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Vehicle Diagnostics Method by Anomaly Detection and Fault Identification Software
Volvo Technology, Sweden.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
AASS Örebro University, Sweden.ORCID iD: 0000-0001-5163-2997
2009 (English)In: SAE international journal of passenger cars : electronic and electrical systems, ISSN 1946-4614, Vol. 2, no 1, p. 352-358Article in journal (Refereed) Published
Abstract [en]

A new approach is proposed for fault detection. It builds on using the relationships between sensor values on vehicles to detect deviating sensor readings and trends in the system performance. However, in contrast to previous approaches based on such sensor relations, our approach uses a fleet of vehicles to define the normal conditions and relations. The relationships between the sensors are also determined automatically in a self-organized way on each vehicle, i.e. no off-line modeling is required. The proposed method is the first step in a remote diagnostics and maintenance service where error detection is done automatically, followed by a download of special purpose diagnostics software for the particular subsystem where the possible fault was detected.

Place, publisher, year, edition, pages
Warrendale, PA: SAE international , 2009. Vol. 2, no 1, p. 352-358
Keyword [en]
Vehicle Diagnostics
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-5018Scopus ID: 2-s2.0-77953147742OAI: oai:DiVA.org:hh-5018DiVA, id: diva2:327081
Available from: 2010-06-28 Created: 2010-06-28 Last updated: 2018-03-23Bibliographically approved

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Scopushttp://saepcelec.saejournals.org/content/2/1/352.abstract

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Svensson, MagnusByttner, StefanRögnvaldsson, Thorsteinn

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