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Author:

Tian, J. (Tian, J..) | Tanaka, A. (Tanaka, A..) | Gao, D. (Gao, D..) | Hou, Q. (Hou, Q..) | Chen, X. (Chen, X..)

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EI Scopus SCIE

Abstract:

This paper reports new research progress on characterizing the burden surface particles of the blast furnace. An algorithm is proposed to extract the contour of the particles on the burden surfaces from their digital elevation models. The statistical distributions of particle size corresponding to the coke and sintered ore burden surfaces are counted from the extraction results of the particle contours. The statistical results obtained in the former research are compared with those of here. The particle surface height distributions can be approximated based on the burden particle size distributions. The peak positions of the estimated particle surface height distribution are consistent with that of the burden surface height distribution. © 2024 Iron and Steel Institute of Japan. All rights reserved.

Keyword:

blast furnace burden particle contour extraction digital elevation model

Author Community:

  • [ 1 ] [Tian J.]Faculty of Information Technology, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing, 100124, China
  • [ 2 ] [Tanaka A.]Faculty of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido, 060-0814, Japan
  • [ 3 ] [Gao D.]Department of Mathematics and Statistics, Sam Houston State University, Huntsville, 77341, TX, United States
  • [ 4 ] [Hou Q.]School of Automation and Engineering, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing, 100083, China
  • [ 5 ] [Chen X.]School of Automation and Engineering, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing, 100083, China

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Source :

ISIJ International

ISSN: 0915-1559

Year: 2024

Issue: 7

Volume: 64

Page: 1218-1222

1 . 8 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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