Intelligent monitoring and control of mill load for grinding processes

Overload in mill is a work-situation fault that commonly occurred in grinding processes. This work-situation fault may cause the deterioration of the product quality and even a total collapse of the grinding production, if it is not detected and controlled in time. We propose an innovative approach for intelligent monitoring and control of the mill load(ML) using rule-based reasoning(RBR) and statistical process control(SPC) techniques. In this approach, we employ a SPC unit, a RBR-based ML monitoring module and an RBR-based supervisory controller to detect the imminent overload situation and automatically adjust the set-points of the control loops. The outputs of the controlled system track the modified set-points, making the ML deviate from the overload-situation gradually. The industrial application shows that this approach guarantees the grinding production of reliable and stable operations with less operational breakdowns.