Correlation of Continuous Vehicle Based and Wayside Inspection Data to Develop Non-Traditional Maintenance Intervention Strategies

Start: September 2017, End: August 2018

Principal Investigator/Researcher

Dr. Allan M Zarembski (professor) and Kyle Ebersole (Graduate student), University of Delaware

Project Description

The vehicle/track interface continues to be of great concern in all rail operations to include high speed and conventional passenger, freight and transit operations. Much research has been performed in this area and in the associated area of the wheel/rail interface, and have resulted in the development of sophisticated inspection technologies aimed at evaluating various track and train component performance and conditions. Until now, the data from these varied inspection technologies have been evaluated at a basic data analysis level, e.g. threshold analysis based. This activity extends improved data Analytic techniques to the analysis of data collect on a complete NYCT transit line.

The focus of this study was analysis of wayside measurement data with a specific emphasis Wheel Profile Data using wheel profile data for every passing wheel on every vehicle in the fleet that operates on the study NYCT line. This data was supplemented by the following additional data:

  • Applied Rail Force Data: measured lateral and vertical forces on the rail from every passing axle
  • Angle of Attack Data: measured angle of attack of the bogie for every passing vehicle

This research study used this wheel wear data, as provided by the New York City Transit Authority (NYCT), to analyze wheel wear trends and forecast wheel maintenance (truing based on flange thickness) and wheel life (replacement based on rim thickness). Using automatic wheel-scanning technology, NYCT was able to collect wheel profile measurements for nearly 4,000 wheels in their fleet over a six-month period, measured weekly. The resulting wheel measurement data was analyzed using advanced stochastic techniques to determine relationships for the changes in flange thickness over time for each wheel in the fleet.

The expected research results will be a set of wheel wear models that can be used to forecast the time it would take for a wheel to reach the flange thickness maintenance threshold as defined by NYCT standards. This is to include both wheel truing maintenance and wheel replacement.

Implementation of Research Outcomes

The research results include a set of wheel wear models that can be used to forecast the time it would take for a wheel to reach the flange thickness maintenance threshold as defined by NYCT standards. This is to include both wheel truing maintenance and wheel replacement.

NYCT has been making increased use of this wheel wear data. Using the models developed here-in NYCT was able to identify a subpopulation of wheels that exhibited very high rates of wear which were classified as “bad actors” and identified for further investigation to understand the cause of accelerated wear.

Railroad

Impacts/Benefits of Implementation

  • Extended life of wheels in service
  • Reduced wheel maintenance costs
  • Identification of bad actor cars that generate excessively high rates of wheel wear.