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Deviation Detection by Self-Organized On-Line Models Simulated on a Feed-Back Controlled DC-Motor
Volvo Technology.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0001-5163-2997
2009 (English)In: Proceeding Intelligent Systems and Control (ISC 2009) / [ed] M.H. Hamza, Cambridge, Mass.: ACTA Press, 2009Conference paper, Published paper (Refereed)
Abstract [en]

A new approach to improve fault detection is proposed. The method takes benefit of using a population of systems to dynamically define a norm of how the system works. The norm is derived from self-organizing algorithms which generate a low dimensional representation of how selected feature data are correlated. The feature data is selected from the state variables and from the control signals. The self-organizing method and limited number of feature signals enable fast deviation detection and low computational footprint on each system to be analyzed. The comparison analysis between the systems is performed at a service centre, to where the low-dimensional representations of the systems are transmitted. The method is demonstrated on a simulated DC-motor and the results are promising for deviation detection.

Place, publisher, year, edition, pages
Cambridge, Mass.: ACTA Press, 2009.
Keywords [en]
Machine learning, fault diagnosis, data mining, mechatronics, deviation detection, state variables
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-5024Scopus ID: 2-s2.0-77952417209ISBN: 978-0-88986-814-4 (print)OAI: oai:DiVA.org:hh-5024DiVA, id: diva2:327075
Conference
Intelligent Systems and Control 2009, Cambridge, Mass., USA, Nov. 2-4, 2009
Note

Track: 665-086

Available from: 2010-06-28 Created: 2010-06-28 Last updated: 2020-05-26Bibliographically approved

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Scopushttp://www.actapress.com/Abstract.aspx?paperId=35575

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Svensson, MagnusForsberg, MagnusByttner, StefanRögnvaldsson, Thorsteinn

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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