Intelligent Prediction And Online Control Of Molten Steel Temperature Model In200T Ladle Furnace During Refining

With the rapid development of the steel industry, the application of automation is also increasing. The automatic steel-making has become prevalent in modern steel industry. The model for molten steel temperature prediction during LF refining process contributes much to improve the level of temperature controlling, decrease production costs, enhance the productivity and the quality of strand for steel plants. In this paper, a200tons ladle furnace was chosen as the research object, and an online prediction model for molten steel temperature during the refining process was established based on the statistics of production date and the numerical simulation. With the function of automatic correction, the model has been successfully applied to the plant. The main research work and results are as follows:(1) Numerical simulation was carried out with the CFD software Fluent to investigate the flow field during the refining process, and the results shows that with the increase of gas rate, the mixing time becomes shorter. Additional argon flow rate has no significant effect on the mixing time when the gas flow rate reaches600NL/min. The critical argon flow rate for exposing a100mm thick slag layer ranges150NL/min to200NL/min. As the argon flow rate increases from200NL/min to500NL/min, the corresponding diameter of slag hole increases from320mm to520mm.(2) The numerical simulation results of the heat transfer shows that the thermal status of the ladle has a significant effect on heat loss of the ladle lining and the temperature drop of molten steel. Grade ladle D (on line ladle) has a0.7℃/min temperature drop rate caused by the heat loss of ladle lining. Compared with the grade ladle A(new ladle), there are about30℃difference of molten steel temperature drop within35min and0.75℃/min difference of the average drop rate of steel temperature. According to the above results, Origin was used to fitting different thermal status of the molten steel temperature drop. The form of fitting equations is:△Tlining=a+bt-ct2+dt3-et4Where a, b,c, d,e are constants(3) According to the results of numerical simulation, the fitting equation of the exposed area with argon gas flow was established.meanwhile, the temperature drop caused by heat radiation rate can be calculated.(4) Combining the research of numerical simulation and production statistics, intelligent prediction model for molten steel temperature was established during LF refining process, the model can adjusts the heating time automatically and calculates heating time according to the heating gears and uploads data. The results of model verification shows that molten steel temperature predicated by the model is almost close to the real temperature the hit rate has achieved82%and90%when the relative error within±5℃and±10℃. The predicated temperature and the actual steel temperature are in good agreement, indicating the model can meets the practical requirements well.