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A self-organized approach for unsupervised fault detection in multiple systems
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).ORCID iD: 0000-0001-5163-2997
Salzburg Research Advanced Networking Center Jakob-Haringer-Str. 51111 5020, Salzburg, Austria.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
Volvo Technology, 405 08 Goteborg, Sweden.
2008 (English)In: 19th International Conference on Pattern Recognition: (ICPR 2008) ; Tampa, Florida, USA 8-11 December 2008, Piscataway, N.J.: IEEE Press, 2008, p. 1-4Conference paper, Published paper (Refereed)
Abstract [en]

An approach is proposed for automatic fault detection in a population of mechatronic systems. The idea is to employ self-organizing algorithms that produce low-dimensional representations of sensor and actuator values on the vehicles, and compare these low-dimensional representations among the systems. If a representation in one vehicle is found to deviate from, or to be not so similar to, the representations for the majority of the vehicles, then the vehicle is labeled for diagnostics. The presented approach makes use of principal component coding and a measure of distance between linear sub-spaces. The method is successfully demonstrated using simulated data for a commercial vehiclepsilas engine coolant system, and using real data for computer hard drives.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2008. p. 1-4
Series
International Conference on Pattern Recognition, ISSN 1051-4651 ; 2008
Keywords [en]
computer hard drives, coolants, engine coolant system, fault diagnosis, mechanical engineering computing, mechatronic systems, mechatronics, multiple systems, principal component coding, self-adjusting systems, self-organizing algorithms, unsupervised fault detection, vehicles
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-5022DOI: 10.1109/ICPR.2008.4761283ISI: 000264729001444Scopus ID: 2-s2.0-77957969461ISBN: 978-1-4244-2175-6 OAI: oai:DiVA.org:hh-5022DiVA, id: diva2:327079
Conference
19th International Conference on Pattern Recognition (ICPR 2008),Tampa, FL, DEC 08-11, 2008
Note

©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Available from: 2010-06-28 Created: 2010-06-28 Last updated: 2018-03-23Bibliographically approved

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Rögnvaldsson, ThorsteinnByttner, StefanSvensson, Magnus

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CiteExportLink to record
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Citation style
  • apa
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Output format
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