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Gold Science and Technology ›› 2023, Vol. 31 ›› Issue (2): 292-301.doi: 10.11872/j.issn.1005-2518.2023.02.161

• Mining Technology and Mine Management • Previous Articles     Next Articles

Research on a Large Homogenized Joint Ore Blending and Production Data Integration and Sharing System Based on the Ant Colony-Ant Cycle Model

Jianhong CHEN(),Yakun ZHAO(),Shan YANG,Xudong ZHONG   

  1. School of Resources and Safety Engineering，Central South University，Changsha 410083，Hunan，China
  • Received:2022-10-30 Revised:2022-12-30 Online:2023-04-30 Published:2023-04-27
  • Contact: Yakun ZHAO E-mail:cjh@263.net;zhaoyakuncsu@163.com

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Abstract:

With the upgrading of mine production modes and the renewal of business philosophy，the problems that commonly exist in mining enterprises，such as low accuracy in manual calculation of ore blending，large fluctuations in ore grade，unbalanced ore quantities，and fragmentation of production data management，have become more and more obvious.Starting from the blending and production data management of ore management work，the mathematical model of large homogenized joint ore blending was established based on the theory of large homogenized joint ore blending technology and the ant colony-ant cycle algorithm model. The integrated management method of production data integration and sharing was proposed based on the large homogenized joint ore blending technology route and the mine on-site situation，summarizing the process，key data，and hierarchical linkage relationship.A large homogenized joint ore blending and production data integration and sharing system was constructed based on the ant colony-ant cycle model.Firstly，integrating the multi-stage ore blending in the mining site，stockpile，and processing plant，optimizing the blending quantity and ore grade from a global perspective，proposing the theory of a large homogenized joint ore blending technology，and establishing a large homogenized joint ore blending function according to the actual blending.Secondly，using the ant colony-ant cycle algorithm as the modeling framework of the blending model，establishing the mathematical model of large homogenized ore blending based on the large homogenized transformation，taking the large homogenized cycle as the number of iterations，and continuously adjusting the blending quality through the automatic blending order output from the model in the producing cycle. Finally，based on the ASP.NET low-code development platform，the B/S framework，and SQL Server database technology，big data charting combined with analysis technology and integrated data interface technology were introduced to develop a large homogenized joint ore blending and production data integration and sharing system.According to the application of the system at Dabaoshan polymetallic mine，the results show that after the system has been put into use，the whole process of mine ore blending and production has been systematized and streamlined，compared with the original ore blending method，the ore grade has been stabilized and balanced，the comprehensive recovery rate has been initially increased by 0.8%，the fluctuation range of the ore grade has been controlled to not exceed ±10%，and the mine management level and mineral product quality have been improved.

Key words: large homogenized joint ore blending, ant colony-ant cycle model, B/S framework, production data integration and sharing system, ore grade

CLC Number: 

  • TD80-9

Fig.1

Road map of large homogenization joint ore blending technology"

Fig.2

Flow diagram of large homogenization joint ore blending model"

Fig.3

Production data integration management method"

Fig.4

Effect diagram of system data statistics"

Fig.5

Effect diagram of system big data chart combined with analysis"

Chen Guangmu， Zhao Yifei， Chen Jianhong，et al，2022.Dabaoshan mine homogenization intelligent ore matching system research［J］.Mining technology，22（1）：142-146，149.
Chen Xin， Gao Feng， Xie Xionghui，et al，2021.Development and application of collaborative platform for mine production technology［J］.Gold Science and Technology，29（3）：449-456.
Ding Hui， He Shuai，2018.Research and application of production efficiency improvement of digital mine management in open-pit mine［J］.Opencast Mining Technology，33（1）：66-69.
Feng Qian， Li Qing， Wang Yaozu，et al，2022.Application of constrained multi-objective particle swarm optimization to sinter proportioning optimization［J］.Control Theory and Applications，39（5）：923-932.
Gao Wei，2008.The intelligent bionic model—Ant colony［J］.CAAI Transactions on Intelligent Systems，3（3）：270-278.
Gu Qinghua， Liu Silu， Zhang Jinlong，2021a.Research on multi-metal and multi-objective intelligent ore blending in open-pit mine based on evolutionary algorithm MOEA/D-AU［J］.Nonferrous Metals （Mining Section），73（6）：1-8.
Gu Qinghua， Zhang Wei， Cheng Ping，et al，2021b.Optimization model of ore blending of limestone open-pit mine based on fuzzy multi-objective［J］.Mining Research and Development，41（12）：181-187.
Hou Jie，2019.Optimization Model of Mining Scheme for Underground Metal Mine Based on Block Value ［D］.Beijing：University of Science and Technology Beijing.
Huang Linqi， He Binquan， Wu Yangchun，et al，2021.Optimization research on the polymetallic multi-objective ore blending for unbalanced grade in Shizhuyuan mine［J］.Mining Research and Development，41（11）：193-198.
Huang Yijuan，2017.Study on the production of ore quality management［J］.World Non-Ferrous Metals，（16）：81-83.
Kou Mingyin， Zhang Zhong， Zeng Wang，et al，2022.Research progress on optimization technology and its model of ore-blending for sinter process［J］.Iron and Steel，57（2）：1-11.
Li Wei，2019.Ore Mixing Characteristics and Regulation of Released Ore Grade during the Ore-drawing in the Main Ore-pass of Jinshandian Iron Mine ［D］.Wuhan：Wuhan University of Science and Technology.
Li Yinxia， Wu Lei，2018.Practice of improving the selected ore quality in large complex strip mine［J］.Modern Mining，34（12）：234-236.
Sun Mingchen， Li Chunyang， Li Xiaoshuai，2019.Research on intelligent optimization of large area coordination allocation in multi-mining areas［C］//Proceedings of the 26th Tenth Province Metal Society Metallurgical and Mining Academic Exchange Conference.Taiyuan：Shanxi Association for Science and Technology.
Tang Qingli， Zhang Jianliang， Li Kejiang，et al，2017.Comparative analysis on methods and algorithms for optimization of raw materials blending in sinter process［J］.China Metallurgy，27（5）：13-18.
Tu Hongjian， Wang Liguan， Chen Xin，et al，2019.Ore grade control blending in open-pit mine based on mixed integer programming［J］.Gold Science and Technology，27（3）：458-465.
Wang Jianrong， Chen Bin， Chen Ke，2022.Research on elevator group control system based on ant colony algorithm［J］.Industrial Instrumentation and Automation，（4）：127-131.
Wang Lei， Cao Han， Wang Changying，2011.Analysis on three parallel models of ant colony algorithm［J］.Computer Engineering，37（12）：170-172，175.
Wang Liguan， Song Huaqiang， Bi Lin，et al，2017.Optimization of open pit multielement ore blending based on goal programming［J］.Journal of Northeastern University Natural Science，38（7）：1031-1036.
Wu Shuliang，2012.Ore Matching Model of Establishment of Underground Bauxite Ore and Optimizational Research［D］.Changsha：Central South University.
Wu Xiaojing，2020.The Research on Sintering Ore Optimization Model and Sinter Quality Prediction［D］.Shijiazhuang：Hebei University of Economics and Business.
Xiong Tao，2018.Application of linear programming in a metal open pit mine［J］.Design and Research of Nonferrous Metallurgy，39（4）：11-13.
Xu Bo， Huang Wusheng，2013.Management system of accurate ore costing for gold mines［J］.Metal Mine，42（5）：125-127.
Yan Zhongxin， Li Yachao， Wang Wenfei，et al，2021.Real-time data acquisition of mineral processing process based on service［J］.Copper Engineering，（3）：93-97.
Zhang Bingbing， Yu Hong， Zhang Zhonglei，et al，2019.Digital and fine management practice of open-pit mining and stripping construction［J］.Gold Science and Technology，27（4）：621-628.
Zhang Lei，2021.Research and application of data information reporting system in coal mine enterprises［J］.Energy and Energy Conservation，（8）：212-213，220.
Zhou Qiaoliang， Liu Nini，2022.Application of ant colony algorithm in intelligent coal preparation process of dense medium［J］.Coal Technology，41（9）：246-248.
陈光木，赵一霏，陈建宏，等，2022.大宝山矿大均化智能配矿系统研究［J］.采矿技术，22（1）：142-146，149.
陈鑫，高峰，谢雄辉，等，2021.矿山生产技术协同平台研发与应用［J］.黄金科学技术，29（3）：449-456.
丁辉，何帅，2018.露天矿数字化矿山管理生产效率提高研究与应用［J］.露天采矿技术，33（1）：66-69.
冯茜，李擎，王耀祖，等，2022.约束多目标粒子群算法在烧结配矿优化中的应用［J］.控制理论与应用，39（5）：923-932.
高玮，2008.新型智能仿生模型——蚁群模型［J］.智能系统学报，（3）：270-278.
顾清华，刘思鲁，张金龙，2021a.基于进化算法MOEA/D-AU的露天矿多金属多目标智能配矿研究［J］.有色金属（矿山部分），73（6）：1-8.
顾清华，张伟，程平，等，2021b.基于模糊多目标的石灰石露天矿配矿优化模型［J］.矿业研究与开发，41（12）：181-187.
侯杰，2019.基于块体价值的金属地下矿山开采规划优化模型研究［D］.北京：北京科技大学.
黄麟淇，何斌全，吴阳春，等，2021.柿竹园矿非均衡品位多金属多目标配矿优化研究［J］.矿业研究与开发，41（11）：193-198.
黄宜卷，2017.生产矿山矿石质量管理研究［J］.世界有色金属，（16）：81-83.
寇明银，张众，曾旺，等，2022.铁矿粉烧结优化配矿及其模型研究进展［J］.钢铁，57（2）：1-11.
李伟，2019.金山店铁矿主溜井放矿过程中矿石混合特性及放出矿石品位调控［D］.武汉：武汉科技大学.
李银霞，吴磊，2018.大型复杂露天铁矿提高入选矿石质量实践［J］.现代矿业，34（12）：234-236.
孙铭辰，李纯阳，李小帅，2019.针对多采区大区域协调配矿智能优化研究［C］//第二十六届十省金属学会冶金矿业学术交流会论文集.太原：山西省科学技术协会.
唐庆利，张建良，李克江，等，2017.烧结配料优化方法及算法对比分析［J］.中国冶金，27（5）：13-18.
涂鸿渐，王李管，陈鑫，等，2019.基于混合整数规划法的露天矿配矿品位控制［J］.黄金科学技术，27（3）：458-465.
王建荣，陈斌，陈柯，2022.基于蚁群算法的电梯群控系统研究［J］.工业仪表与自动化装置，（4）：127-131.
王磊，曹菡，王长缨，2011.蚁群算法的三种并行模型分析［J］.计算机工程，37（12）：170-172，175.
王李管，宋华强，毕林，等，2017.基于目标规划的露天矿多元素配矿优化［J］.东北大学学报（自然科学版），38（7）：1031-1036.
邬书良，2012.地下铝土矿配矿模型的建立及优化研究［D］.长沙：中南大学.
武晓婧，2020.烧结配矿优化模型及烧结矿质量预测研究［D］.石家庄：河北经贸大学.
熊涛，2018.线性规划在某金属露天矿山中的应用［J］.有色冶金设计与研究，39（4）：11-13.
徐波，黄武胜，2013.黄金矿山矿石生产成本精细化管理系统［J］.金属矿山，42（5）：125-127.
严忠新，李亚超，王文飞，等，2021.一种基于服务的选矿流程实时数据采集［J］.铜业工程，（3）：93-97.
张兵兵，喻鸿，张中雷，等，2019.露天矿山采剥施工的数字化精细管理实践［J］.黄金科学技术，27（4）：621-628.
张蕾，2021.煤矿企业数据信息报送系统的研究应用［J］.能源与节能，（8）：212-213，220.
周桥梁，刘妮妮，2022.蚁群算法在重介质智能化选煤过程中的应用［J］.煤炭技术，41（9）：246-248.
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