Mathematical model for cooling process and its self-learning applied in hot rolling mill

Abstract

Control precision of coiling temperature is one of the key factors affecting the profile shape and surface quality during the cooling process of hot rolled steel strip. For this reason, the core of temperature control precision is to establish an effective cooling mathematical model with self-learning function. Starting from this point, a cooling mathematical model with nonlinear structural characteristics is established in this paper for the cooling process of hot rolled steel strip. By the analysis of self-learning ability, key parameters of the mathematical model could be constantly corrected so as to improve temperature control precision and adaptive capability of the model. The site actual application results proved the stable performance and high control precision of the proposed mathematical model, which would lay a solid foundation to improve the steel product qualities.