The Study On The Technology Of BOF Oxygen Supply And Model Development

The oxygen decarbonization is the most important step in the converter steel-making.The effective budget of oxygen consumption is very important for the control of the carbon content at the endpoint of the converter and the temperature of molten steel.Based on the field test,this study has analyzed the influencing factors of the oxygen consumption of the converter,and established an artificial neural network budget model for oxygen consumption and blowing time of converter smelting combined the metallurgical calculation model and the intelligent control method.Firstly,the irreversible thermodynamic velocity equation of the decarburization process was obtained based on the non-equilibrium thermodynamics study on the decarbonization process of converter steelmaking.Then,an empirical model of the converter blowing time had established,which could be a guidance for the determination of on-site blowing time.The metallurgical calculation model of the oxygen consumption of the converter was established by using the intelligent steelmaking model and converter material balance principle,and this model was applied to on-site production to verify its effectiveness,within the range of allowable error ±200m3 oxygen consumption,the metallurgical calculation model's budget hit rate reached 60.7%.In order to more accurately control the oxygen consumption and blowing time of the converter's static blowing process,this study analyzes the influencing factors of the oxygen consumption of the converter based on the Tianjin steel field test.The influencing factors mainly include the gun position,oxygen supply intensity,oxygen pressure and slag.The mechanism of each factor's effect on oxygen utilization efficiency is studied from the perspective of the molten pool dynamics and the carbon and oxygen reaction process,it was found that low gun position,high oxygen pressure and high oxygen supply intensity,and low slag amount are conducive to the improvement of oxygen utilization efficiency and reduction of oxygen consumption,and the equation of action of the gun position on oxygen utilization efficiency is established,and the equation is ?_O2=1-0.273(H_??/(H_max)².Finally,a budget model for the oxygen consumption and blowing time of the converter has established by using a BP neural network development tool inMATLAB based on the oxygen utilization efficiency of converters.It is determined from the perspective of material balance,heat balance,and oxygen utilization efficiency of converter steelmaking.The main factors of oxygen content are taken as the input variables of the model.The neural network is trained by use history information of the converter to adjust and optimize the network structure and process parameters,and the field test data is collected to verify the accuracy of the model.The results show that the BP neural network model of oxygen consumption and the blowing time based on the MATLAB are more accurate in predicting the oxygen consumption of the converter,and the end-point hit rate is higher,in the allowable error of ± 200m3 oxygen consumption,the BP neural network model hit rate of 73.3%.