文献翻译-模糊逻辑法研究粒度对煤浮选动力学的影响.doc

1、翻译翻译原文A study on the effect of particle size on coal flotation kinetics using fuzzy logicEmad Abkhoshk a, Mohammad Kor b,*, Bahram Rezai ca Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iranb Faculty of Mining, Petroleum and Geophysics, Shahrood Univ

2、ersity of Technology, Shahrood, Iranc Amirkabir University of Technology, Tehran, Iranabstract: This paper investigates the effect of particle size on the flotation kinetics of coal in a batch flotation cell.The relationship between flotation kinetics constant and theoretical flotation recovery with

3、 particle size was estimated with nonlinear equations. Analysis of variance shows that varying of particle size is statistically significant on kinetics constant with approximately 96.5% confidence level however it is not significant on maximum theoretical flotation recovery (RI) in 95% confidence l

4、evel. Using fuzzy logicmethod, a multi-input/single-output (MISO) fuzzy model with two input variables: particle size and time and one output variable: cumulative recovery was established to predict the effect of particle size on the flotation kinetics of coal in a batch flotation cell. Application

5、of fuzzy model shows that the results of model fits well to the result of batch flotation and the fuzzy model can be applied to predict cumulative recovery of different coal particle size. The correlation coefficient (R2) values of the proposed fuzzy model were 0.986, 0.993, 0.983, 0.977 and 0.972 f

6、or 37.5 lm, 112.5 lm, 225 lm, 400 lm and 625 lm average particle sizes, respectively.Keywords:Coal Flotation kinetics Modeling Fuzzy logic1. IntroductionFroth flotation is a physicochemical method which is widely used in mineral processing technologies for the separation of finely ground valuable mi

7、nerals from a mixture with gangue minerals initially present in a pulp. Since the cumulative recovery of a component in the concentrate is proportional to flotation time, the flotation process can be considered as a time-rate recovery process(Sripriya, Rao, & Choudhury, 2003; Yuan, Palsson, & Forssb

8、erg,1996). Therefore, mathematical flotation models that incorporate both a recovery and a rate function can completely describe flotation time-recovery profiles. They provide an excellent tool to evaluate flotation tests. The kinetics of flotation has been studied by many workers. Batch flotation t

9、est data in the literature support the first-order rate equation under reasonable operating conditions (Agar, Chia, & Requis, 1998; 莍lek, 2004; Dowling, Klimpel, & Aplan, 1985; Harris & Chakravarti, 1970; Jameson, Nam, & Young, 1977; Mauzimi & Inoue, 1963; Oliveira, Saraiva, Pimenta, & Oliveira, 200

10、1; Wills & Napier-Munn, 2006). A modified first-order rate equation of theform:is proposed, where R is the cumulative recovery after time t, k is the first-order rate constant (time_l), t is the cumulative flotation time and RI is the maximum theoretical flotation recovery. RI (ultimate recovery) an

11、d k (first-order rate constant) are obtained from the model fit to an experimental recovery-time curve. They can be effectively used to evaluate variables affecting flotation process. In the derivation of this equation, it has been assumed that the only independent variable has been the concentratio

12、n of floatable material, and that everything else has remained constant such as size and size distribution, bubble concentration, reagent concentrations, cell operation, etc. (Gupta & Yan, 2006; Labidi, Plach, Turon, & Mutj, 2007; Larsson, Stenius, & Odberg, 1986).It is recognized that coal particle

13、s in a flotation pulp possess a range of rate constants dependent on floatability (Ofori, OBrien, Firth, & Jenkins, 2006). The effect of particle size on flotation rate has been known since the pioneering paper by Gaudin (1932). The results were presented mostly as recovery-size curves, in which the

14、 recovery from a particular size fraction was plotted against the average size of particles in that fraction (King, 1982; Mehrotra & Kapur, 1975; Trahar, 1981). Numerous researchers have studied the kinetics aspects of froth flotation paying special attention to particle size (Herninz & Calero, 2001

15、; Loewenberg & Davis, 1994; Polat, Polat, & Chander, 2003; Radoev, Alexandrova, & Tchaljovska, 1990; Trahar & Warren, 1976; U鐄rum & Bayat, 2007). However the exact relationship between the particle size and flotation rate is complex and not well understood, most probably due to the aggregation of fi

16、ne particles in flotation (Al Taweel et al., 1986; Chander & Polat, 1995; Chander, Polat, & Polat, 1995; Humeres & Debacher, 2002).This study has examined the effects of particle size on the coal flotation kinetics parameters (RI and k). A fuzzy logic model was developed to modeling the effect of particle size on the coal flotation kinetics. Fuzzy logic methodology has been proven to be effective for dealing with complex nonlinear systems wit