Method for predicting temperature of dead stock column of iron-making blast furnace core

Abstract

The invention discloses a method for predicting the temperature of a dead stock column of a furnace core of an iron-making blast furnace, which belongs to the technical field of metallurgical information processing, and comprises the following steps: collecting and preprocessing sample data, extracting features based on a maximum information coefficient, dividing a training set and a test set to obtain a data set 1, and representing the change trend of each column of the data set 1 in a time sequence by 1 or-1, obtaining a data set 2; fitting a regression model of the parameters and the furnace core dead stock column temperature on the data set 1 by using a ridge regression method, and analyzing correlation of a change trend on a time sequence on the data set 2 by using a Gaussian kernel support vector machine; adjusting the prediction result of the regression model reasonably in combination with the analysis of the change trend to reduce the prediction error. A single ridge regression model is combined with a change trend analysis method, and the model is optimized by using data time sequence information, so that the prediction error of the temperature of the dead stock column of the furnace core is further reduced, the calculation precision is improved, and the invention has very high practical application value.

Description

technical field [0001] The invention relates to the technical field of metallurgical information processing, in particular to a method for predicting the temperature of a core dead material column of an ironmaking blast furnace. Background technique [0002] Ironmaking is an important process of iron and steel smelting, and plays an important role in the iron and steel industry. The conditions and service life of ironmaking blast furnaces are of great research value. The blast furnace life is affected by many factors, among which the hearth area has a great influence on the operation and life of the blast furnace. The stable operation of the blast furnace requires that the temperature in the furnace is within a reasonable range, and the raw materials are fully burned to ensure the quality and efficiency of tapping. Therefore, it is very important to analyze the state of the hearth accurately in real time. For this, some researchers have proposed to use the activity of the h...

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is: how to solve the problem that the model in the existing forecasting method is to fit the overall data, resulting in relatively large local errors, which is mainly manifested in the change trend of the predicted value of the temperature value of the furnace core dead material column compared with the actual value at the previous moment. To solve the problem that the value is different from the previous moment, a method for predicting the temperature of the dead material column in the core of the ironmaking blast furnace is provided. The data studied by this method is a time series. The association of the column temperature change trend can adjust part of the predicted value of the regression model according to the correct change trend, further reduce the error, and optimize the prediction result of the dead material column temperature of the ironmaking blast furnace core

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