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Research on Temperature Prediction Model of Molten Steel in LF

Author: GaoYan
Tutor: MaoZhiZhong
School: Northeastern University
Course: Control Theory and Control Engineering
Keywords: LF Temperature Prediction Parameter Identification Genetic Algorithms Online correction
CLC: TF769
Type: Master's thesis
Year: 2008
Downloads: 93
Quote: 0
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Abstract


In recent years, with the development of clean steel production and technological progress and continuous casting technology , refining technology and equipment rapidly growing popularity . Where LF is known for its excellent performance has been widely used in the actual production . The temperature of the molten steel is a very important process parameter in the LF refining process , LF of molten steel temperature is very important to control the quality of the steel and continuous casting operations carried out smoothly , and the forecast for the LF temperature of molten steel is of the conditions precedent to control the LF temperature of molten steel is an important foundation for the refining process computer control . However , in the LF the actual refining process , the high temperature of molten steel , detection harsh environment measurement of the temperature of the molten steel to become a problem in the steel industry . In particular, the molten steel continuous temperature measurement . So accurately forecast the temperature of the molten steel , has important practical significance . In this paper, LF molten steel and slag research system , the establishment of the overall heat balance by the first law of thermodynamics . Which the lining of the heat transfer ( including ladle side wall and underwrite ) were used to describe the cylindrical coordinates and Cartesian coordinate of the one-dimensional non- steady heat conduction differential equation and its initial condition and third boundary conditions , finite difference method Solution. Then , based on the overall heat balance derived LF molten steel temperature prediction model to forecast the temperature of molten steel in the temperature throughout the refining process from the first moment after . For the need in the model is run under actual production conditions Steel bags lining layers of material of the thermal properties of parameters ( thermal conductivity and the ratio of thermal capacity ) is difficult to precise determination of deficiencies , from the entire model departure , using genetic algorithm of global search ability and good global optimize performance, the model is difficult to determine the thermal parameters identification, thermal properties of the model under actual production conditions required parameter values ​​. To verify the prediction precision of the actual refining process simulation results show that the model correctly reflects the LF refining process heat transfer law , the forecast results truthful and reliable . Finally, the use of rolling correction technology online correction LF Temperature Prediction Model to ensure that the model is able to adapt to different working conditions .

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CLC: > Industrial Technology > Metallurgical Industry > Steelmaking > Liquid steel in secondary refining and furnace processing
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