基于距离判别法的采空区塌陷预测研究

A Distance Discriminant Analysis Method for the Prediction of Goaf Collapse

将距离判别法理论应用到采空区塌陷的预测中,建立了采空区塌陷预测的距离判别模型。选取覆盖层类型、覆盖层厚度、地质构造复杂程度、煤层倾角、采空区体积率、采空区距地表的垂直深度、采空区空间叠置层数等7个影响因子作为采空区塌陷预测的距离判别模型的判别因子,以某矿区采空区实测数据中选择18组数据作为训练样本,建立了采空区塌陷的距离判别函数,利用该函数对训练样本回判,其误判率为零,对另外7组预测样本逐一进行了判别分析。研究结果表明:距离判别法判别性能良好,判别准确度高,计算过程简单,可操作性强,因此该法是采空区塌陷预测中的一种非常有效的方法。

Based on distance discriminant method,a distance discriminant model for predicting mining collapse is established.The influential factors such as overburden layer type,overburden layer thickness,the complex degree of geologic structure,the inclination angle of coal bed,volume rate of the cavity region,the vertical goaf depth from the surface and space superposition layer of the goaf region as the discriminant factors of the model.The training samples are tested by the established model,and the correct rate is 100%.Furthermore,the seven samples of waiting forecast sample are predicted by the Distance discriminant model.The results show that the forecast results are fully consistent with the actual situation.The Distance discriminant model can accurately forecast the goaf collapse under different conditions.It provides a new way for predicting mining induced goaf collapse,has good practicality and effectiveness.