Real-Time Rail Defect Detection With Eddy Current (EC) Technique: Signal Processing and Case Studies of Rail Samples

Safety is one of the key issues for rail transportation. Nowadays, rails are exposed to constantly increasing traffic with heavy loads and high-speed trains. Increasing the efficiency, frequency, and speed of rail defect detection can reduce maintenance costs and improve operational safety. The non-contact eddy current system can be operated in high train speeds to measure both surface and subsurface flaws. While methods that rely on eddy currents are available, the commercial Eddy Current (EC) system cannot directly provide defect types and patterns. It is generally based on live measurement data and also relies on commercially designed data acquisition devices for signal analysis. In addition, the ability to identify crack types and the possibility of detecting subsurface defects have been of concern with the current commercial EC system. The main objective of this research was to explore the eddy current based methods for inspecting surface/subsurface defects on rails with enhanced performance for defect classification by distinguish the crack depths or crack angles. In this project, the optimization of eddy current rail inspection technique was conducted in two phases to test the reliability of defect inspection and the ability for classification of different defect signals; Phase 1 developed an integrated hardware & software EC measurement system to accurately detect machined cracks in steel samples sample with different crack depths and angles, the effectiveness of the signal differences with defect geometry changes was investigated ; Phase 2 is a case study on rail samples with different defect types, measured by the established EC rail inspection system and the different defect signals were compared and collected. Specifically, the ability to identify and characterize the following defects is explored; (1) Surface defects: a) rolling contact fatigue (RCF) cracks, b) Bolt hole crack, c) Rail web longitudinal crack, d) Base dent defect, and d) Gauge corner crack; and (2) Subsurface defects: a) Subsurface rail head defect, b) Subsurface rail web defect, and c) Subsurface gauge corner defect.

• Record URL:
  http://www.nurailcenter.org/research/final_reports/MTU/NURail2020-MTU-R18%20Final%20Report.pdf
• 
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/56454
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Michigan Technological University, Houghton

  Department of Civil and Environmental Engineering
  1400 Townsend Drive
  Houghton, MI  United States  49931-1295

  National University Rail Center (NURail)

  University of Illinois at Urbana-Champaign
  Department of Civil and Environmental Engineering, 205 N. Mathews Avenue
  Urbana, IL  United States  61801

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Wang, Jiaqing
  • Dai, Qingli
  • Lautala, Pasi
• Publication Date: 2020-8-30

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: 23p

Subject/Index Terms

• TRT Terms: Case studies; Cracking; Defects; Eddy currents; Flaw detection; Inspection; Optimization; Railroad tracks; Signal processing
• Subject Areas: Maintenance and Preservation; Railroads;

Filing Info

• Accession Number: 01754821
• Record Type: Publication
• Report/Paper Numbers: NURail2020-MTU-R18
• Contract Numbers: DTRT13-G-UTC52
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Oct 19 2020 10:53AM