On-line dynamic optimization control method for converter steelmaking process based on data driving

Abstract

The invention discloses an on-line dynamic optimization control method for a converter steelmaking process based on data driving. The method comprises the following steps: building an off-line prediction model database; building a liquid steel temperature prediction model and a carbon content prediction model by use of a data driving method to obtain a corresponding relationship between operating variables and the temperature and carbon content of liquid steel in the converter steelmaking process; selecting a melt data unit matched with the information of the current converter steelmaking production process and determining a control reference curve of the liquid steel temperature and carbon element content; building a real-time dynamic optimization model of the converter steelmaking process and determining an optimized set value unit of each operating variable; and selecting the set value of each operating variable from the optimized set value unit so as to carry out control operation. The method disclosed by the invention can be used for realizing real-time on-line control over the converter steelmaking process and providing convenience for an operator to set selection conditions according to actual working conditions, thus the production efficiency of a steelmaking plant is improved.

Description

technical field [0001] The invention belongs to the technical field of process control in the metallurgical industry, and relates to a data-driven online dynamic optimal control method for a converter steelmaking process. Background technique [0002] The output of converter steelmaking accounts for more than 80% of the current total steelmaking output, and the control of steel in the converter steelmaking process is an important condition to ensure the quality of molten steel. [0003] Converter steelmaking production process and main control process such as figure 1 shown. A certain amount of solid steel scrap and desulfurized molten iron are loaded into the converter body. Then, the oxygen lance on the vertical furnace bottom enters the furnace mouth from above, oxygen F011 is blown in from the gun mouth, and auxiliary raw materials such as limestone and dolomite F001-F007 are added at the same time, and nitrogen and inert gas F012 are blown into the furnace bottom for ...

AI Technical Summary

Problems solved by technology

The trend of temperature and the content of each element in the steelmaking system of Nippon Steel and Siemens is also for the purpose of forecasting, and the trend of temperature and component content under the current smelting conditions is not clearly considered and used for smelting control.

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