Visualization of the controller states of an autogenous mill from time series data

In addition, the operational variables could be used as reliable predictors in a neural network model to identify the controlled states of the mill. As a complementary approach to visualization of the operation of the mill, a different neural network model could be used to reconstruct a corrected power load curve by compensating for the effect of varying operating conditions.