Blast furnace molten iron silicon content change trend prediction method, device and storage medium

Abstract

The invention provides a blast furnace molten iron silicon content change trend prediction method, a blast furnace molten iron silicon content change trend prediction device and a storage medium. Themethod includes the step that characteristic parameters during an iron making process which are related to silicon content change in blast furnace molten iron are acquired, and a silicon content change trend is predicted on the basis of trained blast furnace molten iron silicon content prediction models, wherein the blast furnace molten iron silicon content prediction models include a first layerprediction model and a second layer prediction model, wherein the first layer prediction model is used for preliminarily predicting the silicon content change trend according to an original sample, and the second layer prediction model predicts the silicon content change trend for the second time according to the prediction result of the first layer prediction model so as to obtain the silicon content change trend. According to the blast furnace molten iron silicon content change trend prediction method, the blast furnace molten iron silicon content change trend prediction device and the storage medium of the invention, a limit gradient enhancement and long-term and short-term memory network fusion model is established to predict the trend of the silicon content in the molten iron, a reference basis is provided for a blast furnace operator to judge the change trend of the condition of the blast furnace and control the amplitude of the blast furnace in advance, and therefore, the smoothness of the iron making process can be ensured, and the quality of the molten iron can be maintained within a normal range.

Description

technical field [0001] The present invention relates to the technical field of automatic control of blast furnace smelting, and more particularly, relates to a method, equipment and storage medium for predicting the change trend of silicon content in blast furnace molten iron. Background technique [0002] Blast furnace smelting is a continuous production process, the operation of the furnace is complex, and there are many physical and chemical reactions. Blast furnace temperature, that is, the temperature of molten iron in the hearth, is one of the important parameters to measure the condition of the blast furnace. If it is too high or too low, it will cause the quality of molten iron to decline and the furnace condition to be unsatisfactory. The furnace temperature is low, the physical heat of molten iron is insufficient, and the heat reserve of the hearth is insufficient, which may easily cause hearth freezing accidents; the furnace temperature is high, and the gas flow i...

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Problems solved by technology

[0005] The present invention provides a method, equipment and storage medium for predicting the change trend of silicon content in blast furnace molten iron, which overcomes the above problems or at least partially solves the above problems, and solves the problem of silicon content trend prediction methods in the prior art. The difference between the two heats before and after is used to define the trend. The division method is relatively rough and cannot reflect comprehensive information, and the accuracy of the model used for forecasting cannot be guaranteed.

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