Kinetic modeling and optimization of flotation process in a cyclonic microbubble flotation column using composite central design methodology

Bu, Xiangning; Xie, Guangyuan; Peng, Yaoli; Chen, Yuran

doi:10.1016/j.minpro.2016.11.006

Cited by 63 publications

(31 citation statements)

References 17 publications

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“…The relationship between the superficial gas rate and circulation pressure is depicted in Appendix B (Table A2). The procedure of the flotation column test is described in previous literature [16]. The flotation column was operated continuously to reach a steady state, confirmed by the constant flow of tailings and froth.…”

Section: Column Flotation Testsmentioning

confidence: 99%

“…Air-sparged hydrocyclone (ASH) minimizes the entrainment of gangue materials via an increase in the fine particle flotation rate and froth drainage in the presence of a centrifugal force [12,14,15]. A cyclonic microbubble flotation column, featuring rough beneficiation, primary separation, and scavenging processes in a single unit, is characterized by a specially designed external bubble generator and the integration of a centrifugal field [16]. The bubble generator used in the flotation column, taking advantage of the Venturi principle, is the most widely used hydrodynamic cavitation device [17].…”

Section: Introductionmentioning

confidence: 99%

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Multi-Stage Flotation for the Removal of Ash from Fine Graphite Using Mechanical and Centrifugal Forces

Zhang

Peng

et al. 2018

Minerals

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Graphite ore collected from Hunan province, south China was characterized by chemical analysis, X-ray diffraction, and optical microscopy. Rougher and multi-stage flotation tests using a mechanical flotation cell and a flotation column containing an additional centrifugal force field were carried out to promote its grade and economic value. In rougher flotation, both the mechanical flotation cell and flotation column reduced the ash content of the graphite ore from 15.43% to 10.8%, while the yield of the flotation column (91.41%) was much higher than that of the mechanical flotation cell (50%). In the presence of hydrophobic graphite, the seriously entrained gangue restricted further improvement in the quality and economic value of the graphite ore. Therefore, multi-stage flotation circuits were employed to diminish this entrainment. Multi-stage flotation circuits using the two flotation devices further decreased the ash content of the graphite ore to~8%, while the yield when using the flotation column was much higher than that obtained from the mechanical flotation cell employed. On the other hand, the ash removal efficiency of the flotation column was 3.82-fold higher than that observed for the mechanical flotation cell. The Cleaner 3 flotation circuit using the flotation column decreased the ash content in graphite from 15.43% to 7.97% with a yield of 77.53%.

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Section: Column Flotation Testsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Stage Flotation for the Removal of Ash from Fine Graphite Using Mechanical and Centrifugal Forces

Zhang

Peng

et al. 2018

Minerals

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“…In the process of coal preparation, flotation is used to separate the ash-forming mineral matter and the carbonaceous materials of fine coal below 0.5 mm in size [ 1 , 2 ]. This process is widely applied in countries such as China, USA, Australia, Canada and India [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Switching and optimizing control for coal flotation process based on a hybrid model

et al. 2017

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Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance.

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“…Finally, the controller performance to keep the output at the steady state within the constraint range is demonstrated by simulation studies, and it is concluded that the optimal control scheme presented in this work makes this flotation process more efficient.Mathematics 2018, 6, 100 2 of 17 sub-processes, such as particle-bubble attachment, detachment, and bubble coalescence, making the process more complex and difficult to predict. After several decades of research and development, the process is still not fully understood; the process control of column flotation has proven to be a great challenge and remains a very important topic for the research community.The process control for column flotation consists of three to four interconnected levels [6-8], but according to the control effects, it can be divided into stability control and optimal control [9,10]. At present, most flotation control systems are based on stability control, and the traditional control method uses PID control to achieve automatic control of the froth depth as well as other easily measurable variables to keep the flotation process as close as possible to the steady state [11,12].…”

mentioning

confidence: 99%

“…The process control for column flotation consists of three to four interconnected levels [6-8], but according to the control effects, it can be divided into stability control and optimal control [9,10]. At present, most flotation control systems are based on stability control, and the traditional control method uses PID control to achieve automatic control of the froth depth as well as other easily measurable variables to keep the flotation process as close as possible to the steady state [11,12].…”

mentioning

confidence: 99%

Model Predictive Control of Mineral Column Flotation Process

et al. 2018

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Column flotation is an efficient method commonly used in the mineral industry to separate useful minerals from ores of low grade and complex mineral composition. Its main purpose is to achieve maximum recovery while ensuring desired product grade. This work addresses a model predictive control design for a mineral column flotation process modeled by a set of nonlinear coupled heterodirectional hyperbolic partial differential equations (PDEs) and ordinary differential equations (ODEs), which accounts for the interconnection of well-stirred regions represented by continuous stirred tank reactors (CSTRs) and transport systems given by heterodirectional hyperbolic PDEs, with these two regions combined through the PDEs' boundaries. The model predictive control considers both optimality of the process operations and naturally present input and state/output constraints. For the discrete controller design, spatially varying steady-state profiles are obtained by linearizing the coupled ODE-PDE model, and then the discrete system is obtained by using the Cayley-Tustin time discretization transformation without any spatial discretization and/or without model reduction. The model predictive controller is designed by solving an optimization problem with input and state/output constraints as well as input disturbance to minimize the objective function, which leads to an online-solvable finite constrained quadratic regulator problem. Finally, the controller performance to keep the output at the steady state within the constraint range is demonstrated by simulation studies, and it is concluded that the optimal control scheme presented in this work makes this flotation process more efficient.Mathematics 2018, 6, 100 2 of 17 sub-processes, such as particle-bubble attachment, detachment, and bubble coalescence, making the process more complex and difficult to predict. After several decades of research and development, the process is still not fully understood; the process control of column flotation has proven to be a great challenge and remains a very important topic for the research community.The process control for column flotation consists of three to four interconnected levels [6-8], but according to the control effects, it can be divided into stability control and optimal control [9,10]. At present, most flotation control systems are based on stability control, and the traditional control method uses PID control to achieve automatic control of the froth depth as well as other easily measurable variables to keep the flotation process as close as possible to the steady state [11,12]. A growing number of scholars have begun to apply advanced control methods, such as model predictive control, fuzzy control, expert systems, and neural network control, to regulate the column flotation process and/or combine these novel control methods to achieve better flotation column regulation [13][14][15][16].Model predictive control is the most widely used multivariable control algorithm in current industrial practice. One of its major advanta...

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Kinetic modeling and optimization of flotation process in a cyclonic microbubble flotation column using composite central design methodology

Cited by 63 publications

References 17 publications

Multi-Stage Flotation for the Removal of Ash from Fine Graphite Using Mechanical and Centrifugal Forces

Multi-Stage Flotation for the Removal of Ash from Fine Graphite Using Mechanical and Centrifugal Forces

Switching and optimizing control for coal flotation process based on a hybrid model

Model Predictive Control of Mineral Column Flotation Process

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