Machine vision inspection of railroad track

Camargo, Luis Fernando Molina; Resendiz, Esther; Hart, John; Edwards, J. Riley; Ahuja, Narendra; Barkan, Christopher P. L.; University Transportation Centers Program (U.S.); University of Illinois at Urbana-Champaign. Dept. of Civil and Environmental Engineering; Association of American Railroads

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Machine vision inspection of railroad track

2011-01-10
By Camargo, Luis Fernando Molina ; Resendiz, Esther ; Hart, John ; ...

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Creators:

Camargo, Luis Fernando Molina ; Resendiz, Esther ; Hart, John ; Edwards, J. Riley ; Ahuja, Narendra ; ... More +

Camargo, Luis Fernando Molina ; Resendiz, Esther ; Hart, John ; Edwards, J. Riley ; Ahuja, Narendra ; Barkan, Christopher P. L. Less -
Corporate Creators:

University Transportation Centers Program (U.S.) ; University of Illinois at Urbana-Champaign. Dept. of Civil and Environmental Engineering ; Association of American Railroads

University Transportation Centers Program (U.S.) ; University of Illinois at Urbana-Champaign. Dept. of Civil and Environmental Engineering ; Association of American Railroads Less -
Subject/TRT Terms:

[+]

Image Analysis Inspection Equipment Machine Vision Maintenance Of Way Railroad Tracks
Publication/ Report Number:

NEXTRANS Project No. 0281Y02
Resource Type:

Tech Report
OCLC Number:

705932924
Corporate Publisher:

NEXTRANS Center (U.S.)
NTL Classification:

NTL-RAIL TRANSPORTATION-RAIL TRANSPORTATION;NTL-RAIL TRANSPORTATION-Rail Safety;NTL-INTELLIGENT TRANSPORTATION SYSTEMS-INTELLIGENT TRANSPORTATION SYSTEMS;
Abstract:

North American Railways and the United States Department of Transportation

(US DOT) Federal Railroad Administration (FRA) require periodic inspection of railway

infrastructure to ensure the safety of railway operation. This inspection is a critical, but

labor-intensive task resulting in large annual operating expenditures and it has limitations

in speed, quality, objectivity, and scope. A machine vision approach is being developed

to automate inspection of specific components in the track structure. The machine vision

system consists of a video acquisition system for recording digital images of track and

custom designed algorithms to identify defects and symptomatic conditions from these

images, providing a robust solution to facilitate more efficient and effective track

inspection. The main focus of the system is the detection of irregularities and defects in

wood-tie fasteners, rail anchors, and turnout components. An experimental on-track

image acquisition system has been developed and used to acquire video in the field of

different track classes. The machine-vision algorithms use a global-to-local component

recognition approach, in which edge and texture-based detection techniques are used to

narrow the search area where components are likely to be detected. The system will be

designed to evaluate the railway infrastructure in accordance with FRA track safety

regulations, but will be adaptable to railroad-specific track standards. In the future,

defect analysis and comparison with historical data will enhance the ability for longerterm

predictive assessment of the health of the track system and its components, more

informed and proactive maintenance strategies, and improved understanding of track

structure degradation and failure modes.
Format:

PDF
Funding:

DTRT07-G-005
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:65f7c1eb411b30a1dce12e80e7b34b739761d9f9dbb0cd7ed082125a4d23e78f
Download URL:

https://rosap.ntl.bts.gov/view/dot/18644/dot_18644_DS1.pdf
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Machine vision inspection of railroad track

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