Research Of Control Models For Hot Strip Mill Laminar Cooling System

Laminar cooling is a part of the technique for the control of rolling and cooling, it effects the tissue and properties of plate directly. So laminar cooling process plays an important role in hot plate production. The control accuracy of the coiling temperature of the hot plate laminar cooling system is the plate mill to guarantee the better quality and flatness of plate. This paper takes a laminar cooling system of hot plate mill for ShouGang QianGang2250mm, and has a deep study for how to raise the accuracy of cooling temperature of the hot rolled plate.First, ShouGang laminar cooling control model in several important modules is introduced. The pre-set module is completed by the pre-computed model, that is to say, the strip finishing mill provides information and data, then application of pre-set model calculates control of the strip head, the value of message is sent to basic automation system, from an automated system to perform, which can effectively eliminate the entire cooling system control actions lag effect. The main task of real-time control module is to monitor the actual state of the cold layer, based on the size of slab, the heat transfer coefficient and the current operating environment are calculated to achieve the target set of valves coiling temperature. Adaptive control module based on the current strip coiling temperature measured and calculated values of the deviation between the signal and process output adjustable system influent the feedback, then the parameters of the controller is modified, so that the control error tends to zero.Second, through the systematic analysis, raised issues:temperature control dead zone caused by improper temperature settings range is overshoot, the coiling temperature of pipeline steel cannot be automatically controlled, coiling temperature feedback control and self-learning control cannot be inputted, the pre-computed deviation is too large. Third, by configuring the appropriate equipment and setting valve failure, according to the pyrometer measured temperature, the model automatically feedback controls, thus ensuring the feedback control is input to the model used to solve a real-time feedback control, which cannot be put into use in the calculation the problem, in order to ensure participation from the study of strip segments, the middle model and coiling pyrometer temperature greater than or equal to the average temperature of100degrees, so that ensuring the data block strip is successfully written to the self-study documents, for the late correction of pipeline steel rolling, thus ensuring the success of self-learning function is used.Finally, the optimization of laminar flow cooling system control functions, which solves the problem in this paper and through field application, achieves the target.