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Networked vehicles for automated fault detection
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
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
Volvo Technology, SE-405 08 Göteborg, Sweden.
Volvo Technology of America, 7825 National Service Rd., Greensboro, NC 27409, United States.
Show others and affiliations
2009 (English)In: 2009 IEEE International Symposium on Circuits and Systems: circuits and systems for human centric smart living technologies, conference program, Taipei International Convention Center, Taipei, Taiwan, May 24-May 27, 2009 / [ed] Guo li Chenggong da xue, Piscataway, N.J.: IEEE Press, 2009, 1213-1216 p.Conference paper, (Refereed)
Abstract [en]

Creating fault detection software for complex mechatronic systems (e.g. modern vehicles) is costly both in terms of engineer time and hardware resources. With the availability of wireless communication in vehicles, information can be transmitted from vehicles to allow historical or fleet comparisons. New networked applications can be created that, e.g., monitor if the behavior of a certain system in a vehicle deviates compared to the system behavior observed in a fleet. This allows a new approach to fault detection that can help reduce development costs of fault detection software and create vehicle individual service planning. The COSMO (consensus self-organized modeling) methodology described in this paper creates a compact representation of the data observed for a subsystem or component in a vehicle. A representation that can be sent to a server in a backoffice and compared to similar representations for other vehicles. The backoffice server can collect representations from a single vehicle over time or from a fleet of vehicles to define a norm of the vehicle condition. The vehicle condition can then be monitored, looking for deviations from the norm. The method is demonstrated for measurements made on a real truck driven in varied conditions with ten different generated faults. The proposed method is able to detect all cases without prior information on what a fault looks like or which signals to use.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2009. 1213-1216 p.
Keyword [en]
automated fault detection software, backoffice server, consensus self-organized modeling methodology, data mining, mechatronic system, network servers, networked vehicles, radio networks, software fault tolerance, telecommunication computing, traffic engineering computing, vehicle condition, wireless communication
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-5023DOI: 10.1109/ISCAS.2009.5117980ISI: 000275929800311Scopus ID: 2-s2.0-70350142425ISBN: 978-1-4244-3827-3 OAI: oai:DiVA.org:hh-5023DiVA: diva2:327077
Conference
2009 International Symposium on Circuits and Systems, May 24-27, Taipei, Taiwan
Note

©2009 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: 2013-10-15Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
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  • Other locale
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Output format
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