| A study is described with the objective to create models that can be used in a general system for prediction of steel temperature in the ladle. The effort has been concentrated on the thermal status of the ladle and its effect on the heat loss of the steel. With the practical results, the effects of influencing factors on the heat states of 300t ladles and molten steel temperature in production cycles at BAOSteel were analysed, and the main influencing factors were discovered.In allusion to the problem of large variation range of the factors affecting on ladle hot states in production cycles, the ladle hot behavior in production cycles was mathematically simulated by the finite difference method and the effects of different kind of influencing factors on ladles hot behavior were studied. The on-line model to predict the temperature of molten steel was obtained by the many-factor regressed method and based on this, the temperature prediction system was established. By combining the actual situation, the calculated and measured values were in a good agreement. The theoretical basis for qualified molten steel production and dynamic control of steel temperature is thus provided. On accout of the use of the model, the final temperature could be exactly predict, the results were: the hitting rate within a tolerance of ±5℃ and ±10℃ is 80% and 90%.The adaptive computer intelligent static model system has been established based on database of SQL Server2000 and Delphi. The model can form training set automatiocally and adjust automaticly according to time and adjust according to the production conditions, and predict molen steel temperature.
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