using thermal imagery.

Details

• Creators:
  Havens, Timothy ; Deilamsalehy, Hanieh ; Lautala, Pasi
• Corporate Creators:
  Michigan Technological University. Department of Civil and Environmental Engineering
• Corporate Contributors:
  National University Rail Center (U.S.)
• Subject/TRT Terms:
  • Sliding friction
  • Car wheels (Railroads)
  • Wheelsets (Railroads)
  • Bearings
  • Thermal imagery
  • Hot bearings
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  National University Rail Center (U.S.)
• Abstract:
  One of the most important safety-related tasks in the rail industry is early detection of defective rolling ; stock components. Railway wheels and wheel bearings are two components prone to damage due to ; their interactions with brakes and railway track, which makes them a high priority when the rail ; industry investigates improvements to current detection processes. One of the specific wheel defects is ; a flat wheel, which is often caused by sliding during a heavy braking application. The main ; contribution of this research work is development of a computer vision method for automatically ; detecting the sliding wheels from images taken by wayside thermal cameras. As a byproduct, the ; process will also include a method for detecting hot bearings from the same images. We trained our ; algorithm with a set of simulated data and tested it on several thermal images collected in in North ; American revenue service by the Union Pacific Railroad (UPRR).
• Format:
  PDF
• Funding:
  Grant Number: DTRT12-G-UTC18 ; NURail Project ID: NURail2013-MTU-R06
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/31427/dot_31427_DS1.pdf
• File Type:
  [PDF - 1.09 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:df3496985c612810e24f9a8a93794f38a19a715b61d087d820b2dd10b20822e4