Fuzzy Neural Network's Application in Furnace Temperature Compensation Based on Rolling Information Feedback

In hot rolling process, reheating furnace and roughing mill are controlled separately in general, and the transfer of production information between the two facilities is very limited, so rolling information of roughing mill can not be fed back to reheating furnace to adjust slab's heating process dynamically, which leads to exceeding energy consumption. In this paper, fuzzy neural network (FNN) is used to deal with the feedback of rolling information, and then real-time compensation of furnace temperature setting can be obtained. Simulation results show that by using this method slab's heating process can be optimized dynamically, and energy consumption of hot rolling process can be reduced greatly, and rolling security of roughing mill can be guaranteed at the same time.