Low Power Wireless Sensors for Railroad Bearing Health Monitoring

The research team proposes to develop an integrated, self-powered condition monitoring system for rail vehicle bearings. This system will leverage previous research at University Transportation Center for Railway Safety (UTCRS) on damage detection sensors and algorithms, service life prediction, signal processing for rail environments, and energy harvesting. The research team's UTRGV railroad research group has already shown that a combination of vibration, temperature, and load sensing can detect bearing defects and damage at a very early stage, and before it becomes a safety hazard, enabling selective preventive replacement during planned maintenance stops. The research group has also demonstrated signal processing electronics that allow detection of critical signals in challenging noise environments.The developed system will consist of self-powered miniature modules, directly mounted on bearing adapters, which will monitor the vibration spectrum, temperature history, and total applied vertical load on the bearing, and wirelessly transmit the data to a compact analysis module located on the rail vehicle. While there have been similar systems, the research team's would be unique in: (a) incorporation of the research team's signal processing electronics that have proven success in extracting usable data from high noise situations, (b) a combination of vibration, temperature, and load sensors and sampling rates that have been optimized in both laboratory and field testing environments, (c) initial data analysis at the bearing sensor level to determine whether further analysis is warranted, (d) spectrum analysis algorithms, embedded in the compact analysis module, that have demonstrated superior performance in detecting and classifying bearing defects, and (e) self-powering using energy harvesting techniques. Benefits of the proposed system include the following: (1) Accident prevention through early detection of impending failures, (2) Reduced operating costs through fewer stoppages, and more efficient and effective replacement and maintenance schedules, and (3) Creation of a large-scale database of bearing incidents, enabling further research. Deliverables will include a set of working prototype modules for one railcar, a compact analysis module (CAM), design information including schematics, signal processing parameters, and algorithms, and comprehensive test data. System validation and verification will be carried out through extensive laboratory testing.

Language

  • English

Project

  • Status: Active
  • Funding: $85866
  • Contract Numbers:

    DTRT13-G-UTC59

  • Sponsor Organizations:

    University of Texas Rio Grande Valley

    1201 W. University Dr
    Edinburg, Texas  United States  78539
  • Managing Organizations:

    University of Texas Rio Grande Valley

    1201 W. University Dr
    Edinburg, Texas  United States  78539
  • Performing Organizations:

    University of Texas Rio Grande Valley

    1201 W. University Dr
    Edinburg, Texas  United States  78539
  • Principal Investigators:

    Foltz, Heinrich

  • Start Date: 20170201
  • Expected Completion Date: 20180831
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01634816
  • Record Type: Research project
  • Source Agency: University Transportation Center for Railway Safety
  • Contract Numbers: DTRT13-G-UTC59
  • Files: UTC, RiP
  • Created Date: May 16 2017 12:28PM