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Gold Science and Technology ›› 2016, Vol. 24 ›› Issue (5): 94-101.doi: 10.11872/j.issn.1005-2518.2016.05.094

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HU Xiaokun,SONG Huichang,LIU Qing   

  1. State Key Laboratory of Advanced Metallurgy,University of Science and Technology Beijing,Beijing   100083,China
  • Received:2016-06-29 Revised:2016-07-27 Online:2016-10-28 Published:2016-12-27

Abstract:

The grinding and classification process is an important process of gold ore processing.Realizing the optimization of grinding and classification process is significant to save resources and improve the economic benefit of concentrator.By studing on the grinding and classification process of a domestic gold concentrator,the mathematical model is set up and a simulation system of grinding and classification process is developed based on the simulation software ExtendSim.The structure and functions of simulation system are introduced in detail.As a platform of simulation experiment,the simulation system could help to study the production status of grinding and classification process with different technological parameters.In the simulation example,some simulation tests are designed based on uniform design experimentation to ensure the optimal experiment scheme quickly which choose the rotational speed,the filling ratio and the powder-to-ball ratio of ball mill as factors.In order to obtain the best technological parameters of grinding and classification process,a subsequent series of single factor simulation experiments are implemented.Comparing the multi-bank simulation test results,the optimal parameters of ball mill is obtained under a certain condition of production plan and raw material properties.The simulation results could provide effective reference basis for practical production.

Key words: gold ore, grinding and classification, simulation system, ExtendSim

CLC Number: 

  • TD921

[1] Tie M,Yue H,Chai T.A hybrid intelligent soft-sensor model for dynamic particle size estimation in grinding circuits[M]//Advances in Neural Networks-ISNN 2005.Springer Berlin Heidelberg,2005:871-876.
[2] 柴天佑.生产制造全流程优化控制对控制与优化理论方法的挑战[J].自动化学报,2009,35(6):641-649.
[3] 王泽红.选矿数学模型[M].北京:冶金工业出版社,2015:4-5.
[4] 卢绍文,余策.磨矿粒度动态过程的一种快速Monte Carlo仿真方法[J].自动化学报,2014(9):1903-1911.
[5] 卢绍文.磨矿破裂过程的蒙特卡洛仿真方法研究[J].东北大学学报(自然科学版),2014,35(6):770-774.
[6] 丁进良,陈小品,柴天佑.面向全流程优化的选矿过程仿真系统研发[J].控制工程,2012,19(3):365-369.
[7] Bouche C, Brandt C, Broussaud A.Advanced control of gold ore grinding plants in South Africa[J].Minerals Engineering,2005(18):866-876.
[8] Farzanegan A,Ghalaei A E.Simulation-assisted evaluation of grinding circuit flowsheet design alternatives aghdarreh gold ore[J].Archives of Mining Sciences,2015,60(1):123-141.
[9] Austin L G,Klimpel R R,Luckie P T.Process Engineering of Size Reduction:Ball Milling[M].New York:Society of Mining Engineers of the AIME,1984:69-135.
[10] Wang X,Wang Y,Yang C,et al.Hybrid modeling of an industrial grinding-classification process[J].Powder Technology,2015,279:75-85.
[11] Verkoeijen D,Pouw G A,Meesters G M H,et al.Population balances for particulate processes:a volume approach[J].Chemical Engineering Science,2002(57):2287-2303.
[12] Ying D,Li S R.Mathematical Models of Mineral Processing[M].Changsha:Central South University of Technology Press,1993:128-162.
[13] 马天雨,桂卫华,王雅琳,等.基于分批试验的工业球磨机粒级分布预测模型[J].北京工业大学学报,2012,38(9):1281-1286.
[14] Makokha A B,Moys M H,Bwalya M M,et al.Modeling the RTD of an industrial overflow ball mill as a function of load volumn and slurry concentration[J].Minerals Engineering,2011,24(3/4):335-340.
[15] Cho H,Austin L G.The equivalence between different residence time distribution models in ball milling[J].Powder Technology,2002,124(1):112-118.
[16] Yang D,Xu Z.A model for simulating the grinding and classification cyclic system of waste PCBs recycling production line[J].Journal of Hazardous Materials,2011,192(3):1450-1457.
[17] 谢恒星,李松仁.分级机理与分级模型的研究[J].武汉化工学院学报,1993,15(3):48-53.
[18] 庞学诗.水力旋流器的分离粒度计算方法[J].国外金属矿选矿,1992(5):15-24.
[19] 薛来文,谢琼泽.球磨—旋流器数学模型在磨矿分级自控系统中的应用[J].矿业工程,2012,32(1):50-53.
[20] 王玉,刘昶.ExtendSim 仿真在半导体生产线动态调度研究中的应用[J].机械设计与制造,2014(1):265-268.
[21] 韦科举.选矿过程流程模拟软件系统的设计与开发[D]. 沈阳:东北大学,2009.
[22] Pavlou D, Orfanou A,Busato P,et al.Functional modeling for green biomass supply chains[J].Computer and Electonics in Agriculture,2016,122:29-40.
[23] Peng Fubing,Dun E Er,Cui Tenglong.Research on simulation evaluation of strategic projection base construction planning in ExtendSim environment[J].Applied Mechanics and  Materials,2014,641:704-710.

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