Modeling of fine coal flotation separation based on particle characteristics and hydrodynamic conditions

被引:5
作者
Shahbazi B. [1 ]
Chelgani S.C. [2 ]
机构
[1] Department of Mining Engineering, Tarbiat Modares University, Tehran
[2] Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, 48109, MI
关键词
Coal processing; Flotation; Hydrodynamic conditions; Modeling; Particle characteristics;
D O I
10.1007/s40789-016-0147-9
中图分类号
学科分类号
摘要
Flotation is a complex multifaceted process that is widely used for the separation of finely ground minerals. The theory of froth flotation is complex and is not completely understood. This fact has been brought many monitoring challenges in a coal processing plant. To solve those challenges, it is important to understand the effect of different parameters on the fine particle separation, and control flotation performance for a particular system. This study is going to indicate the effect of various parameters (particle characteristics and hydrodynamic conditions) on coal flotation responses (flotation rate constant and recovery) by different modeling techniques. A comprehensive coal flotation database was prepared for the statistical and soft computing methods. Statistical factors were used for variable selections. Results were in a good agreement with recent theoretical flotation investigations. Computational models accurately can estimate flotation rate constant and coal recovery (correlation coefficient 0.85, and 0.99, respectively). According to the results, it can be concluded that the soft computing models can overcome the complexity of process and be used as an expert system to control, and optimize parameters of coal flotation process. © 2016, The Author(s).
引用
收藏
页码:429 / 439
页数:10
相关论文
共 66 条
[1]  
Abkhoshk E., Kor M., Rezai B., A study on the effect of particle size on coal flotation kinetics using fuzzy logic, Expert Syst Appl, 37, pp. 5201-5207, (2010)
[2]  
Agar G.E., Chia J., Requis-c L., Flotation rate measurements to optimise an operating circuit, Miner Eng, 11, 4, pp. 347-360, (1998)
[3]  
Amini E., Influence of flotation cell hydrodynamics on the flotation kinetics and scale up of flotation recovery (PhD thesis), The University of Queensland in Sustainable Minerals Institute—Julius Kruttschnitt Mineral Research Centre, pp. 1-207, (2012)
[4]  
Arnold B.J., Aplan F.F., The hydrophobicity of coal macerals, Fuel, 68, pp. 651-658, (1989)
[5]  
Atkinson K., An introduction to numerical analysis, (1989)
[6]  
Barraza J., Guerrero J., Pineres J., Flotation of refuse tailings fine coal slurry, Fuel Process Technol, 106, pp. 498-500, (2013)
[7]  
Bastian A., Identifying fuzzy models utilizing genetic programming, Fuzzy Set Syst, 113, pp. 335-350, (2000)
[8]  
Buragohain M., Mahanta C., A novel approach for ANFIS modelling based on full factorial design, Appl Soft Comput, 8, pp. 609-625, (2008)
[9]  
Chelgani S.C., Makaremi S., Explaining the relationship between common coal analyses and Afghan coal parameters using statistical modeling methods, Fuel Process Technol, 110, pp. 79-85, (2013)
[10]  
Chelgani S.C., Shahbazi B., Rezai B., Estimation of froth flotation recovery and collision probability base on dimensional parameters using artificial neural network, Int J Miner Metall Mater, 17, 5, pp. 526-534, (2010)