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首页> 外文期刊>Journal of the Southern African Institute of Mining and Metallurgy >Predicting rock fragmentation based on drill monitoring: A case study from Malmberget mine, Sweden
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Predicting rock fragmentation based on drill monitoring: A case study from Malmberget mine, Sweden

机译:根据钻监测预测岩石碎片化:瑞典Malmberget矿的案例研究

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摘要

Fragmentation analysis is an essential part of the optimization process in any mining operation. The costs of loading, hauling, and crushing the rock are strongly influenced by the size distribution of the blasted rock. Several direct and indirect methods are used to analyse or predict fragmentation, but none is entirely applicable to fragmentation assessment in sublevel caving mines, mainly because of the limitations imposed by the underground environment and the lack of all the required data to adequately describe the rock mass. Over the past few years, measurement while drilling (MWD) data has emerged as a potential tool to provide more information about the in-situ rock mass. This research investigated if MWD can be used to predict rock fragmentation in sublevel caving. The MWD data obtained from a sublevel caving mine in northern Sweden were used to find the relationship between rock fragmentation and the nature of the rock mass. The loading operation of the mine was filmed for more than 12 months to capture images of loaded load-haul-dump (LHD) buckets. The blasted material in those buckets was classified into four categories based on the median particle size (X50). The results showed a stronger correlation for fine and medium fragmented material with rock type (MWD data) than coarser material. The paper presents a model for prediction of fragmentation, which concludes that it is possible to use MWD data for fragmentation prediction.
机译:碎片分析是任何采矿操作中优化过程的重要组成部分。岩石的装载,拖拉和压碎的成本受到爆破岩石的尺寸分布的强烈影响。几种直接和间接方法用于分析或预测碎片化,但没有一个完全适用于在分布式洞穴矿山中的分裂评估,这主要是因为地下环境施加的局限性以及缺乏所有必需的数据来充分描述岩石质量。在过去的几年中,钻探(MWD)数据的测量已成为提供有关原位岩石质量的更多信息的潜在工具。这项研究调查了MWD是否可以用于预测船舶塌陷中的岩石碎片化。从瑞典北部的一台洞穴矿获得的MWD数据被用来找到岩石碎片和岩石质量的性质之间的关系。矿山的负载操作被拍摄了12个月以上,以捕获负载荷兰 - 唐普(LHD)桶的图像。这些水桶中的爆破材料根据中位粒径(x50)分为四类。结果表明,与更粗的材料相比,与岩石类型(MWD数据)的细材料和中等碎片材料的相关性更强。本文提出了一个预测碎片的模型,该模型得出结论,可以将MWD数据用于碎片化预测。

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