The Application And Research Of Intelligent Control About Temperature Predict Inside Blast Furnace

The puddling of blast furnace plays an important part in iron and steel industry which is stanchion industry of country economic.The temperature of blast furnace ensures that the blast furnace could work steadily,which is an important guideline of estimating condition.How to establish and realize the temperature prediction model has not only important theoretical value but also practical value.But from the theory of cybernation,the process of blast furnace is non-linearity system which has much difficulty in modeling.And the expression of temperature is especially harder.Because the silicon content of molten iron can indirectly reflect the change of temperature,this task choose the model of the silicon content of molten iron as the temperature model of blast furnace.First,this text summarizes the technical process of puddling of blast furnace,expatiate the produce value and technical difficulty of the temperature prediction.Then by analyzing the process of puddling,it ascertains important complication of influencing temperature,analyzes and pretreats these parameters.Then by analyzing time sequence model,illegibility control model and neural network model,it put forward an new mathematics model: time-sequence neural network model.Finally according to the data from locale,it experiments emulationally.The emulational result indicates: the mathematics model based on time-sequence arithmetic and neural network shoots straight in the temperature prediction, which shows rationality of this method and the feasibility of this model based on this arithmetic.