Advancement of data-driven SHM: A research paradigm on AE-based switch rail condition monitoring-Reference-Cited by-同舟云学术

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Advancement of data-driven SHM: A research paradigm on AE-based switch rail condition monitoring

Published:2024-09 Issue:3 Volume:3 Page:100107
ISSN:2772-9915
Container-title:Journal of Infrastructure Intelligence and Resilience
language:en
Short-container-title:Journal of Infrastructure Intelligence and Resilience

Author:

Zhou Lu^ORCID,Chen Si-Xin^ORCID,Ni Yi-Qing^ORCID,Liu Xiao-Zhou

Publisher

Elsevier BV

Reference86 articles.

1. An integrated deep neural network model combining 1D CNN and LSTM for structural health monitoring utilizing multisensor time-series data;Ahmadzadeh;Struct. Health Monit.,2024

2. Phased array ultrasonic inspection of near-surface cracks in a railhead and its verification with rail slicing;Anandika;Insight-Non-Destructive Testing and Condition Monitoring,2020

3. Damage monitoring of carbon fibre reinforced polymer composites using acoustic emission technique and deep learning;Barile;Compos. Struct.,2022

4. Modeling guided wave propagation with application to the long-range defect detection in railroad tracks;Bartoli;NDT E Int,2005

5. Modeling wave propagation in damped waveguides of arbitrary cross-section;Bartoli;J. Sound Vib.,2006

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