Deep Learning-Based Acoustic Emission Scheme for Rail Crack Monitoring-Reference-Cited by-同舟云学术

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Deep Learning-Based Acoustic Emission Scheme for Rail Crack Monitoring

Published:2021-12-21 Issue: Volume: Page:
ISSN:
Container-title:2021 16th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)
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Author:

Suwansin Wara,Phasukkit Pattarapong

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9677631/9678150/09678162.pdf?arnumber=9678162

Reference13 articles.

1. Out-of-round railway wheels-a literature survey

2. The role of wear in enhancing rail life;kapoor;Tribology Series,2003

3. Wheel/rail rolling contact fatigue – Probe, predict, prevent

4. Acoustic Emission

5. Evaluation of the acoustic emission monitoring method for stress corrosion cracking on aboveground storage tank floor steel

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1. Application of Object Detection Algorithms in Non-Destructive Testing of Pressure Equipment: A Review;Sensors;2024-09-13

2. A full 3D reconstruction of rail tracks using a camera array;Measurement;2024-02

3. Sensor-based smart diagnosis of rail defects using an ann model;Asian Journal of Civil Engineering;2023-05-11

4. Current Trends on Deep Learning Techniques Applied in Iron and Steel Making Field: A Review;Tetsu-to-Hagane;2022

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