Evaluation model for comprehensive operation condition of vanadium and titanium blast furnace based on big data mining
LI Hongwei1, LI Xin1, LIU Xiaojie1, LIU Ran1, CHEN Shujun2, LÜ Qing1
1. College of Metallurgy and Energy, North China University of Science and Technology, Tangshan 063009, Hebei, China; 2. Chengde Vanadium Titanium, HBIS Group, Chengde 067102, Hebei, China
Abstract：The fluctuation of blast furnace conditions have a serious impact on the yield, quality of molten iron and energy consumption in the blast furnace production. A timely and comprehensive overview of blast furnace operating conditions to reduce furnace condition fluctuations is the key to maintaining stable and smooth blast furnace production. Based on the historical data of a vanadium and titanium blast furnace, a comprehensive evaluation model for the blast furnace operation is eastablised with the big data mining. Using the data warehouse of the blast furnace iron-making process, the related production data is collected and integrated, the null values and outliers of the raw data are processed, thus the clean data for the model is obtained. Combined with the process and expert experiences, 33 evaluation indexes characterizing the comprehensive operation condition of blast furnace are selected to carry out the evaluation system of the operation indexes for blast furnace. According to the combination weighting of analytic hierarchy process and entropy weight method based on game theory and the improved TOPSIS method, the AHP_EWM_TOPSIS model is established to evaluate the blast furnace operation. The comprehensive matching rate from the evaluation results verified with the actual production reaches 94.49%, which indicates this model could accurately evaluate the comprehensive operation of blast furnace and provide the timely and effective information for the operators. The statistical analysis of the blast furnace operation is carried out to derive the evolution of that. As the blast furance is operated well, the optimum operational parameters are summarised, which could further provide the operational basis and data support for the optimisation of blast furnace production. This model can quickly judge the real-time operation of blast furnace, and optimize the blast furnace production, as a result, the long-term stable operation of the blast furnace is obtained, and the production purposes include high quality, high production, low consumption, and long life of blast furance are realized.
李红玮, 李欣, 刘小杰, 刘然, 陈树军, 吕庆. 基于大数据挖掘的钒钛高炉综合运行状态评价模型[J]. 钢铁, 2023, 58(10): 51-66.
LI Hongwei, LI Xin, LIU Xiaojie, LIU Ran, CHEN Shujun, LÜ Qing. Evaluation model for comprehensive operation condition of vanadium and titanium blast furnace based on big data mining[J]. Iron and Steel, 2023, 58(10): 51-66.
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2023, Vol. 58 
