Automation on thermal control of blast furnace

Intelligent Prediction and Real-time Monitoring System for Gas Flow Distribution at the Top of Blast Furnace

“…To address the problems of the conventional blast furnace GFD prediction and identification models mentioned in the introduction, a multi-algorithm fusion of BOX-WD, LSTM and FCM was used to establish a blast furnace GFD intelligent prediction and real-time monitoring system. In the experimental process, (1) All the above experiments were implemented in Python on a computer with AMD Ryzen7 4 800 H 3.6 GHz and 16 GB RAM. To measure the merit of the experimental results, R 2 , MSE, MAE, SSE, SC and training time were used as the evaluation criteria for each prediction model.…”

“…Ran LIU, 1) Wei-guang ZHAO, 1) Song LIU, 2) * Xiao-jie LIU, 1) Xin LI, 1) Zhi-feng ZHANG, 1) Jun ZHAO 3) and Qing LYU 1) 1) College of Metallurgy & Energy, North China University of Science and Technology, Tangshan, 063021 China. 2) Institute of Artificial Intelligence, Tangshan College, Tangshan, 063002 China.…”

“…The blast furnace is the core equipment in the steel production process, which affects the product quality and energy consumption of the steel industry, and maintaining the stable smooth running of the blast furnace is the common goal pursued by the whole steel industry. 1) The blast furnace top gas flow distribution (GFD) is one of the main factors affecting the production condition of the blast furnace, and a reasonable GFD is conducive to the smooth running of the blast furnace, high production and lower coke ratio, Therefore, it is very important to grasp and predict the GFD in real time. However, the blast furnace is in a "black box" state during operation, and there are thousands of operating parameters involved in the long process of blast furnace production from raw material feeding to product discharging, so the adjustments made by manual analysis of GFD results often have serious lags.…”