Closed Blast Furnace Conditions. Prediction Model Based On Zinc Production Optimization Study

Imperial Smelting Furnace (ISF) smelting process is a very complex system with nonlinearity, time variety, coupling and uncertainty and very difficult to express conventional mathematics functions. It is important to do research work on operational optimization of ISF status based on Zn-output by applying control theory into ISF smelting process, which can improve the productivity, reduce pollution and make plants more competitive.Some problems based on principle of ISF smelting process are analyzed and an operational optimization approach of ISF status based on Zn-output forecasting model is presented. Original samples are normalized, noise samples are filtrated and the mechanism analysis and Principal Component Analysis (PCA) are applied to the historical sample data to select variables used for modeling. Multivariate Linear Regression forecasting model is formed to predict the Zn output. An estimation model using the Expert Rules method is formed to evaluate the ISF status. Combining the mechanism analysis with Fuzzy Clustering technique, an optimization and decision-making model about operating parameters in the ISF smelting process is built.On the research mentioned above, a system of ISF smelting process status evaluation and operation optimization is developed. The structure and function of system are presented. Software is also designed. The system software, developed by VC, realizes functions of main monitoring, ISF status prediction, operation optimization, data query and help. Debugged and run in the plant, the precision and reliability of the software have been proved.