Change search
CiteExportLink to record
Permanent link

Direct link
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
  • rtf
Statistical Anomaly Detection for Train Fleets
RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.ORCID iD: 0000-0003-1597-6738
RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.ORCID iD: 0000-0001-8577-6745
RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.ORCID iD: 0000-0002-7181-8411
Bombardier Transportation, Sweden.
Show others and affiliations
2012 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We have developed a method for statistical anomaly detection which has been deployed in a tool for condition monitoring of train fleets. The tool is currently used by several railway operators over the world to inspect and visualize the occurrence of "event messages" generated on the trains. The anomaly detection component helps the operators to quickly find significant deviations from normal behavior and to detect early indications for possible problems. The savings in maintenance costs comes mainly from avoiding costly breakdowns, and have been estimated to several million Euros per year for the tool. In the long run, it is expected that maintenance costs can be reduced with between 5 and 10 % by using the tool.

Place, publisher, year, edition, pages
Toronto, Canada, 2012, 9. Vol. 3, p. 2217-2223
Keywords [en]
Anomaly detection, Maintenance cost, Normal behavior, Railway operators, Statistical anomaly detection, Train fleets
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-24031Scopus ID: 2-s2.0-84868290884ISBN: 9781577355687 (print)OAI: oai:DiVA.org:ri-24031DiVA, id: diva2:1043110
Conference
Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference
Projects
DUST
Note

Accepted for publication.

Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2023-05-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

Scopus

Authority records

Bohlin, MarkusHolst, AndersEkman, Jan

Search in DiVA

By author/editor
Bohlin, MarkusHolst, AndersEkman, Jan
By organisation
SICSDecisions, Networks and Analytics lab
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 108 hits
CiteExportLink to record
Permanent link

Direct link
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
  • rtf