Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods

Marcin Blachnik; Tadeusz Wieczorek; Krystian Ma̧czka; Grzegorz Kopeć

doi:10.1007/978-3-642-17534-3_86

Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods

Marcin Blachnik
, Tadeusz Wieczorek
, Krystian Ma̧czka
, Grzegorz Kopeć

Department of Industrial Informatics (RM/RM4)

Silesian University of Technology

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

Abstract

A constant aspiration to optimize electric arc steelmaking process causes an increase of the use of advanced analytical methods for the process support. Optimization of the production processes lead to real benefits, which are, for example, lower costs of production. More often computational intelligence methods are used for this purpose. In this paper authors present three methods used for identification of liquid state of scrap in electric arc furnace using analysis of signals of the current of furnace electrodes.

Original language	English
Title of host publication	Neural Information Processing
Subtitle of host publication	Models and Applications - 17th International Conference, ICONIP 2010, Proceedings
Pages	700-707
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-17534-3_86
Publication status	Published - 2010
Event	17th International Conference on Neural Information Processing, ICONIP 2010 - Sydney, NSW, Australia Duration: 22 Nov 2010 → 25 Nov 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6444 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Neural Information Processing, ICONIP 2010
Country/Territory	Australia
City	Sydney, NSW
Period	22/11/10 → 25/11/10

Keywords

classification
electric arc furnace
industrial application
noise estimation
process modeling
signal processing

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-17534-3_86

Cite this

Blachnik, M., Wieczorek, T., Ma̧czka, K., & Kopeć, G. (2010). Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods. In Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings (PART 2 ed., pp. 700-707). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6444 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-17534-3_86

Blachnik, Marcin ; Wieczorek, Tadeusz ; Ma̧czka, Krystian et al. / Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods. Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. PART 2. ed. 2010. pp. 700-707 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods",

abstract = "A constant aspiration to optimize electric arc steelmaking process causes an increase of the use of advanced analytical methods for the process support. Optimization of the production processes lead to real benefits, which are, for example, lower costs of production. More often computational intelligence methods are used for this purpose. In this paper authors present three methods used for identification of liquid state of scrap in electric arc furnace using analysis of signals of the current of furnace electrodes.",

keywords = "classification, electric arc furnace, industrial application, noise estimation, process modeling, signal processing",

author = "Marcin Blachnik and Tadeusz Wieczorek and Krystian M{\c a}czka and Grzegorz Kope{\'c}",

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Blachnik, M, Wieczorek, T, Ma̧czka, K & Kopeć, G 2010, Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods. in Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6444 LNCS, pp. 700-707, 17th International Conference on Neural Information Processing, ICONIP 2010, Sydney, NSW, Australia, 22/11/10. https://doi.org/10.1007/978-3-642-17534-3_86

Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods. / Blachnik, Marcin; Wieczorek, Tadeusz; Ma̧czka, Krystian et al.
Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. PART 2. ed. 2010. p. 700-707 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6444 LNCS, No. PART 2).

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

TY - GEN

T1 - Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods

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AU - Wieczorek, Tadeusz

AU - Ma̧czka, Krystian

AU - Kopeć, Grzegorz

PY - 2010

Y1 - 2010

N2 - A constant aspiration to optimize electric arc steelmaking process causes an increase of the use of advanced analytical methods for the process support. Optimization of the production processes lead to real benefits, which are, for example, lower costs of production. More often computational intelligence methods are used for this purpose. In this paper authors present three methods used for identification of liquid state of scrap in electric arc furnace using analysis of signals of the current of furnace electrodes.

AB - A constant aspiration to optimize electric arc steelmaking process causes an increase of the use of advanced analytical methods for the process support. Optimization of the production processes lead to real benefits, which are, for example, lower costs of production. More often computational intelligence methods are used for this purpose. In this paper authors present three methods used for identification of liquid state of scrap in electric arc furnace using analysis of signals of the current of furnace electrodes.

KW - classification

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KW - industrial application

KW - noise estimation

KW - process modeling

KW - signal processing

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DO - 10.1007/978-3-642-17534-3_86

M3 - Conference contribution

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SN - 3642175333

SN - 9783642175336

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Blachnik M, Wieczorek T, Ma̧czka K, Kopeć G. Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods. In Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. PART 2 ed. 2010. p. 700-707. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-17534-3_86

Identification of liquid state of scrap in electric arc furnace by the use of computational intelligence methods

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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