Intelligent Setting Method of Laminar Cooling Process for Hot Rolled Strip

Abstract

In order to improve the control accuracy of the coiling temperature of strip in the laminar cooling process when working condition is varying, an intelligent setting method of the cooling water volume is researched in this paper. The strip coiling temperature mechanism model is built firstly. Secondly, the key model parameters are identified with case-based reasoning (CBR) technology to improve the model accuracy. Lastly, the cooling water volume setting method based the model is proposed where disturbance input method is applied. The simulation result showed that the proposed method can improve the strip coiling temperature accuracy when the operation condition is changing. The strip coiling temperature accuracy can be improved due to the CBR technology which can adjust the key model parameters according to the varying operation condition. So, the setting values based the improved model are adjusted with the changing working condition, with self-adaptive ability.