Improvement and In-Situ Application of an Evaluation Method of Ballasted-Track Condition Using Digital 2-D Image Analysis
Source abstract
Abstract
The advancement in digital image analysis methods has led to the development of various techniques, i.e., quantification of ballast gravel abrasion. In this study, the recognition rate of gravel aggregates has been significantly increased by improving the image analysis methods. The correlation between the track quality index (TQI), which is the standard deviation of vertical track irregularity and represents the condition of a high-speed railway, and the number of maintenance works was analyzed by performing an image analysis on the samples collected from various locations of a high-speed railway. The results revealed that roundness has the highest correlation with the TQI, whereas sphericity has the highest correlation with the number of maintenance works. The ballast replacement would be performed to improve maintenance efficiency if the abrasion of the ballast aggregates becomes approximately 10%.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Railway Engineering and Dynamics · Surface Roughness and Optical Measurements · Tribology and Lubrication Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Track & Roadbed Research Team, Korea Railroad Research Institute (KRRI), Cheoldobangmulgwan-ro 176, Uiwang-si, Gyeonggi-do 16105, Korea
Railroad Structure Research Team, Korea Railroad Research Institute (KRRI), Cheoldobangmulgwan-ro 176, Uiwang-si, Gyeonggi-do 16105, Korea
Funding
The Korea Railroad Research Institute (KRRI)
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