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

Abstract

The invention discloses a method for predicting the dead stock column temperature of an iron-making blast furnace core and belongs to the field of metallurgical information processing. The method disclosed by the invention comprises the following steps of firstly, collecting and processing sample data; dividing the processed sample data into a training set and a test set; carrying out principal component analysis on the sample data of the training set, selecting variables according to the correlation between principal components and the variables, analyzing the correlation between sample features and target values by using a parson correlation coefficient, screening the selected variables, and carrying out ridge regression modeling according to the screened variables to obtain a ridge regression model; and then performing goodness-of-fit test on the ridge regression model, and verifying the effectiveness of the ridge regression model by using the test set. The method aims at overcomingthe defects that in the prior art, the calculation process of the furnace core dead stock column temperature of the large blast furnace is tedious and excessively depends on experience. The ridge regression model is established, so that the furnace core dead stock column temperature can be predicted. The calculation efficiency of the furnace core dead stock column temperature can be further improved.

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] The working conditions of the blast furnace hearth have an important and far-reaching impact on whether the blast furnace production can achieve the overall goal of "high efficiency, high quality, low consumption, and long life". As the source of all reduction reactions, the hearth is the focus of blast furnace production. From a short-term point of view, it affects the stability of the blast furnace condition and various economic and technical indicators of blast furnace production. In the long run, it directly affects the blast furnace. generation furnace age. The managers and producers of modern iron and steel enterprises always try their best to maintain the long-term stable operation of blast furnace production in ...

AI Technical Summary

Problems solved by technology

However, the disadvantage of this method is that there is a lack of multicollinearity among the sample features in the regression modeling process.

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