首页> 外文期刊>Tunnelling and underground space technology >Performance prediction of roadheaders in metallic ore excavation
【24h】

Performance prediction of roadheaders in metallic ore excavation

机译:掘进机在金属矿石开挖中的性能预测

获取原文
获取原文并翻译 | 示例
           

摘要

Using mechanical miners such as roadheaders may be a solution to increase the production rate and to decrease the costs in metallic mines. In this study, the performance prediction and cutter consumption of roadheaders were investigated for the eight different ore types. Small-scale linear cutting tests, Cerchar abrasivity tests and physico-mechanical tests were carried out on the ore samples collected from the site. The instantaneous cutting rates of a selected roadheader were calculated using specific energy (SE) values and compared to the previous models. The amount of cutter consumption was also calculated for each ore type and it was seen that the estimated cutter consumption values for the tested ores are generally lower than the proposed economical upper limit. Since only the performance prediction and cutter consumption of roadheaders were investigated for the excavation of ores in the current study, analyzing all mining operations is necessary for the adaptation of roadheader excavation to a mine. Simple and multiple regression models were also derived for the estimation of SE from the ore properties. A significant practical model including the Schmidt hammer value and density of ores was produced from the multiple regression analysis. This regression model can be reliably used for the estimation of SE especially for the preliminary studies.
机译:使用机械式采矿机(例如掘进机)可能是提高生产率并降低金属矿山成本的解决方案。在这项研究中,研究了八种不同矿石类型的掘进机的性能预测和切刀消耗。对从现场收集的矿石样品进行了小型线性切割试验,Cerchar耐磨性试验和物理机械试验。使用特定能量(SE)值计算选定掘进机的瞬时切割率,并将其与以前的模型进行比较。还针对每种矿石类型计算了刀具消耗量,并且可以看出,用于测试矿石的刀具消耗量估计值通常低于建议的经济上限。由于在当前研究中仅对掘进机的性能预测和绞车消耗量进行了研究,因此分析所有采矿作业对于使掘进机挖掘适应矿山是必要的。还从矿石性质中推导了简单和多重回归模型来估算SE。通过多元回归分析得出了一个重要的实用模型,其中包括施密特锤值和矿石密度。该回归模型可以可靠地用于SE的估计,尤其是对于初步研究而言。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号