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

doi:10.1109/SICE.2006.315156

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

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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 language	English
Title of host publication	2006 SICE-ICASE International Joint Conference
Pages	4112-4115
Number of pages	4
DOIs	https://doi.org/10.1109/SICE.2006.315156
Publication status	Published - 2006 Dec 1
Event	2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of Duration: 2006 Oct 18 → 2006 Oct 21

Publication series

Name	2006 SICE-ICASE International Joint Conference

Conference

Conference	2006 SICE-ICASE International Joint Conference
Country/Territory	Korea, Republic of
City	Busan
Period	06/10/18 → 06/10/21

Keywords

ICA
JIT modeling
Prediction
Process control

ASJC Scopus subject areas

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2006.315156

Cite this

Hijikata, Y, Mori, J, Uchida, K, Ogai, H, Ito, M, Matsuzaki, S & Nakamura, K 2006, Large scale database-based online modeling using ICA of visualized process data for blast furnace operation. in 2006 SICE-ICASE International Joint Conference., 4108229, 2006 SICE-ICASE International Joint Conference, pp. 4112-4115, 2006 SICE-ICASE International Joint Conference, Busan, Korea, Republic of, 06/10/18. https://doi.org/10.1109/SICE.2006.315156

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

abstract = "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.",

keywords = "ICA, JIT modeling, Prediction, Process control",

author = "Y. Hijikata and J. Mori and K. Uchida and H. Ogai and M. Ito and S. Matsuzaki and K. Nakamura",

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AU - Hijikata, Y.

AU - Mori, J.

AU - Uchida, K.

AU - Ogai, H.

AU - Ito, M.

AU - Matsuzaki, S.

AU - Nakamura, K.

PY - 2006/12/1

Y1 - 2006/12/1

N2 - 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.

AB - 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.

KW - ICA

KW - JIT modeling

KW - Prediction

KW - Process control

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

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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