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Gold Science and Technology >

2021 , Vol. 29 >Issue 2: 287 - 295

DOI: https://doi.org/10.11872/j.issn.1005-2518.2021.02.140

Mining Technology and Mine Management

Grade Model Constructing and Reclaiming Grade Predicting of Ore Yard

  • Xin CHEN , 1 ,
  • Liguan WANG 1, 2 ,
  • Jinling LI , 1
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  • 1. Changsha Digital Mine Co. ，Ltd. ，Changsha 410083，Hunan，China
  • 2. School of Resources and Safety Engineering，Central South University，Changsha 410083，Hunan，China

Received date: 2020-07-29

  Revised date: 2020-12-29

  Online published: 2021-05-28

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Highlights

Ore yard is an indispensable part of most mines，and the precisely controll of its grade spatial distribution is the foundation of follow-up processes.The development and application of surveying technology provided technical guidance to the surveying and modeling of ore yard.Domestic and foreign scholars applied GPS RTK，3D laser scanning，GPR integration and unmanned aerial vehicle tilt photogrammetry to 3D modeling of ore yard. At the same time，grade distribution in ore body，production region and blasting muck yard was researched richly. But few scholars pay attention to grade distribution in ore yard，for the lacking of sample information to support the research of the spatial grade analysis of ore yard. The deeply application of grade on-line analyzer in mine production detection provided data sources for the modeling of ore yard’s grade model. Combined with the detecting real-time value of grade on-line analyzer，method of grade model constructing was proposed. 3D ore yard model was discretized. Ore yard was discretized as sub-segment in the length direction，and as sub-level in the cross section. Secondly，according to the spatial distance and ore flow velocity，the time gap between different locations when ore flow passed was calculated.Finally，turn the serialized data into 3D model of ore yard based on the time gap of ore flow. Then quantity and grade of each sub-segment and sub-level was analyzed. Based on 3D ore yard grade model，grade distribution was analyzed on the reclaimer’s working surface with the location and angle of claw.As the result，real-time grade was predicted. In order to verify the accuracy of ore yard grade model and reclaiming grade predicting method，grade data of MgO was contrasted between 4 shifts.Used hourly sampling test value as baseline，mean value and predictive value were contrasted. When used mean value as the reclaiming grade，the maximal hourly gap in 4 shifts is 13.87%，17.04%，15.65% and 12.54% respectively，and maximal shift average gap is 5.66%，9.41%，7.76% and 6.63% respectively. Meanwhile，when used predictive value as the reclaiming grade，the maximal hourly gap in 4 shifts is 2.93%，3.44%，3.50% and 3.16% respectively，and maximal shift average gap is 1.88%，1.98%，1.83% and 1.73% respectively. Contrastive analysis between mean value，test value and predictive value show that hourly gap is lower than 3.5%，and shift average gap is lower than 2%. The ore yard grade modeling and reclaiming grade predicting method is accurate and real-time，which improves the effect of grade control in mine.

Cite this article

Xin CHEN , Liguan WANG , Jinling LI . Grade Model Constructing and Reclaiming Grade Predicting of Ore Yard[J]. Gold Science and Technology, 2021 , 29(2) : 287 -295 . DOI: 10.11872/j.issn.1005-2518.2021.02.140

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力拓集团将从位于美国的Kennecott矿的铜冶炼中回收关键矿物

力拓集团（Rio Tinto）将在犹他州盐湖城附近的Kennecott矿建设一座新工厂，以通过铜精炼回收碲（一种用于太阳能电池板的关键矿物）。

力拓集团将为该工厂的建设投资290万美元，从废料流中提取有价值矿物，作为铜冶炼副产品回收碲。该工厂的碲生产能力约20吨/年。力拓集团预计将在2021年12月开始生产碲，从而建立新的北美关键矿物供应链。

碲是碲化镉的重要成分，碲化镉是一种用于制造薄膜光伏太阳能电池板的半导体，用这种化合物制成的薄膜可以有效地将阳光转化为电能。碲还可以用作钢和铜的添加剂，以提高加工性能使金属更易于切割，还可以添加它来提高对硫酸、振动和疲劳的抵抗力。

力拓集团Kennecott矿的董事总经理Gaby Poirier表示，“我们生产的矿物和金属对于加速向可再生能源的过渡至关重要。将碲添加到我们的产品组合中，可为北美的客户提供安全可靠的碲来源，即利用可再生能源在最严格的环境和劳工标准下生产。力拓集团致力于利用创新来减少生产过程中的浪费，并从开采和加工的材料中获得尽可能多的价值。”

犹他州州长Spencer Cox表示，“犹他州拥有丰富的自然资源，是协助供应维持美国制造业竞争力必不可少的关键矿物的理想选择。位于Kennecott的力拓集团冶炼厂是仅有的两家能够生产铜和其他重要矿物的冶炼厂之一。新的碲生产厂是美国关键矿物独立和能源安全的又一重要贡献。”

除了生产美国近20%的铜外，Kennecott的冶炼流程还回收金、银、碳酸铅、铂、钯和硒，同时还从Copperton选厂回收钼。目前，总共有9种产品是从Kennecott提取的矿石中回收的。

力拓集团是美国能源部关键材料研究所（CMI）的合作伙伴，正与CMI的专家紧密合作，以发现进一步经济性回收碲和锂等关键矿物副产品的方法。此外，该公司正在投资建设新设施，以从加利福尼亚州的硼矿废料中提取电池级锂以及从魁北克省的Sorel-Tracy冶金厂废料中提取高品质的氧化钪。

http://www.goldsci.ac.cn/article/2021/1005-2518/1005-2518-2021-29-2-287.shtml

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