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10 May 2024 A non-destructive technique to evaluate neutral temperature in welded rails based on impact-driven vibrations
Alireza Enshaeian, Matthew Belding, Piervincenzo Rizzo
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Proceedings Volume PC12950, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVIII; PC129500C (2024) https://doi.org/10.1117/12.3009726
Event: SPIE Smart Structures + Nondestructive Evaluation, 2024, Long Beach, California, United States
Abstract
This paper presents a novel method for monitoring continuous welded rails (CWR) to estimate longitudinal stress and determine the rail neutral temperature (RNT). The technique combines vibration measurements, finite element analysis (FEA), and machine learning (ML). FEA establishes the relationship between boundary conditions and stress, serving as the foundation for training an ML algorithm using field data from accelerometers on the track. In the field tests, the method accurately predicted RNT and stress levels, with the ML model demonstrating the ability to learn effectively from experimental data. This approach holds promise for improving rail safety, maintenance, and performance optimization.
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Alireza Enshaeian, Matthew Belding, and Piervincenzo Rizzo "A non-destructive technique to evaluate neutral temperature in welded rails based on impact-driven vibrations", Proc. SPIE PC12950, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVIII, PC129500C (10 May 2024); https://doi.org/10.1117/12.3009726
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KEYWORDS
Vibration
Finite element methods
Nondestructive evaluation
Accelerometers
Boundary conditions
Data modeling
Machine learning
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