矿石堆场品位模型构建及取料品位估算方法

doi:10.11872/j.issn.1005-2518.2021.02.140

摘要/Abstract

摘要：

矿石堆场是大多数矿山不可或缺的重要组成部分，对其品位空间分布情况的精确掌控是后续工艺的基础。结合品位在线分析仪检测的实时品位数据，提出矿石堆场品位模型构建方法，将序列化的实时品位数据三维空间化；同时给出相应的取料品位估算方法，动态预测取料品位。为验证品位模型构建及取料品位估算的准确性，将取料品位估算结果与实验室化验结果进行对比，结果表明：每小时品位偏差小于3.5%，班平均品位偏差小于2%，基于矿石堆场品位模型的取料品位估算结果准确、实时性高，极大地提高了矿山品位控制的效果。

关键词: 矿石堆场, 品位模型, 模型离散化, 品位在线分析, 动态预测, 取料品位估算

Abstract:

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.

Key words: ore yard, grade model, model discretization, grade on-line analyzer, dynamic prediction, re-claiming grade estimation

中图分类号:

TD672

陈鑫,王李管,李金玲. 矿石堆场品位模型构建及取料品位估算方法[J]. 黄金科学技术, 2021, 29(2): 287-295.

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.

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