露天矿抛掷爆破工艺爆堆形态的数据融合估值算法

针对露天矿抛掷爆破工艺中的爆堆形态估算问题,提出了一种便捷的爆堆形态估值算法,仅利用采集到的同类多源数据即可得到精确的预测结果。提出了爆堆形态估值算法的计算步骤为“数据采样—融合精度判别—数据融合最优权值计算—获得数据融合结果”,并制定了数据采样规则、推导了精度判别方法与最优权值确定方法。以黑岱沟露天矿某次抛掷爆破工程为研究案例,分别利用爆堆形态数据融合估值算法与Weibull分布预测方法,在拉斗铲作业平盘高度为11~13m的情况下,对拉斗铲倒堆系统各工艺作业量进行了计算,结果显示：采用数据融合算法的误差可控制在5%以内,更优于Weibull分布预测方法,可以满足满足现场算量精度要求。

Data Fusion Estimation Algorithm for Burst Form of Blasting Process in Open pit Mine

Aiming at the estimation of the muck-pile shape in the cast blasting process, a convenient method is proposed. Only the similar multi-source data can be used to obtain the accurate prediction result. The method of estimating the muck-pile shape is proposed as "data sampling-fusion accuracy discrimination-data fusion optimal weight calculation-get data fusion result", and the data sampling rules are established, the method of precision discrimination and the method of determining the optimal weight are deduced. Taking the cast blasting project in Heidaigou open-pit mine as a research case, the method of data fusion and Weibull distribution prediction are used to calculate the volume in dragline system at 11 ~ 13m of dragline operation bench ,The results show that the error of data fusion algorithm can be controlled within 5%, which is better than Weibull distribution prediction method, which can meet the requirement of satisfying the accuracy of field calculation.