Large scale database-based online modeling using ICA of visualized process data for blast furnace operation

Y. Hijikata*, J. Mori, K. Uchida, H. Ogai, M. Ito, S. Matsuzaki, K. Nakamura

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


The large scale databace-based online modeling, called LOM, is a type of Just-In-Time modeling for blast furnace. The database of LOM is so far built by quantizing directly measurement process data. Recently it has been shown that the image data generated by visualizing shaft pressure and stave temperature is very useful for blast furnace operation and guidance. In this paper we try to extend LOM to the one incorporated with the visualized process data. First we extract features of the visualized process data by using independent component analysis (ICA), and add the features (independent components) of the visualized process data, as process data, to the database of LOM. Prediction performance of the extended LOM is illustrated by using real process data.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Number of pages4
Publication statusPublished - 2006 Dec 1
Event2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
Duration: 2006 Oct 182006 Oct 21

Publication series

Name2006 SICE-ICASE International Joint Conference


Conference2006 SICE-ICASE International Joint Conference
Country/TerritoryKorea, Republic of


  • ICA
  • JIT modeling
  • Prediction
  • Process control

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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