摘要
为研究不同标志性气体对煤层自然发火可能性的准确预报,利用相关仪器对煤样进行程序升温氧化实验。以温度、CO、C2H4等10种原始数据为研究指标,通过多元统计学中的主成分分析法,对其进行主成分提取,并解释各主成分含义;命名第一主成分为"温度—CO因子",第二主成分为"CO/CO2—C2H4/C2H6因子"。从数据分析角度证明了温度、CO、CO/CO2以及C2H4/C2H6对煤层自燃倾向性的预报效果较好。在现场生产实践中,可以依据此估计煤层自燃倾向性的程度。
In order to study the accurate prediction of spontaneous combustion tendency of coal seam with different characteristics of gas,the temperature of coal sample was programmed using relevant instruments. Taking temperature,CO,C2H4 and other 10 kinds of raw dataas research index,the principal of component extraction and explanation of each principal component were made by multivariate statisticalprincipal component analysis method. The first and second principal components were named as Temperature-CO factor,CO/ CO2-C2H4/C2H6 factor respectively. The data analysis proved that the temperature,CO/ CO2,CO and C2H4/ C2H6 had good effects on predictionof coal seam spontaneous combustion tendency.
出处
《洁净煤技术》
CAS
2015年第6期119-122,共4页
Clean Coal Technology
基金
基础研究重大项目前期研究专项(2011ZX05041-003)
关键词
煤层自燃
指标气体
主成分分析
预测
coal seam spontaneous combustion
indicator gas
principal component analysis（PCA）
prediction
