了对数型数学模型。该模型将实验生成的气体作为自变量,煤温作为因变量,可以用于辨识煤的自然发火程度。
Spontaneous combustion in coal mine is one of the main hazard sources that affect mine safety production. When there is a sign of spontaneous combustion, accurate identification of the degree of spontaneous combustion is helpful to take scientific and effective fire-fighting measures in time to ensure the safe production of the mine. Firstly, temperature programmed experiment is performed with collected coal samples, and the results of the experiment are standardized to eliminate the influence of dimension. Then, correlation analysis is used to analyze the correlation between gas indexes and temperature, as well as between gas indexes. Finally, a logarithmic mathematical model is constructed by using principal component analysis and principal component regression. The experimental gas is taken as independent variable and coal temperature as dependent variable in this model, which can be used to identify the spontaneous combustion degree of coal.
作者
杜斌
DU Bin(China Coal Research Institute,Beijing 100013,China;China Coal Technology&Engineering Group Shenyang Research Institute,Fushun 113122,China;State Key Laboratory of Coal Mine Safety Technology,Fushun 113122,China)
出处
《煤矿安全》
CAS
北大核心
2021年第1期189-193,共5页
Safety in Coal Mines
关键词
主成分分析
回归
自然发火
氧化程度
定量评价
principal component analysis
regression
spontaneous combustion
oxidation degree
quantitative estimation
