基于三维可视化的爆堆形态灰色敏感度分析

爆堆形态是评价爆破质量的重要指标,研究影响其形态的主控因素可以更好地优化爆破质量。 为了探 究影响爆堆形态的主控因素,以乌龙泉露天矿爆破为背景,利用无人机倾斜摄影技术对爆堆形态进行三维建模,运用 灰色关联分析模型确定出影响爆堆形态因素的主次关系。 结果显示:本研究所分析的露天矿爆破的 6 个指标中,单位 炸药消耗量、孔距和排距影响程度接近,灰色绝对关联系数分别为 2. 576 5、2. 500 1、2. 460 1,钻孔深度影响程度最小 为 1. 665 7。 通过结果分析得出,对爆堆形态进行优化时,应首先考虑炸药单耗量,随着炸药单耗量的增加,爆堆的松 散系数也逐渐增大,当炸药单耗量为 0. 78 kg / m3 时,爆堆的松散系数最大为 1. 44;其次应该考虑孔网参数,孔网参数 (孔距×排距)为 7. 5 m2 时,爆堆的松散系数达到最大为 1. 44,但孔网参数需根据矿区实际情况调整确定。 依据爆破 因素的敏感度调整爆破参数取值,可以优化爆堆形态从而提高爆破质量。 基于三维可视化和灰色理论的露天矿爆堆 形态分析能够为爆破后续工作以及爆破优化设计提供依据。

Grey Sensitivity Analysis of Blasting Stockpile Morphology Based on 3D Visualization

The blasting stockpile morphology is an important index to evaluate the blasting quality. Studying the main control factors affecting the morphology can better optimize the blasting quality. In order to explore the main control factors affecting the blasting stockpile morphology,this paper takes the blasting of Wulongquan Open-pit Mine as the background,uses the UAV oblique photography technology to carry out the three-dimensional modeling of the blasting pile shape,and uses the grey correlation analysis model to determine the primary and secondary relations affecting the blasting stockpile morphology.The results show that among the six indexes of open pit blasting analyzed in this paper,the influence degree of unit explosive consumption,hole spacing and row spacing is close,the grey absolute correlation coefficients are 2. 576 5,2. 500 1,2. 460 1 and the minimum influence degree of drilling depth is 1. 665 7. Through the analysis of the results,it is concluded that the unit explosive consumption should be considered first in the optimization of the blasting stockpile morphology. With the increase of the unit explosive consumption,the loose coefficient of the blasting stockpile gradually increases. When the unit explosive consumption is 0. 78 kg/m³,the loose coefficient of the pile is 1. 44;secondly,the hole network parameter should be considered. When the hole network parameter (hole spacing× row spacing) is 7. 5 m²,the loose coefficient of the explosion pile reaches the maximum of 1. 44,but the hole network parameter needs to be adjusted and determined according to the actual situation of the mining area. Adjusting the value of blasting parameters according to the sensitivity of blasting factors can optimize the blasting stockpile morphology and improve the blasting quality. The blasting stockpile morphology analysis of open pit based on three-dimensional visualization and grey theory can provide basis for subsequent blasting work and blasting optimization design.