Modeling the Moment of Resistance Generated by an Ore-Grinding Mill

The pertinence of modeling the moment of resistance generated by the ore-grinding mill is substantiated. Based on the ranking of technological indices obtained in the result of the survey among the specialists of several beneficiating plants, the factors determining the level of the moment of resistance generated by the mill are revealed. A priori diagram of the ranks is obtained in which the factors are arranged in the descending order of the impact degree on the level of the moment. The obtained model of the moment of resistance shows the technological character of the operation modes of the ore-grinding mill and can be used for improving the operation modes of the system motor-mill and preventing the abnormal mode of the drive synchronous motor.




References:
[1] Hart, S., Valery, W., Clements, B., Reed, M., Song, M., and Dunne, R. “Optimization of the Cadia Hill SAG Mill Circuit,” International Conference on Autogenous and Semiautogenous Grinding Technology (SAG2001), 30 September - 3 October, Vancouver, BC, Canada, Vol. 1, pp. 11-30.
[2] Herbst, J.A., and Lichter, J.K., “Use of multiphysics models for the optimization of comminution operations,” Advances in Comminution, S. Komar Kawatra, ed., SME, 2006, pp. 193-204.
[3] Jones, S.M., Jr., 2006, “Autogenous and semi-autogenous mills 2005 update,” International Conference on Autogenous and Semiautogenous Grinding Technology (SAG2006), 23-27 September, Vancouver, BC, Canada, Vol. 1, pp. 398-425.
[4] McIvor, R., “Effects of speed and liner configuration on ball mill performance,” Mining Engineering, 1983, Vol. 35, No. 6, June, pp. 617-622.
[5] Wills, B.A., and Napier-Munn, T., Wills’ Mineral Processing Technology, Elsevier, 2006, Chapter 7, pp. 146-185.
[6] Nordell L.K., Potapov, A.Y., and Herbst, J.A. “Comminution simulation using discrete element method (DEM) approach - From single particle breakage to full-scale sag mill operation,” International Conference on Autogenous and Semiautogenous Grinding Technology (SAG2001), 30 September-3 October, Vancouver, BC, Canada, Vol. 4, pp. 235-251.
[7] M. Baghdasaryan A Model for Forming the Moment of Resistance Created by the Ore Grinding Mill / Problems of Applied Mechanics, Tbilisi, 2002, N 1 (7), pp. 58-61
[8] M. Baghdasaryan On Working out a Model of the Active Power Consumed by the Ore Grinding Mill / Proceedings of NAS, RA and SEUA. Series: ES, -2002, vol. 55, N 1, pp. 84-88.
[9] Albert, J.H. Bayesian estimation of the polychoric correlation coefficient. Journal of Computation and Simulation, 1992, vol. 44, pp. 47-61.
[10] Drasgow F. Polychoric and polyserial correlations. In Kotz L, Johnson NL (Eds.), Encyclopedia of Statistical Sciences. 1988, Vol. 7, New York, pp. 69-74.
[11] Andersen, E. B. Latent regression analysis based on the rating scale model. Psychology Science, 2004, 46(2), pp. 209-226.