Establishment of Three-Section Billet Temperature Prediction Model

In the metallurgical industry, measuring the temperature distribution directly and accurately in billet heating process is a well-known difficult work. To improve the quality of heating billet, a billet temperature prediction model of heating furnace is necessary. This paper combined with the furnace section partition control characteristics, establish three-section billet temperature prediction model based on modified BP neural network, and then use the L-M algorithm to improve the model. The simulations results show that this model can be roughly predict the billet temperature trend. Forecast precision is improved, small fluctuation, prediction curve and actual curve fitting degree is high. All of these proved that this model is effective.