Research On Optimization Methods Of Furnace Temperature In Walking Beam Reheating Furnace With Operating Mode’s Switch

Reheating furnace production process is the key process in the steel’s hot rolling production process. For the aim that the billets in the reheating furnace must satisfied the requirements of the rolling technology, the reheating furnace operation should be optimized those set-point values of the temperature of different part of it respectively and billets’ forward speed to maximize the capacity of reheating furnace under the constraint of quality.The present way of work is due to the workers’experience, and makes it unable to provide the optimal operation value. The objective of the reheating furnace’s temperature-optimization is to realize the reheating furnace’s optimal operation by given the temperature and walking speed, which is under the essential technologies and the resource constraints, and the aspects of the overall optimization.Reheating furnace’s working process is slabs’ heating process. The heating process can be described by nonlinear heat transfer partial differential equation and partial differential equation. There are so many uncertainty factors such as the initial temperature, the types and specifications of the steels, makes that the product process exist strongly uncertainty and dynamic characteristic.Firstly, this paper analyzes and describes the production process and the temperature’s optimization of reheating furnace, and then formulates the slabs’temperature model which is based on heat exchange theory between slabs and furnace, the steady state work conditions index model and constraints model which are based on the furnace’s temperature optimize problem in this conditions. On the basis of the methods of normalize and weighting the operation index, the discretization of the heat transfer equation, this paper designs the interior-point algorithm which is used for solute the temperature optimization of furnace.Then, the optimal ascend curve belongs to the slabs in the furnace and the corresponding optimal temperature curve distributed in the furnace are got. Indeed, the optimal temperature forecasting curve can be got too. While, the optimization setting of the temperature in the furnace is achieved, and the consumption of heating energy is rapidly reduced.