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Analysis of Wheel Impact Load Detector (WILD) System Implementation on Metro-North Railroad

[+] Author Affiliations
Monique Stewart, Edward Flynn

Federal Railroad Administration, Washington, DC

Hamed Pouryousef, Som P. Singh, Anand Prabhakaran

Sharma & Associates, Inc., Countryside, IL

Paper No. JRC2018-6200, pp. V001T02A007; 6 pages
doi:10.1115/JRC2018-6200
From:
  • 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

abstract

The Federal Railroad Administration (FRA) has partnered with Metro-North Railroad (MNR), Long Island Rail Road (LIRR) and New York & Atlantic Railway (NYA) to promote operations safety through implementation of wayside detection systems and technologies. Under this partnership, opportunities were identified to enhance safety operations through the analysis of existing and planned wheel impact load detector (WILD) installations and operational procedures, including recommendations for future wayside detection systems implementations on these networks.

Currently, MNR has a four-detector system operating near the Grand Central Terminal, since 2010. This paper includes an analysis of this WILD system and its impact on rolling stock maintenance. The analysis shows that the WILD system has gradually reduced the annual average number of high impact load wheels from 0.32/car in 2010 to 0.27/car in 2015.

Review of data from the detectors on four tracks at the WILD site shows that train operations below a certain speed has a significant effect on the detection rate and should be a major consideration in selecting a location for WILD installation.

The data show that the highest number of high impact wheels is detected in the month of November, potentially due to leaves on the rails during fall season.

Our analysis shows that the currently used trigger threshold of dynamic ratio (DR)≥3 at MNR provides well-reasoned balance between the available fleet, maintenance demand and the maintenance shop capacity. At this threshold setting, the number of wheels detected per million wheel passages is quite small indicating a well maintained fleet.

Copyright © 2018 by ASME
Topics: Sensors , Stress , Railroads , Wheels

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