Study On The Inverse Calculation Of The Distribution Matrix In The Blast Furnace Distribution Process

In the complex blast furnace ironmaking process,the charging system is used as an upper adjustment method to adjust the operating state of the furnace condition in the blast furnace.Under the setting of the operating parameters of the distribution matrix,the spatial distribution of ore,coke and other furnace materials through the rotary chute at the throat of the furnace plays a decisive role in the rational use of gas flow and the stable forward movement of the blast furnace.According to the actual production situation of the blast furnace,adjusting the distribution shape of the formed material surface and giving the theoretical basis for the optimization calculation of the distribution matrix not only helps to guide the formulation of the distribution matrix on site,but also is an effective way to stabilize the blast furnace forward,save energy and reduce emissions.However,due to the imperfect mapping relationship between the distribution matrix and the distribution shape of the material surface,the formulation of the distribution matrix during the blast furnace charging process is still adjusted by the on-site foreman in conjunction with expert opinions.This adjustment mode is not conducive to real-time adjustment of the blast furnace Running status.In this paper,based on the mathematical description between the distribution of the material surface during the charging process of the blast furnace and the mapping relationship between the distribution matrix and the evaluation parameters of the optimal material surface and the radial ore coke ratio,the expected output surface shape distribution and the expected material layer are constructed.The two optimized models of thickness distribution provide the model basis for the inverse calculation and formulation of the burden distribution matrix.Based on the above two optimization models,this paper establishes an optimization method based on genetic algorithm through in-depth study of genetic algorithm when inverse calculation of the burden distribution matrix.In order to verify the accuracy of genetic algorithm optimization results,PSO algorithm that isalso suitable for solving this problem is introduced.When performing optimization calculations in this paper,the two optimization algorithms use the same population number and maximum iteration value,and use the measured data of industrial processes for simulation experiments.The results show that the genetic algorithm has a higher search accuracy when solving the inverse calculation of the cloth matrix,and the cloth matrix obtained by using the optimization model based on the genetic algorithm is more in line with the desired goal,and can be reasonably and effectively formulated.In the blast furnace smelting process,the decline of the charge has always existed,because the decline of the charge will cause the distribution shape of the material surface at the throat to change accordingly,so before formulating a reasonable distribution matrix,it is necessary to investigate the decline of the charge at the throat.The research shows that there is a difference in the actual descent rate of the charge in the radial direction of the blast furnace throat.Based on the conservation of mass,a mathematical model of non-uniform charge descent is established in this paper,and the accuracy of the model is verified by simulation experiments.Under the premise of the inverse calculation of the multi-ring distribution model,the charge decline model and the genetic algorithm-based distribution matrix,this paper presents the dynamic balance of the blast furnace distribution process,and through simulation experiments,the feasibility of achieving the dynamic balance of the blast furnace distribution is preliminarily verified.In the future,the formulation and adjustment of the distribution matrix during the blast furnace charging process will provide a certain theoretical basis.