Machine-learning-assisted analysis of highly transient X-ray imaging sequences of weld pools-Reference-Cited by-同舟云学术

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Machine-learning-assisted analysis of highly transient X-ray imaging sequences of weld pools

Published:2024-08-13 Issue:1 Volume:104 Page:
ISSN:0950-0839
Container-title:Philosophical Magazine Letters
language:en
Short-container-title:Philosophical Magazine Letters

Author:

Wu Fan¹²,Zhang Juzheng³,Falch Ken Vidar¹,Mirihanage Wajira¹

Affiliation:

1. Department of Materials, The University of Manchester, Manchester, UK

2. Department of Engineering, University of Leicester, Leicester, UK

3. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, People’s Republic of China

Funder

Engineering and Physical Sciences Research Council

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09500839.2024.2388159

Reference25 articles.

1. Revisiting fundamental welding concepts to improve additive manufacturing: From theory to practice

2. Keyhole threshold and morphology in laser melting revealed by ultrahigh-speed x-ray imaging

3. Microstructure evolution and mechanical properties in a gas tungsten arc welded Fe42Mn28Co10Cr15Si5 metastable high entropy alloy

4. Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis

5. A simulation-based approach to characterise melt-pool oscillations during gas tungsten arc welding

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