Data Fusion Based Quality Monitoring and Control of Strip Thickness

Abstract

This paper first introduces the principle of AGC and conventional AGC in Hot Strip Mill (HSM). A linearized and discretized state-space model used for rolling force and thickness control is obtained by using recursive squares method. A data fusion algorithm based on Kalman filter is presented. For hot strip systems with complex multi-variables, an asynchronous fusion estimation algorithm is built and applied to the thickness prediction of the hot strip mill and the plasticity coefficient Q of strip prediction. Finally, real-time prediction on thickness and plasticity coefficient of the coming strip is synthetically utilized in hot strip rolling thickness control system, to improve the quality of final coming strip thickness.