Closed Blast Furnace Smelting Process Sinter Softening Point Of Intelligent Integrated Prediction Model

The softening point of sinter is a key factor that affects the smelting process of Imperial Smelting Furnace (ISF). The softening temperature of sintering is an importance parameter that influences the outputs of the ISF, which affects not only the distributing of soft-melting zone and permeability in ISF, but also the furnace status and blast time.The complexity of softening point of sinter decides that the classical models cannot meet the control precision requirements. So, an intelligent model integrated with the NN model and the linear regression model is presented in this paper, which is based on the least square optimal weights arithmetic. This method resolves the disadvantages of NN and linear regression, and rebuilds a relation model between the softening point of sinter and the ingredients of sinter. The simulation and practical running results not only show that the results of the model can satisfy the requirements of the site, but also prove that this intelligent integrated model is feasible.Firstly, the problems of the sintering process of ISF are briefly described in this paper. Secondly, the linear regression model, the NN model and the intelligent integrated model among the softening point and the ingredients of sinter are presented based on the study of the mechanism analysis and the simulation results are given. Finally, it is introduced the conclusion of this project, the development and the application of the system software.