Design And Implementation Of Iron Ore Matching System Based On.NET

To improve the comprehensive utilization of iron ore and reduce the cost of iron smelting,this paper developed the iron ore matching system based on the.NET platform under the background of the actual puddling process of an steelworks.The system mainly includes three core functional modules: iron ore evaluation,sintering ore blending and blast furnace burden.In the iron ore evaluation module,a complete iron ore evaluation system was established considering the relationship between the performance parameters of iron ore.The comprehensive performance and price of iron ore could be evaluated by the calculation results of the evaluation rules,guiding the purchase of iron ore.In the sintering blending module,the linear programming model and the quality prediction model of sintering were established,taking into account the relationship between various substances in the sinter.The simplex method and BP neural network algorithm were used to solve the model respectively,therefore the ore-blending scheme and quality prediction effect under the lowest sintering cost were obtained.In the blast furnace burden module,the linear equation group of batching were established according to the relation between the raw materials.The raw material cost,slag composition and molten iron cost of the blast furnace were predicted by solving the unknowns in the equations,thus determining the lowest cost of the blast furnace batching program.In this paper,the iron ore matching system was designed and implemented based on the real data and requirements in the puddling process of steelworks.The operation results show that the iron ore matching system could not only evaluate the comprehensive properties of iron ore quickly and reasonably,but also provided the procurement suggestions and proportioning schemes scientifically.This system improved production efficiency of steelworks,reduced the iron-making cost,and provided theoretical basis and technical support for strengthening the intelligent management of iron-making process.