Optimization Technology of Blast Furnace Ironmaking Process Based on Particle Swarm Optimization
In order to realize the optimization of blast furnace ironmaking process and improve the pass rate of producing pig iron,an optimization method of blast furnace ironmaking process based on particle swarm algorithm was proposed.Taking the economic demand of blast furnace ironmaking production units as the function construction goal,this paper constructs the optimization objective function based on the smelting time level and cost level,introduces particle swarm algorithm,initializes iterative particles through design,and carries out different links or different processes in the blast furnace ironmaking process.The optimization of the process parameters realizes the design of the optimal processing and production parameters.Based on the multi-objective angle,the coordinated processing between the optimal solutions of the objective function is carried out,so as to complete the process optimization design based on multi-objectives.Taking a large blast furnace ironmaking enterprise in a certain area as an example,a comparative experiment is designed.The experimental results show that compared with the traditional method,the designed optimization method can not only improve the blast furnace utilization coefficient in the ironmaking process,but also improve the pig iron pass rate in practical application.
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