矿山井巷掘进爆破参数优化设计及其三维可视化研究

Study on the Optimization Design of Blasting Parameters and Three-dimensional Visualization of Mine Roadway Excavation

针对矿山井下掘进爆破参数设计工作量大、二维图纸不直观等现状,开展了巷道掘进爆破参数优化设计及其三维可视化研究。首先利用粒子群优化算法与神经网络算法,建立了井巷掘进爆破参数优化设计模型,计算获得了待开挖巷道的最佳爆破参数;其次依据爆破钻孔参数及其特点,提出了爆破钻孔三维模型的参数化表征方法,形成了基于参数化的钻孔三维模型自动构建方法;最后以优化设计的爆破参数为基础,自动生成了爆破钻孔三维模型(含装药结构等细节),实现了钻孔三维模型的旋转、缩放、图层显示等交互操作。以山东某矿为工程背景开展了相关研究,结果表明:由优化模型得出的爆破参数与成功案例爆破参数相比误差小,对比指标MAE、RMSE、R^(2)分别为0.154、0.096、0.914;所构建的爆破钻孔三维模型质量高,可直观描述爆破钻孔空间分布、装药结构等信息。

In view of the current situation that the workload of designing blasting parameters for underground excavation in mines is large and inefficient,and the construction layout drawings are mostly two-dimensional plans,it is proposed to use particle swarm optimization algorithm and neural network algorithm to establish an improved model for the design optimization of blasting parameters for underground excavation to accurately predict the optimal blasting parameters for the roadway to be excavated.Using the designed optimal blasting parameters as data support,3D visualization techniques are applied to automatically construct 3D fine models of blast holes,charge structures,etc.The study was carried out in a mine in Shandong Province to optimize the design of blasting parameters and construct a 3D visualization model.The results show that the error between the blasting parameters designed in this study and the blasting parameters of typical successful cases is small,MAE,RMSE and R^(2) are 0.154,0.096 and 0.914 respectively.The established 3D model of blasting borehole is of high quality and can directly describe the information of blasting boreholes such as spatial distribution,charging structure and so on.