Blast furnace molten iron temperature prediction method, device, equipment and medium
By using a long short-term memory neural network model to screen and process characteristic parameters related to blast furnace molten iron temperature, the problem of insufficient adaptability and accuracy of time-series data processing in existing technologies is solved, and high-precision prediction of blast furnace molten iron temperature is achieved, adapting to complex and ever-changing production conditions.
CN122133425APending Publication Date: 2026-06-02LOUDI HUALING YUNCHUANG DIGITAL TECHNOLOGY CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- LOUDI HUALING YUNCHUANG DIGITAL TECHNOLOGY CO LTD
- Filing Date
- 2025-12-30
- Publication Date
- 2026-06-02
Smart Images
Figure CN122133425A_ABST
Abstract
This application discloses a method, apparatus, equipment, and medium for predicting blast furnace molten iron temperature, relating to the field of blast furnace smelting technology. The method includes: selecting characteristic parameters related to molten iron temperature from blast furnace operating data, performing time-series alignment and minimum-maximum value normalization to obtain standardized time-series characteristic data. Then, the normalized data is input into a preset temperature prediction model, ultimately outputting the predicted molten iron temperature. Through precise feature selection and data preprocessing, the method effectively captures the time-series characteristics of molten iron temperature, improving the robustness and generalization ability of the model, and enhancing the accuracy, time-series adaptability, and generalization ability of molten iron temperature prediction, thus better adapting to the complex and ever-changing production conditions of blast furnaces.
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