基于BP神经网络的爆破参数优化

Optimization of Blasting Parameters Based on BP Neural Network

针对露天矿山台阶爆破效果欠佳造成后续工艺效率不高的现象,以某露天矿为依托,利用BP神经网络系统建立爆破参数优化预测模型,对现场爆破参数进行优化,对比优化前后的现场爆破效果证明模型优化的爆破参数大大改善了爆破效果,100 cm以上大块率减小6.88个百分点,60 cm以下块度增加了35.94个百分点,为提高铲装效率创造了条件。

Due to the poor effect in subsequent process of bench blasting,an optimization model of the blasting parameters was established by the BP neural network system based on an openpit mine. Then,the blasting parameters were optimized,and the blasting effects before and after optimization were compared. The results proved that the optimized parameters based on the model had improved the blasting effect obviously. The boulder yield of the ores with diameters over 100 cm reduced by 6. 68 percent points,and boulder yield of the ores with diameters less than 60 cm increased by 35. 94 percent points,which created favorable conditions for improving the loading efficiency.