Study On Intelligent Batch Decision-making Model Of 90t EAT In Steel Plant

The EAF steelmaking process have important position in recent years in China.The electric furnace steelmaking process have short process characteristics,low energy consumption,resource recycling and high thermal efficiency as compare to the converter steelmaking process.The raw material of EAF steelmaking is scrap,and the smelting process of scrap is an important process in steelmaking plant.The scrap smelting process has always been the frontier research field of electric arc furnace steelmaking,and still have many problems to be solved.Based on 90 t EAF smelting process as the research background,combined with electric arc furnace smelting process molten pool response characteristics,and application of mathematical model for numerical simulation method,the different production practice of smelting process in the electric arc furnace under the conditions of scrap melting time and yield process conditions to carry out the system research,such as intelligent ingredients arc furnace optimization model is established.The melting process and yield of scrap steel of different material types in a factory were studied by means of laboratory hot melting test.It is found that the yield of pulverized material and slag steel is small,61.35% and 46% respectively,and the rest are more than 94%.According to the data of more than 1000 furnaces produced,an optimization algorithm is proposed to correct the scrap yield in real time.When the optimal value is less than or equal to 1% of the variance,it is considered to be the scrap yield.Combined with the numerical simulation of scrap melting process,the influences of different process parameters,such as scrap material type,scrap preheating,scrap type and scrap shape,on the melting process of scrap are discussed.The simulation study on the batching scheme of scrap in a certain plant shows that the melting time of the same quality scrap in the furnace can be reduced by7.1min after optimized batching.The simulation results provide a clear and reliable basis for the batching process of scrap in the arc furnace.Based on thermal test and numerical simulation,a dynamic database of scrap yield was established.The intelligent batch model of optimal arc furnace is established in order to improve the quality of molten steel with the lowest cost energy consumption.Can real-time guidance arc furnace steel structure optimization,for factory scrap steel procurement and inventory optimization to provide the reference basis,can be used for online decision ingredients arc furnace optimization scheme,online generation time costs,electric arc furnace smelting furnace and benefit analysis.The results show that the average cost per ton of steel material consumption in electric arc furnace can save 12.1 yuan/t.through analyzing plant scrap raw material yield and scrap melting process parameters such as time study,in order to optimize the electric arc furnace production process parameters and improve the quality of molten steel and cost savings to provide a theoretical basis and practical guidance.