hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
  • rtf
Knowledge Extraction from Real-World Logged Truck Data
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0002-4143-2948
Volvo AB.
Volvo AB.
2009 (English)In: SAE International Journal of Commercial Vehicles, ISSN 1946-391X, Vol. 2, no 1, p. 64-74Article in journal (Refereed) Published
Abstract [en]

In recent years more data is logged from the electronic control units on-board in commercial vehicles. Typically, the data is transferred from the vehicle at the workshop to a centralized storage for future analysis. This vast amount of data is used for debugging, as a knowledgebase for the design engineer and as a tool for service planning.

Manual analysis of this data is often time consuming, due to the rich amount of information contained. However, there is an opportunity to automatically assist in the process based on knowledge discovery techniques, even directly when the trucks data is first offloaded at the workshop. One typical example of how this technique could be helpful is when two groups of trucks behave differently, e.g. one well-functioning group and one faulty group, when the two groups have the same specification. The desired information is the specific difference in the logged data, e.g. what particular sensors or signals are different.

An evaluation cycle is proposed and applied to extract knowledge from three different large real-world data-sets measured on Volvo long haulage trucks. Information in the logged data that describes the vehicle’s operating environment, allows the detection of trucks that are operated differently from their intended use. Experiments to find such vehicles were conducted and recommendations for an automated application are given.

Place, publisher, year, edition, pages
Warrendale, PA: Society of Automotive Engineers, 2009. Vol. 2, no 1, p. 64-74
Keywords [en]
Trucks, Amount of information, Automated applications, Commercial vehicles, Design engineers, Electronic control units, Functioning groups, Haulage trucks, Knowledge base, Knowledge discovery techniques, Knowledge extraction; Manual analysis; Operating environment; Real world data; Real-world; Service planning
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-5547DOI: 10.4271/2009-01-1026Scopus ID: 2-s2.0-77953071927OAI: oai:DiVA.org:hh-5547DiVA, id: diva2:346654
Available from: 2010-09-02 Created: 2010-09-02 Last updated: 2018-03-23Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Grubinger, ThomasWickström, Nicholas

Search in DiVA

By author/editor
Grubinger, ThomasWickström, Nicholas
By organisation
Halmstad Embedded and Intelligent Systems Research (EIS)
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 202 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
  • rtf