Machine Vision Inspection of Railroad Track
Railroad engineering practices and Federal Railroad Administration (FRA) regulations require track to be inspected for physical defects at specified intervals, which may be as often as twice per week. Most of these inspections are conducted visually by railroad track inspectors and include detecting defects relating to the ballast section, ties, fasteners, rail, and special trackwork. Enhancements to the current manual inspection process are possible using machine-vision technology, which consists of recording digital images of track elements of interest and analyzing them using custom algorithms to identify defects or their symptoms. Based on analysis of FRA accident data, discussion with railroad track engineering experts and consultation with Association of American Railroads researchers, this project focuses on using machine vision to detect irregularities and defects in wood-tie fasteners, rail anchors, crib ballast, and turnout components. Development of a machine-vision-based inspection system will permit more efficient, effective, and objective inspection of these track elements. The system will be adaptable to inspect in accordance with FRA track safety regulations as well as railroad-specific track standards that may involve additional parameters of interest. Also, because data will be stored digitally, recall and quantitative comparative analysis is possible thereby enabling relative comparisons and trend analysis. This will enhance the ability for longer-term predictive assessment of the health of the track system and its components, and lead to more informed preventative maintenance strategies and a greater understanding of track structure degradation and failure modes.
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Supplemental Notes:
- This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
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Corporate Authors:
Purdue University
3000 Kent Avenue
Lafayette, IN United States 47906-1075Research and Innovative Technology Administration
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Authors:
- Camargo, Luis Fernando Molina
- Resendiz, Esther
- Hart, John M
- Edwards, J R
- Ahuja, Narendra
- Barkan, Christopher P L
- Publication Date: 2011-1-10
Language
- English
Media Info
- Media Type: Web
- Edition: Final Report
- Features: Figures; Photos; References;
- Pagination: 46p
Subject/Index Terms
- TRT Terms: Crash data; Degradation failures; Inspection; Machine vision; Maintenance of way; Railroad engineering; Railroad tracks; Railroad transportation
- Subject Areas: Maintenance and Preservation; Railroads; I61: Equipment and Maintenance Methods;
Filing Info
- Accession Number: 01342820
- Record Type: Publication
- Report/Paper Numbers: NEXTRANS Project No. 0281Y02
- Contract Numbers: DTRT07-G-005 (Grant)
- Files: UTC, NTL, TRIS, USDOT
- Created Date: Jun 23 2011 9:07AM