Machine Vision for Railroad Equipment Undercarriage Inspection Using Multi-Spectral Imaging

Current practices for inspection of railcars and locomotives include both manual and automated systems. However, inspection of railroad equipment undercarriages is almost entirely a manual process. Visual inspections by humans are performed either in a pit or trackside. The equipment is usually stopped over the pit or run slowly past the trackside inspector. In the latter case, it is not possible for a human to have an unobstructed view of the undercarriage as a train rolls by. Automated inspection by electronic systems has the potential to overcome certain limitations of human inspection. The report describes the Innovations Deserving Exploratory Analysis (IDEA) project conducted to develop a new approach to undercarriage inspection by means of machine vision analysis. This approach uses multispectral imaging from cameras viewing the undercarriage from a below-the-track perspective. Imaging using both visible and infrared spectra provides a means by which incipient failure detection can be addressed. Detection of missing, damaged, and foreign objects can also be identified using this approach. By extracting frames from video recordings in both spectra, panoramic images of the entire train can be created and analyzed. These images are further subdivided into individual railcar panoramas that can be matched to templates of railcars in known good condition to detect missing and foreign objects. More detailed diagnosis can be provided by using specific component-level templates allowing identification of damaged and overheated subcomponents. In addition, comparisons can be made of duplicate component systems during operation, such as disk brakes, to discover thermal outliers indicating improper function. A prototype of this machine vision inspection system has been developed and tested at a passenger car service and inspection facility. This investigation demonstrates the feasibility of a machine vision system to provide undercarriage inspection capabilities, as the train passes over the pit, aiding inspection crews and repair personnel. The system provides a clear and unobstructed visible spectrum assessment of the undercarriage in addition to an assessment from the thermal spectrum as well. The joint analysis of these undercarriage views can provide automatic detection of components in need of repair and also those that may be over worked or near failure. This allows the inspector to be aware of indications indicative of component problems that are developing, which may fail in the future. Therefore the system has potential for providing advanced warning, allowing additional time for repair personnel to plan repairs prior to possible in-service failures.

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  • Supplemental Notes:
    • This HSR-IDEA project was conducted by the University of Illinois, Urbana-Champaign. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
  • Authors:
    • Ahuja, Narendra
    • Barkan, Christopher P L
  • Publication Date: 2007-12


  • English

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Filing Info

  • Accession Number: 01145896
  • Record Type: Publication
  • Report/Paper Numbers: HSR-IDEA Project 49
  • Files: TRIS, TRB
  • Created Date: Dec 4 2009 11:43AM