Enhancing Anomaly Diagnosis of Automatic Train Supervision System Based on Operation Log

Yan Li, Binbin Chen, Vincent W. Zheng, William G. Temple, Zbigniew Kalbarczyk, Yue Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Automatic train supervision (ATS) systems are designed to improve the reliability of train services. An ATS system coordinates the trains and other systems in a metro and records alarms if faults occur. In this work, we propose a context-aware anomaly diagnosis tool to analyze the underlying causes of alarms for ATS system. Using 61-day data collected from an operational ATS system, we apply our diagnosis tool to conduct systematic analysis of the alarms and identify interesting correlations among different assets and events. Our analysis shows that the alarms can be correlated with certain system events if they are in the same operations or the assets associated with them belong to the same or linked systems. These results can improve the efficiency of anomaly diagnosis and maintenance for metro system.

Original languageEnglish (US)
Title of host publicationProceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-136
Number of pages4
ISBN (Electronic)9781538622728
DOIs
StatePublished - Aug 30 2017
Event47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2017 - Denver, United States
Duration: Jun 26 2017Jun 29 2017

Publication series

NameProceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2017

Other

Other47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2017
Country/TerritoryUnited States
CityDenver
Period6/26/176/29/17

Keywords

  • automatic train supervision
  • context-aware anomaly diagnosis
  • log analysis
  • metro system

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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