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Predict, Detect and React to Signaling and Train Control Failures With Improved Diagnostics Achieved With a Suite of Data Collection and Analysis Tools in a Maintenance and Diagnostic Center

[+] Author Affiliations
Joseph A. Greco, II

Bombardier, Pittsburgh, PA

Paper No. JRC2018-6271, pp. V001T04A006; 9 pages
  • 2018 Joint Rail Conference
  • 2018 Joint Rail Conference
  • Pittsburgh, Pennsylvania, USA, April 18–20, 2018
  • Conference Sponsors: Rail Transportation Division
  • ISBN: 978-0-7918-5097-8
  • Copyright © 2018 by ASME


The highest level of automation may be achieved with traditional fixed block systems with numerous benefits. Diagnostic Data can be collected from wayside infrastructure and stored in a central depository. Diagnostics from the vehicle may also be collected, not typically in a dynamic fashion, and stored in a centralized depository. This data is not easily integrated or sequenced between the onboard and wayside. External systems are added to collect all data. This centralized system composes a Maintenance and Diagnostic Center.

In addition, with CBTC systems, communication between the wayside and the vehicle include ATP information, Movement Authority, Speed Restrictions from the wayside to the vehicle and reports of train location, speed, travel direction and vehicles status. With ATO, data is also transferred between the train and wayside. Much of the vehicle reported ATO data includes vehicle and on-board controller alarms and events. This train and wayside communicated data is collected and stored in the MDC with the added benefit of being integrated between the on-board and wayside. This integrated data allows data mining to be performed to evaluate many operating aspects of the system.

This presentation identifies some of the types of data collected and the analysis that may be performed on the data to identify improvements that are to be integrated in system operation, detect system components that are degrading to a point of failure to help schedule maintenance before failure and provide the capability to review events post mortem to identify the root cause of failures that occur in the system.

Copyright © 2018 by ASME



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