Railroad Infrastructure Health Assessment Using Multiway Data Factorization - A Case for Railroad Track Geometry Data
Large amounts of railroad track geometry data are generated by both passenger and freight railroad systems in the U.S. and results from the analysis of this data could serve as the basis for proactive maintenance to improve safety and system performance. Different methods have been used to analyze track geometry data but this work focuses on how multiway data analysis can be used to generate insights from this data. The results obtained from this analysis are compared to the 2 dimensional approach for analyzing the same data in order to showcase the main advantages associated with using multidimensional data analysis techniques in the management of railroads.
Language
- English
Project
- Status: Completed
- Funding: $50000
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Contract Numbers:
69A3551747132
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
University of Delaware, Newark
Department of Civil Engineering
301 DuPont Hall
Newark, DE United States 19716 -
Project Managers:
Zarembski, Allan
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Performing Organizations:
University of Delaware, Newark
Department of Civil Engineering
301 DuPont Hall
Newark, DE United States 19716 -
Principal Investigators:
Attoh-Okine, Nii
- Start Date: 20170601
- Expected Completion Date: 20210430
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Data analysis; Geometry; Maintenance of way; Railroad tracks; Structural health monitoring
- Subject Areas: Data and Information Technology; Maintenance and Preservation; Railroads;
Filing Info
- Accession Number: 01703227
- Record Type: Research project
- Source Agency: University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability
- Contract Numbers: 69A3551747132
- Files: UTC, RiP
- Created Date: Apr 27 2019 8:08PM