Topological Data Analysis and Track Geometry Data
Rail geometry defects constitute a major cause of accidents in the United States. Geometry related accidents are often very severe and damaging. While rail geometry-caused derailments continue to increase according to Federal Railroad Administration (FRA) safety data, track quality analysis remains effectively unchanged. The use of TQI or track quality index takes a narrow view of track assessment by focusing on quality without considering safety. The bipartite analysis of track quality and safety results into two maintenance types: routine and corrective maintenance respectively. This report shows how to create a hybrid index that combines both element of safety and geometry quality to predict only one maintenance regime based on track condition. It is an initial step towards the big picture of creating indices that will be iterated based on maintenance savings and defect probability thresholds. This study employs a linear and nonlinear dimension reduction technique that expresses the probability distribution of observations based on the similarity or dissimilarity in their embedded space whilst also maximizing the variance in data. This study found application in principal component analysis (PCA) and T-Stochastic neighbor embedding (TSNE) for separating geometry defects from higher dimensional space to lower dimensions. Results show that while both techniques effectively reduces track geometry data, PCA yields a potential defect probability threshold in spite of TSNE being a better geometry defect predictor. This study employs a linear and nonlinear dimension reduction technique that expresses the probability distribution of observations based on the similarity or dissimilarity in their embedded space whilst also maximizing the variance in data.
Language
- English
Project
- Status: Active
- Funding: $50000
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Sponsor Organizations:
University Transportation Center Program
1200 New Jersey Avenue, SE
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: 20180901
- Expected Completion Date: 20240930
- Actual Completion Date: 20191031
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Defects; Geometry; Maintenance of way; Railroad safety; Railroad tracks; Ride quality
- Subject Areas: Maintenance and Preservation; Planning and Forecasting; Railroads;
Filing Info
- Accession Number: 01935437
- Record Type: Research project
- Source Agency: University Transportation Center on Improving Rail Transportation Infrastructure Sustainability and Durability
- Files: UTC, RIP
- Created Date: Oct 29 2024 3:25PM