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

研究成果: Article査読

7 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)827-834
ページ数8
ジャーナルJOURNAL OF CHEMICAL ENGINEERING OF JAPAN
47
11
DOI
出版ステータスPublished - 2014

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)

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