An Index for Rail Weld Health Assessment in Urban Metro Using In-Service Train

Rail welds are considered as the weak part of a railway track. Their defects and health can directly affect wheel-rail interaction, track safety, and reliability. Current practices for rail welds health assessment are based on 2D vertical and lateral wear measurement which needs time and track block...

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Bibliographic Details
Published in:Mathematical problems in engineering 2022-12, Vol.2022, p.1-10
Main Authors: Shadfar, Morad, Molatefi, Habibollah, Nasr, Asghar
Format: Article
Language:English
Subjects:
Acceleration
Accuracy
Algorithms
Axleboxes
Condition monitoring
Defects
Engineering
Fast Fourier transformations
Geometry
Mechanical components
Methods
Neural networks
Nondestructive testing
Principal components analysis
Railway tracks
Reliability analysis
Sensors
Statistical methods
Structural health monitoring
Structural vibration
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Summary:Rail welds are considered as the weak part of a railway track. Their defects and health can directly affect wheel-rail interaction, track safety, and reliability. Current practices for rail welds health assessment are based on 2D vertical and lateral wear measurement which needs time and track blocking. The development of inertia-based condition monitoring methods such as measuring axle box acceleration (ABA) comes with a crucial question on criteria or index for each rail track component health monitoring. In this study, an index for evaluation of rail weld health is proposed through integrated numerical and field experiment data within a metro line using the ABA technique. The relationship between the speed, wheel structural vibration, and acceleration amplitude is investigated using fast Fourier transformation (FFT) and a nonlinear neural network principal component analysis (PCA) model. An index is introduced to assess weld severity level based on the statistical method. This index is simple and applicable for maintenance practice.
ISSN:1024-123X
1563-5147
DOI:10.1155/2022/4911952