Mechanism-data hybrid driven model building method for RH decarbonization
ZHOU Chunhao1, HE Yang1, LIU Jianhua1, YANG Fei2, XIAO Min3, YUAN Jing3
1. National Engineering Research for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing 100083, China; 2. School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China; 3. Xinyu Iron and Steel Co., Ltd., Xinyu 338001, Jiangxi, China
Abstract：RH refining is one of the important processes in smelting ultra-low carbon steel, in which the control of carbon content is particularly important. A mechanism-data hybrid driven model for RH decarbonization was proposed to improve the accuracy and generalization of RH decarbonization model. Firstly, in order to get closer to the operation of oxygen blowing in the actual production process, the oxygen assumption during RH process was predicted by just-in-time algorithm. Then, the weight parameters of decarbonization at different sites were introduced into the decarbonization formula, and the parameter values were determined by just-in-time algorithm combined with historical data. Finally, mechanism-data hybrid driven model was built by substituting the weight parameters into the decarbonization mechanism model, which was adopted to predict the carbon content during RH process. The results show that the hybrid model for RH decarbonization has higher prediction accuracy compared with the traditional mechanism model. The hit rate is 89% for the oxygen blowing predicted error within ±10 m3, and the hit rates are 100% and 78% for the carbon mass fraction predicted error within ±5×10-6 and ±3×10-6, respectively. This model could provide reference for field operators.
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2023, Vol. 33 
