基于摄影测量法的袁家村铁矿爆破块度预测

Prediction of blasting fragmentation in Yuanjiacun iron mine based on photogrammetry

以宝武集团下的袁家村露天铁矿为背景,运用无人机摄影测量技术对爆破后的块度分布情况进行了统计;基于Kuz-Ram模型计算得到的平均块度X_(m)与采用摄影测量技术分析得到的平均块度I_(50)之间存在较大误差,进而分析两者差值较大的原因。结果表明:原位岩体的物理力学性质与节理发育程度对爆破后的块度的分布有很大影响,而这个影响主要由Kuz-Ram模型中的岩石系数A所决定;采用最小二乘法原理对Kuz-Ram模型中的岩石系数A进行修正计算得到的平均块度X_(p)^(m)与I_(50)之间的相对误差均在10%以下,其准确性明显提升。

Based on Yuanjiacun open-pit iron mine of Baowu Group,the article counts blasting fragmentation by using the UAV photogrammetry technology.There is a big error between the mean particle sizeX_(m) calculated based on Kuz-Ram model and the mean particle size I_(50) analyzed by photogrammetry.The results show that the physical and mechanical properties of in-situ rock mass and the degree of joint development have a great influence on the blasting fragmentation,which is mainly determined by the rock coefficient A in Kuz-Ram model.The article modifies rock coefficient A in Kuz-Ram model by using the least squares principle,the relative difference between the X_(p)^(m) and I_(50) is less than 10%and the accuracy of the modified Kuz-Ram model is obviously improved.