Structural health monitoring of railway truss bridge under moving train load using decision tree models and residual neural networks
Sharan Kumar Sunchikala,
Mohan S C,
Sai Dheeraj Gopala
et al.
Abstract:This paper introduces an efficient machine learning-based structural health monitoring method for railway truss bridges, addressing the time-consuming and error-prone nature of traditional approaches. By utilizing measured vibration responses under train load, the technique employs wavelets, Fourier transforms, and spectrograms to extract damage-induced changes in signals for training machine learning models. Given the slow and impractical data collection from real-world bridges, the paper proposes generating … Show more
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