Research On Slab Temperature Modeling Method Of Reheating Furnace

As one of the important equipment in the production line of steel rolling, the main purpose of reheating furnace is to make slabs heat to the temperature that can comply with requirements. In the actual industrial production, reheating furnace is the main energy consumption equipment on iron and steel industry. Thus, it is essential and beneficial to research on mathematic modeling and control of the reheating furnace to improve heating efficiency and reduce energy consumption for steel industry.This paper does the research on regenerative reheating furnace system. Firstly, a temperature model is established to measure the distribution of temperature in the furnace. Then, a slab temperature prediction model based on heat transfer mechanism is studied. Aiming at the prediction model that based on single total heat exchange factor can not explicit the actual condition of reheating furnace, the model is modified and a prediction model based on three total heat exchange factors is proposed in this paper.The total heat exchange factor is vital to improve the precision of the model. As the theoretical calculation of the total heat exchange factor is complex and cumbersome, genetic algorithm is applied to this paper to obtain the optimal total heat exchange factor. In order to overcome the non-stationary of total heat exchange factor, a fuzzy inference system is introduced to compensate the total heat exchange factor and enhance the adaptive ability of the model.Taking into account the actual demands of the industrial production, a monitoring platform software about furnace process control is designed in this paper. The platform software can complete functions like calculation of slab temperature in furnace, the optimization of model parameters and the optimize setting of furnace temperature, the off-line analog and calculation of the heating process of a slab, the tracking and correction of material and management of users.Simulation results indicate that compared with the slab temperature prediction model based on single total heat exchange factor, the model built in this paper can calculate the slab temperature quite accurately. The average absolute errors of slab temperature predicted by the modified model are within the 5℃ limits, which can meet the technological requirements. The platform designed in this paper can show the actual production situation precisely, it can also guide the users to control the process accurately and effectively which is helpful for high quality production.