Prediction of molten steel temperature in steel making process with uncertainty by integrating gray-box model and bootstrap filter

Iftikhar Ahmad, Manabu Kano, Shinji Hasebe, Hiroshi Kitada, Noboru Murata

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)827-834
Number of pages8
JournalJOURNAL OF CHEMICAL ENGINEERING OF JAPAN
Volume47
Issue number11
DOIs
Publication statusPublished - 2014 Jan 1

Keywords

  • Bootstrap filter
  • Gray-box modeling
  • Process uncertainty
  • Steel making process

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)

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