Statistical Anomaly Detection for Train Fleets

  • Anders Holst Swedish Institute of Computer Science
  • Markus Bohlin Swedish Institute of Computer Science
  • Jan Ekman Swedish Institute of Computer Science
  • Ola Sellin Bombardier Transportation
  • Björn Lindström Addiva Consulting AB
  • Stefan Larsen Addiva Eduro AB

Abstract

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.
Published
2012-12-06
How to Cite
Holst, A., Bohlin, M., Ekman, J., Sellin, O., Lindström, B., & Larsen, S. (2012). Statistical Anomaly Detection for Train Fleets. AI Magazine, 34(1), 33. https://doi.org/10.1609/aimag.v34i1.2435
Section
Articles