Predictive system for blast furnaces by integrating a neural network with qualitative analysis

Abstract

Silicon content in pig iron has long been used as one of the most important indices to represent the thermal state of a blast furnace. In this paper, a predictive system for blast furnaces by integrating a neural network with qualitative analysis is presented. The qualitative trend of the process in blast furnace is predicted through causal analysis and qualitative reasoning, and the relevant variables as the inputs of a neural network model are determined. Then, a neural network model is constructed and trained with appropriate data. Evaluation of the system is made by comparing the predicted values with observed data (totally 610 heats are included), and the performance of the system is excellent.