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Comprehensive Track Component Inspection

Description:

Track component inspection is critical for maintaining track to required safety standards. Using technology to inspect track components such as insulated joints, joint bars, fasteners, and anchors enhances the human visual track inspections performed by walking, hi-railing, or inspection car cameras/scanners along the track. This research should focus on improving the technology that is used to detect track components by improving change detection of components and using analysis tools to determine degree of deterioration.

Objective:

The objective of this research is to develop technology that will provide accurate condition assessments and change of track components. Ideally, the technology will provide the following: high-quality images and other tools that can be used for off-site inspection to compare data run-over-run, utilizes GPS positioning for locating components, and provides a software analysis tool that makes condition assessment more consistent, accurate, and less time consuming. A traffic light style warning system to alert users of changing conditions.

Benefits:

Results from this research would include improved technology for component detection and assessment. The technology would allow for better decision making that does not increase track occupancy time.

Related Research:

“Extended Field Trials of LRAIL for Automated Track Change Detection,” Federal Railroad Administration Office of Research, Development and Technology, DOT/FRA/ORD-20/14

“Laser Triangulation for Track Change and Defect Detection,” Federal Railroad Administration Office of Research, Development and Technology, DOT/FRA/ORD-20/08

“Detection of Concrete Tie Rail Seat Deterioration,” Federal Railroad Administration Office of Research, Development and Technology, DOT/FRA/ORD-19/33

“Demonstration of Commercial-Off-The-Shelf Change Detection on Railway Images,” Federal Railroad Administration Office of Research, Development and Technology, DOT/FRA/ORD-19/22

“Joint Bar Failure Study – Field Investigation,” Federal Railroad Administration Office of Research, Development and Technology, DOT/FRA/ORD-19/20

“Automatic Railroad Track Components Inspection Using Real-Time Instance Segmentation,” Beijing Jiaotong University

“Application of machine learning techniques toward time-based change in track condition using an onboard sensor in revenue-service rolling stock”, University Transportation Center on Improving Rail Transportation Infrastructure

“Rail Track Asset Management and Risk Management”, Center for Advanced Infrastructure and Transportation”

“Development of Multi-Rotor-UAV-based Rail Track Irregularity Monitoring and Measuring Platform with Image and LIDAR Sensors”, University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability

“Automated Track Geometry Monitoring System”, Mountain-Plains Consortium

“Benefit Cost Analysis of Railroad Track Monitoring Using Sensors On-Board Revenue Service Trains”, Mountain-Plains Consortium

“Principal components analysis and track quality index: A machine learning approach”, University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability

Tasks:

Development of new inspection technologies to identify missing or damaged components as well as objectively quantify the condition of track components with particular emphasis on technologies that can be deployed on unmanned platforms.

Development and demonstration of* i*nnovative approaches of using existing inspection technology products to determine new information regarding track components.

Development and demonstration of new data analysis methods to assess the conditions of track components including predictive data analysis techniques.

Implementation:

Research could be performed by universities, railroads, private industry.

Relevance:

All railroads invest large amounts of time and money inspecting track to adhere to safety standards and maintain safe and reliable track conditions. Supplementing human inspection with technology would add a modern time and cost saving approach to manual inspection methods.

Sponsoring Committee:AR050, Railroad Infrastructure Design and Maintenance
Research Period:12 - 24 months
Research Priority:High
RNS Developer:Amanda Kessler, Amtrak; Eric Sherrock, ENSCO
Date Posted:01/08/2021
Date Modified:05/27/2021
Index Terms:Maintenance of way, Railroad tracks, Track components, Inspection, Deterioration, Technological innovations,
Cosponsoring Committees: 
Subjects    
Railroads
Maintenance and Preservation

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