An energy efficient decision-making strategy of burden distribution for blast furnace

Abstract Burden distribution plays an important role in the optimization of energy-consuming index of a blast furnace (BF). However, due to the complex mechanism of the burden distribution process and the poor understanding of this process, it is difficult for operators to make a suitable decision for burden distribution parameters. In this paper, a decision-making strategy of burden distribution parameters is devised for improving energy-consuming index, where carbon-monoxide utilization rate (CMUR) is taken as the energy-consuming index. Firstly, the support vector regression is used to build a model between the burden distribution parameters and BF state variables that are closely related to CMUR. Then, a probability-based case-matching model is built by the historical data to predict the trend of CMUR’s change. Finally, based on the trend of CMUR’s change, a decision for burden distribution parameters is obtained. Simulation results based on industrial data show that the devised decision-making strategy provides a good guide on making a suitable decision for burden distribution parameters.