Inferential measurement of SAG mill parameter'

Semi-autogenous (SAG) mill total load and ball load have a marked influence an mill performance. Direct measurement of these inventories is difficult, hence inferential measurement is an attractive option to open the way to t heir control. Advances have been made in this area based on combined state and parameter estimation formulations, though there is still scope for furt her soft sensor development. This work investigates the use of mill powerdr aw and weight simulation models combined with the corresponding measured va riable (to form residual equations) to obtain estimates of total volumetric load fraction, J(b) and ball charge volumetric fraction, J(b), by the appl ication of a constrained nonlinear optimisation technique. The sensitivity of the estimates to model parameters and the uncertainty in the estimates a re investigated. Results show that, although all estimates illustrated good agreement with nominal conditions, the estimates from the weight-based mod els contained the least uncertainty. The inclusion of a mill finer wear mod el in combined stare and parameter estimation formulations is recommended d ue to the notable contribution of the liner weight to the mill weight measu red variable. (C) 2001 Elsevier Science Ltd. All rights reserved.