Research On Rolling Force And Strip Shape Control Of Hot Strip Mill

As an important driving force of the national economy, iron and steel industry has been playing an indispensable role in the long-term development of the economy. As an important equipment to improve the quality of strip, the flat machine has been paid more and more attention, and has been widely used in the steel industry. Flatness is the main method to improve the quality of the plate shape, and the accurate prediction of the rolling force is the main factor to determine the quality of the plate shape.In this paper, the rolling force prediction model is used to predict the rolling force and the main influencing factors are determined. The prediction value of the rolling force is obtained by calculating the rolling force. The prediction model of BP neural network is put forward, which is based on the characteristics of on-line prediction of rolling force. Through the detailed introduction of BP neural network related knowledge, using MATLAB neural network toolbox for simulation, based on the actual production data of a hot rolling mill, the rolling force prediction results are obtained. Because of the shortage of the forecast value to meet the requirements of the plate shape control system for the rolling force prediction accuracy, this paper proposes a combination of gray theory system and BP neural network.In the end of this paper, the basic concept of plate shape, the relationship between rolling force and elongation is described. The relationship between rolling force and elongation is the basis of the selection of the control and rolling force of the rolling process.