Controlling the percent solids of concentration plant No.1 hydrocyclones overflow by a soft sensor at the Sarcheshmeh Copper Complex

Document Type : research - paper

Authors

1 Student of Mineral Processing, Mining Engineering Department, Vali-e-Asr University of Rafsanjan

2 Mineral Processing Group, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

3 Kashigar Mineral Processing Research Center, Shahid Bahonar University of Kerman, Kerman, Iran

4 Sarcheshmeh copper compelex, Rafsanjan, Iran

5 Mining Engineering Department, Shahid Bahonar University of Kerman, Kerman, Iran

Abstract

The primary grinding of the concentration plant No.1 at the Sarcheshmeh copper complex includes eight ball mills working in a closed circuit with hydrocyclones. Due to the importance of the density of hydrocyclones in the classification process, the overflow density control loop was included in the initial plant design. Because of high cost, additional maintenance efforts, safety issues and constraints of nuclear density meters, this control loop never became operational. In this research, the percent solids was determined based on the mass balance equations in a format of a soft sensor. These sensors are computer programs that are used as an inexpensive alternative to hardware sensors and their use has increased in the material processing industry in the recent years. After transferring of the measured data to the control room, a program based on mass balances of solid and water the calculations for all 8 ball mills was prepared. To start the overflow density control loop, a control valve was installed on the inlet of the hydrocyclones feed tank. With the installation of hardware and the use of a soft sensor, the hydrocyclones overflow density control loop made operational for one of the ball mills. The monitoring of the circuit showed that the percent solids fluctuation of hydrocyclones overflow decreased from the range of 30.4 ± 4.5 when the percentage of solids was not displayed to a range of 28 ± 0.5 when using the percent solids control loop was operational. Furthermore, the measurement of the size distribution indicated that the percent of material finer than 75 microns of the overflow increased from 63.5% to 67% on account of installation of the control loop.

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Main Subjects

References

  1. منابع

    1. Kawatra, S.K., Eisele, T.C., Zhang, D., Rusesky, M.; 1988;“Effects of temperature on hydrocyclone efficiency”. Int. J. Miner. Process. 23, 205–211.
    2. Heiskanen, K.; 1993;“Particle Classification”. Chapman & Hall, London,UK.
    3. Wills,B.A., Finch, J.A.; 2016; “Will’s Mineral Processing Technology”, 8nd ed., Elsevier.
    4. Heiskanen, K.; 2000;“Experimental hydrocyclone coping models”. Chem. Eng. J. 80,289–293.
    5. Nageswararao, K., Wiseman, D.M., Napier-Munn, T.J.; 2004;“Two empirical hydrocyclone models revisited”. Miner. Eng. 17, 671–687.
    6. Neesse, T.; 1971;“Hydrocyclone as a turbulence classifier”. Chem. Tech. (Leipzig) 23,146.
    7. Neesse, T., Golyk, V., Kaniut, P., Reinsch, V.; 2004;“Hydrocyclone control in grinding circuits”. Miner. Eng. 17, 1237–1240.
    8. Neesse, T., Schneider, M., Golyk, V., Tiefel, H.; 2004;“Measuring the operating state of the hydrocyclone”. Miner. Eng. 17, 697–703.
    9. Aldrich, C., Uahengo, F.D.L., Kistner, M.; 2015; “Estimation of particle size in hydrocyclone underflow streams by use of multivariate image analysis”.Miner. Eng. 70, 14–19.
    10. Elsele, T.C., Jeltema, C.H.N., Walqui, H., Kawatra, S.K.; 2013;“Coarse and fine ‘‘fishhook” inflections in hydrocyclone efficiency curves”.Miner. Metall. Process. 30,137–144.
    11. Renner, V.G., Cohen, H.E.; 1978;“Measurement and interpretation of size distribution of particles within a hydrocyclone”. Trans. Inst. Min.Metall., Sec. C. 87 (June), C139C145.
    12. Leith, D., Licht, W.; 1972;“The collection efficiency of cyclone type particle collector: anew theoretical approach”. AIChE Symp.Series(Air-1971). 68 (126), 196206.
    13. Kraipech, W., et al.; 2006;“The performance of the empirical models on industrial hydrocyclone design”. Int. J. Miner. Process. 80, 100115.
    14. Plitt, L.R.; 1976;“A mathematical model of the hydrocyclone classifier”.CIM Bull. 69 (Dec.), 114123.
    15. Palaniandy S., Yahyaei M, Powell M.; 2017; “Assessment of hydrocyclone operation in gravity induced stirred mill circuits”. Elsevier; Minerals Engineering 108 (2017) 83–92
    16. Napier-Munn, T.J.; 1996;“Mineral Comminution Circuits: Their Operation and Optimisation”. Chapter 12, Julius Kruttschnitt Mineral Research Centre (JKMRC), The University of Queensland, Brisbane, Australia.
    17. Westendorf, M., et al.; 2015;“Managing cyclones: A valuable asset, the Copper Mountain case study”. Min. Eng. 67 (6), 2641.
    18. Cirulis, D., Russell, J.; 2011;“Cyclone monitoring system improves operations at KUC’s Copperton concentrator”. Eng. Min. J. 212 (10), 4449.
    19. King, R.P.; 2001; “Modeling and Simulation of Mineral Processing Systems”, Butterworth – Heinemann.
    20. Flintoff, B.C., Mular A.L.; 1991; "The Plant Audit”, A Practical Guide to Process Controls in the Minerals Industry, UBC, Brenda, P.P.48.
    21. Sliškovic, D., Grbic, R. Hocenski, Z.; 2011;“Methods for Plant Data-Based Process Modeling in Soft-Sensor Development” ATKAFF 52(4), 306–318(2011).
    22. Pan X.W., Metzner G.; 2004; “Development of Weightometer Soft Sensor” APCOM 2004, Cape Town.
    23. Bazin, C. and Trusiak, A.; 1998; “A Soft Sensor for Flotation Plants” The Canadian Journal of Chemical Engineering, Volume 76, February, 1998.
    24. Casali, A., Vallebuona, G., Bustos, M. Gonzalez, G. and Gimenez, P.; 1998; “A Soft-Sensor For Solid Concentration In Hydrocyclone Overflow”, Minerals Engineering, Vol. 11, No. 4, pp. 375-383.
    25. Pan X.W.; 2012; “Smart Ore Tracking System Using Soft Sensor Technology” AGH Journal of Mining and Geoengineering, vol. 36, No. 4.
    26. Pan X.W.; 2012;“Development Of Stock plile Soft Sensor” AGH Journal of Mining and Geoengineering, vol. 36, No. 4.
    27. Du Y-G, del Villar R, Thibault J.; 1997; “Neural net-based soft sensor for dynamic particle size estimation in grinding circuits”, International Journal of Mineral Processing, 52(2):121–135
    28. National Iranian Copper Industries Company; 1977;“Fine Crushing and Fine Ore Storage, Operating Manual”.

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History

  • Receive Date: 02 March 2019
  • Revise Date: 08 January 2020
  • Accept Date: 10 January 2020

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