Prediction of Molten Steel Temperature in Steel Making Process with Uncertainty by Integrating Gray-Box Model and Bootstrap Filter

• Ahmad Iftikhar

  Department of Chemical Engineering, Kyoto University

• Kano Manabu

  Department of Systems Science, Kyoto University

• Hasebe Shinji

  Department of Chemical Engineering, Kyoto University

• Kitada Hiroshi

  Nippon Steel and Sumitomo Metal Corporation, Ltd.

• Murata Noboru

  Department of Electrical Engineering and Bioscience, Waseda University

Abstract

Stable operation of a continuous casting process requires precise control of molten steel temperature in a tundish (TD temp), which is a container used to feed molten steel into an ingot mold. Since TD temp is implicitly controlled by adjusting molten steel temperature in the preceding secondary refining process (RH temp), a model relating TD temp with RH temp is required. This research proposes a procedure to predict the probability distribution of TD temp by integrating a gray-box model and a bootstrap filter to cope with uncertainties of the process. The derived probability distribution is used not only to predict TD temp but also to evaluate the reliability of prediction. The proposed method was validated through its application to real operation data at a steel work, and it was confirmed that the developed model satisfied the requirements for its industrial application.

Journal

• JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

  JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 47 (11), 827-834, 2014

  The Society of Chemical Engineers, Japan

Keywords

• Gray-Box Modeling
• Steel Making Process
• Process Uncertainty
• Bootstrap Filter

Details

• CRID: 1390001204569044608
• NII Article ID: 130004703868
• NII Book ID: AA00709658
• DOI: 10.1252/jcej.14we067
• ISSN: 18811299
• ISSN: 00219592
• NDL BIB ID: 026001521
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I026001521
• Web Site: https://www.jstage.jst.go.jp/article/jcej/47/11/47_14we067/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed