Actuator fault diagnosis using single and meta-classification strategies

Mateusz Kalisch; Piotr Przystałka; Anna Timofiejczuk

doi:10.1007/978-3-319-28868-0_8

Actuator fault diagnosis using single and meta-classification strategies

Department of Fundamentals of Machinery Design (RMT/RMT6)

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

5 Citations (Scopus)

Abstract

The paper presents the application of various classification schemes for actuator fault diagnosis in industrial systems. The main objective of this study is to compare either single or metaclassification strategies that can be successfully used as reasoning means in the diagnostic expert system that is realized within the frame of the DISESOR project. The applied research was conducted on the assumption that classic as well as soft computing classification methods would be adopted. The comparison study was carried out within the DAMADICS benchmark problem which provides a popular framework for confronting different approaches in the development of fault diagnosis systems.

Original language	English
Title of host publication	Artificial Intelligence for Knowledge Management - 2nd IFIP WG 12.6 International Workshop, AI4KM 2014, Revised Selected Papers
Editors	Mieczysław Lech Owoc, Eunika Mercier-Laurent, Danielle Boulanger
Publisher	Springer New York LLC
Pages	132-149
Number of pages	18
ISBN (Print)	9783319288673
DOIs	https://doi.org/10.1007/978-3-319-28868-0_8
Publication status	Published - 2015
Event	2nd IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2014 - Warsaw, Poland Duration: 7 Sept 2014 → 10 Sept 2014

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	469
ISSN (Print)	1868-4238

Conference

Conference	2nd IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2014
Country/Territory	Poland
City	Warsaw
Period	7/09/14 → 10/09/14

ASJC Scopus subject areas

Information Systems
Computer Networks and Communications
Information Systems and Management

Access to Document

10.1007/978-3-319-28868-0_8

Cite this

Kalisch, M., Przystałka, P., & Timofiejczuk, A. (2015). Actuator fault diagnosis using single and meta-classification strategies. In M. L. Owoc, E. Mercier-Laurent, & D. Boulanger (Eds.), Artificial Intelligence for Knowledge Management - 2nd IFIP WG 12.6 International Workshop, AI4KM 2014, Revised Selected Papers (pp. 132-149). (IFIP Advances in Information and Communication Technology; Vol. 469). Springer New York LLC. https://doi.org/10.1007/978-3-319-28868-0_8

Kalisch, Mateusz ; Przystałka, Piotr ; Timofiejczuk, Anna. / Actuator fault diagnosis using single and meta-classification strategies. Artificial Intelligence for Knowledge Management - 2nd IFIP WG 12.6 International Workshop, AI4KM 2014, Revised Selected Papers. editor / Mieczysław Lech Owoc ; Eunika Mercier-Laurent ; Danielle Boulanger. Springer New York LLC, 2015. pp. 132-149 (IFIP Advances in Information and Communication Technology).

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abstract = "The paper presents the application of various classification schemes for actuator fault diagnosis in industrial systems. The main objective of this study is to compare either single or metaclassification strategies that can be successfully used as reasoning means in the diagnostic expert system that is realized within the frame of the DISESOR project. The applied research was conducted on the assumption that classic as well as soft computing classification methods would be adopted. The comparison study was carried out within the DAMADICS benchmark problem which provides a popular framework for confronting different approaches in the development of fault diagnosis systems.",

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Kalisch, M , Przystałka, P & Timofiejczuk, A 2015, Actuator fault diagnosis using single and meta-classification strategies. in ML Owoc, E Mercier-Laurent & D Boulanger (eds), Artificial Intelligence for Knowledge Management - 2nd IFIP WG 12.6 International Workshop, AI4KM 2014, Revised Selected Papers. IFIP Advances in Information and Communication Technology, vol. 469, Springer New York LLC, pp. 132-149, 2nd IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2014, Warsaw, Poland, 7/09/14. https://doi.org/10.1007/978-3-319-28868-0_8

Actuator fault diagnosis using single and meta-classification strategies. / Kalisch, Mateusz ; Przystałka, Piotr ; Timofiejczuk, Anna.
Artificial Intelligence for Knowledge Management - 2nd IFIP WG 12.6 International Workshop, AI4KM 2014, Revised Selected Papers. ed. / Mieczysław Lech Owoc; Eunika Mercier-Laurent; Danielle Boulanger. Springer New York LLC, 2015. p. 132-149 (IFIP Advances in Information and Communication Technology; Vol. 469).

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

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AB - The paper presents the application of various classification schemes for actuator fault diagnosis in industrial systems. The main objective of this study is to compare either single or metaclassification strategies that can be successfully used as reasoning means in the diagnostic expert system that is realized within the frame of the DISESOR project. The applied research was conducted on the assumption that classic as well as soft computing classification methods would be adopted. The comparison study was carried out within the DAMADICS benchmark problem which provides a popular framework for confronting different approaches in the development of fault diagnosis systems.

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Kalisch M , Przystałka P , Timofiejczuk A. Actuator fault diagnosis using single and meta-classification strategies. In Owoc ML, Mercier-Laurent E, Boulanger D, editors, Artificial Intelligence for Knowledge Management - 2nd IFIP WG 12.6 International Workshop, AI4KM 2014, Revised Selected Papers. Springer New York LLC. 2015. p. 132-149. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-319-28868-0_8

Actuator fault diagnosis using single and meta-classification strategies

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