聚类分析和因子分析对深井软岩软化系数的预测

为了预测深井软岩巷道开挖后不同水环境下的岩石软化系数,将深井软岩软化系数定义为含水率的函数,利用聚类分析和因子分析理论研究影响其软化系数的因子之间的相关性,并建立分析模型。结果表明：深井软岩的干密度、颗粒密度、孔隙率对其软化系数的影响具有共性,可归为一类因子;含水率和黏土矿物质量分数分别为一类。文中提出的分析模型与实验结果相吻合,对矿山深井巷道施工和支护设计具有一定的指导意义。

Prediction of cluster analysis and factor analysis to softening coefficients of soft rocks in deep mine

Aimed at predicting the softening coefficients lowing an excavation in deep soft rock roadways, this paper cients of rocks as a function of uniaxial compressive strength of rocks in different water environment fol- is focused on defining the softening coeffi- with different moisture and using the cluster analysis and factor analysis to study the relevance in the factors influencing the softening coefficients. The result shows that the dry density, grain density and porosity come under the same class of factors due to their same contribution to the softening coefficients of rocks and the moisture content and clay mineral content are classified as an independent class respectively. The analytical model producing calculation re- sults consistent with the experimental ones could serve as a guide for the construction and support design in deep soft rock roadways.