Time delay neural network modeling for particle size in SAG mills

Particle size is a very important variable in semi-autogenous grinding processes. It is desirable to measure the variable efficiently or even predict its variations in advance. In this paper, the time delay neural network model is developed to predict the feed particle size of a semi-autogenous grinding mill, and the Levenberg–Marquardt algorithm is used to train the network. Results show that the model predicted values fit well with the industrial operating data. The proposed model can predict the particle size in advance and allow adequate time to take corrective actions during abnormal operations, and therefore provide a great advantage in monitoring and control of the industrial processes.