An Intelligent Temperature Prediction Method Based on PSO-ELM

The tuyere raceway is a very complex area in the process of blast furnace (BF) smelting and an important reaction area for stable operation of BF. Stable and accurate detection of combustion states in this area extremely important for the quality of molten iron, maintaining an active hearth, running the furnace smoothly, and extending the life of the furnace, it determines the heat demand of the BF and tons of iron fuel consumption. Therefore, the PSO-ELM method is proposed to study the change of tuyere raceway temperature. In this method, PSO is used to select the optimal parameters of the ELM model and ELM is used to predict the temperature quickly. Finally, the effectiveness of the proposed method is validated by using BF data. The experimental results show that this method can accurately predict the tuyere raceway temperature.