A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications

O Avci, O Abdeljaber, S Kiranyaz, M Hussein… - Mechanical systems and …, 2021 - Elsevier
Monitoring structural damage is extremely important for sustaining and preserving the
service life of civil structures. While successful monitoring provides resolute and staunch …

[HTML][HTML] Advancing railway track health monitoring: Integrating GPR, InSAR and machine learning for enhanced asset management

M Koohmishi, S Kaewunruen, L Chang, Y Guo - Automation in construction, 2024 - Elsevier
Railway track health monitoring and maintenance are crucial stages in railway asset
management, aiming to enhance the train operation quality and service life. For this aim …

[HTML][HTML] A review of synthetic and augmented training data for machine learning in ultrasonic non-destructive evaluation

S Uhlig, I Alkhasli, F Schubert, C Tschöpe, M Wolff - Ultrasonics, 2023 - Elsevier
Ultrasonic Testing (UT) has seen increasing application of machine learning (ML) in recent
years, promoting higher-level automation and decision-making in flaw detection and …

A hierarchical extractor-based visual rail surface inspection system

J Gan, Q Li, J Wang, H Yu - IEEE Sensors Journal, 2017 - ieeexplore.ieee.org
Rail inspection based on visual inspection system (VIS) has drawn much attention recently,
since VIS is automatic, fast, nondestructive, and objective. However, visual rail inspection is …

[HTML][HTML] Artificial intelligence, machine learning and smart technologies for nondestructive evaluation

H Taheri, M Gonzalez Bocanegra, M Taheri - Sensors, 2022 - mdpi.com
Nondestructive evaluation (NDE) techniques are used in many industries to evaluate the
properties of components and inspect for flaws and anomalies in structures without altering …

A real-time visual inspection system for discrete surface defects of rail heads

Q Li, S Ren - IEEE Transactions on Instrumentation and …, 2012 - ieeexplore.ieee.org
Discrete surface defects impact the riding quality and safety of a railway system. However, it
is a challenge to inspect such defects in a vision system because of illumination inequality …

Inspection of concrete structures externally reinforced with FRP composites using active infrared thermography: A review

M Yumnam, H Gupta, D Ghosh, J Jaganathan - Construction and Building …, 2021 - Elsevier
Fiber reinforced polymer (FRP) composites have become one of the most important
strengthening and retrofitting materials for reinforced concrete structures. However, these …

A coarse-to-fine model for rail surface defect detection

H Yu, Q Li, Y Tan, J Gan, J Wang… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Computer vision systems have attracted much attention in recent years for use in detecting
surface defects on rails; however, accurate and efficient recognition of possible defects …

The recent applications of machine learning in rail track maintenance: A survey

M Chenariyan Nakhaee, D Hiemstra… - Reliability, Safety, and …, 2019 - Springer
Railway systems play a vital role in the world's economy and movement of goods and
people. Rail tracks are one of the most critical components needed for the uninterrupted …

Comparison of wear and rolling contact fatigue behaviours of bainitic and pearlitic rails under various rolling-sliding conditions

Y Hu, LC Guo, M Maiorino, JP Liu, HH Ding, R Lewis… - Wear, 2020 - Elsevier
Rolling-sliding wear experiments were performed to investigate the wear and rolling contact
fatigue (RCF) behaviours of a premium pearlitic rail (PH), a carbon-free bainitic rail (BH) and …