Abstract




 
   

IJE TRANSACTIONS B: Applications Vol. 17, No. 2 (July 2004) 121-130   

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  MODELING OF TEXTURE AND COLOR FROTH CHARACTERISTICS FOR EVALUATION OF FLOTATION PERFORMANCE IN SARCHESHMEH COPPER PILOT PLANT, USING IMAGE ANALYSIS AND NEURAL NETWORKS
 
N. Saghatoleslam, H. Karimi and R. Rahimi

Department of Chemical Engineering, University of Sistan and Baluchestan
Zahedan, Iran 98164
psaghatoleslami@yahoo.com - Hajirk@yahoo.com - Rahimi@hamoon.usb.ac.ir


H. H. A. Shirazi

Department of Mining Engineering, University of Bahonar
Kerman, Iran
 
 
( Received: January 04, 2003 – Accepted in Revised Form: June 10, 2004 )
 
 

Abstract    Texture and color appearance of froth is a discreet qualitative tool for evaluating the performance of flotation process. The structure of a froth developed on the flotation cell has a significant effect on the grade and recovery of copper concentrate. In this work, image analysis and neural networks have been implemented to model and control the performance of such a system. The result reveals that these techniques can be employed to control the performance of flotation cells, improve the recovery of the copper concentrate and finally reduce the dependency of the performance on the solely observation of an operator which can be otherwise subjected to human error.

 

Keywords    Froths Flotation, Digital Image Processing, Copper Concentration, Neural Networks

 

References   

 
1. Moolman, D. W., Aldrich, C., Van Deventer, J. S. J. and Stange, W., “Digital Image Processing as Tool for On-Line Monitoring of Froth in Flotation Plants”, Minerals Eng., Vol. 7, No. 9, (1994), 1149-1164.

2. Van Deventer, J. S. J., Bezuidenhout, M. and Moolman, D. W., “On-Line Visualization Flotation Performance Using Neural Computer Vision of the Froth Texture”, Min. Cong., Aachen, Germany, (1997), 315-326.

3. Bonifazi, G., Serranti, S., Volpe, F. and Zuco, R., “Characterization of Flotation Froth Color and Structure by Machine Vision”, Computers and Geosciences, in press, (2000).

4. Bonifazi, G., et. al., “Characterization of the Flotation Froth Structure and Color by Machine Vision (CHACO)”, Proc. XXI Int. Min. Proc. Cong., (2001), C8a-39-C8a49.

5. Castleman, Kenneth R. “Digital Image Processing”, McGraw-Hill Book Company, N. Y., (1996).

6. Bonifazi, G., Massascci, P. and Meloni, A., “3D Froth Modeling by Image Analysis”, Proc. XXI Int. Min. Proc. Cong., (2001), B8a-178-B8a189.

7. Saghatoleslami, N., Karimi, H., Rahimi, R. and Shirazi, H. A., “Quantitative Experimental Investigation of the Effect of Operating Conditions on the Froth Structure in Copper Flotation Process, using Image Analysis”, Iranian J. of Chemistry and Chemical Eng., In press, (2004).

8. Moolman, D. W., Ekesteen, J. J., Aldrich, C. and Van Deventer, J. S. J., “The Significance of Flotation Froth Appearnce for Machine Vision Control”, Int. J. Miner. Process, Vol. 48, (1996), 135-158.





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