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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.
Vise andre og tillknytning
2012 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Toronto, Canada, 2012, 9. Vol. 3, s. 2217-2223
Emneord [en]
Anomaly detection, Maintenance cost, Normal behavior, Railway operators, Statistical anomaly detection, Train fleets
HSV kategori
Identifikatorer
URN: urn:nbn:se:ri:diva-24031Scopus ID: 2-s2.0-84868290884ISBN: 9781577355687 (tryckt)OAI: oai:DiVA.org:ri-24031DiVA, id: diva2:1043110
Konferanse
Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference
Prosjekter
DUST
Merknad

Accepted for publication.

Tilgjengelig fra: 2016-10-31 Laget: 2016-10-31 Sist oppdatert: 2023-05-09bibliografisk kontrollert

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Bohlin, MarkusHolst, AndersEkman, Jan

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Totalt: 108 treff
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