Dynamic modeling and simulation of a SAG mill for mill charge characterization

Abstract

The modeling and simulation of semiautogenous (SAG) mills have been widely used in the design and optimization of mill performance in terms of its power draw, processing capacity and product size distribution. However, these models are solved under steady approximation and do not provide any information on mill charge distribution in real time. This paper attempts to characterize mill contents by solving Whiten’s first-order content-based model in the MATLAB/Simulink environment. The parameters in the model, such as breakage rate constant, discharge rate and appearance function, were estimated using process and design data collected from a gold mine operating in Alaska coupled with a nonlinear parameter estimation scheme. This model was then used to predict the dynamic responses of other key operational variables, such as mill power, bearing pressure, charge level and product size distribution. The transient response of mill behavior with respect to changes in feed size distribution, tonnage and mill feed water is also presented. This dynamic simulation approach can be used for practicing different control strategy and training purposes. The observed response of mentioned variables was validated using dynamic response data from the plant to encompass operational characteristics of SAG mill behavior.