Residual Swin transformer-based weld crack leakage monitoring of pressure pipeline-Reference-Cited by-同舟云学术

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Residual Swin transformer-based weld crack leakage monitoring of pressure pipeline

Published:2023-12-05 Issue: Volume: Page:
ISSN:0043-2288
Container-title:Welding in the World
language:en
Short-container-title:Weld World

Author:

Huang Jing,Zhang Zhifen^ORCID,Qin Rui,Yu Yanlong,Li Yongjie,Wen Guangrui,Cheng Wei,Chen Xuefeng

Funder

the 14th Five-Year Equipment Preliminary Research Special Technology Project

Publisher

Springer Science and Business Media LLC

Subject

Metals and Alloys,Mechanical Engineering,Mechanics of Materials

Link

https://link.springer.com/content/pdf/10.1007/s40194-023-01632-1.pdf

Reference36 articles.

1. Morks MF (2008) Overview of recent welding technology relating to pipeline construction. Trans JWRI 37:1–5

2. Dubov A, Dubov A, Kolokolnikov S (2018) Detection of local stress concentration zones in engineering products—The lacking link in the non-destructive testing system. Welding in the world 62:301–309

3. Huang J, Zhang Z, Qin R, Yu Y, Wen G, Cheng W, Chen X (2023) Lightweight neural network architecture for pipeline weld crack leakage monitoring using acoustic emission. IEEE Trans Instrum Meas 72:1–10

4. Wang L, Mao Z, Xuan H, Ma T, Hu C, Chen J, You X (2022) Status diagnosis and feature tracing of the natural gas pipeline weld based on improved random forest model. Int J Press Vessels Pip 200:104821

5. Dakhel A, Gáspár M, Koncsik Z, Lukács J (2023) Fatigue and burst tests of full-scale girth welded pipeline sections for safe operations. Welding in the World 67:1193–1208

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A review of underground transport infrastructure monitoring in CCS: Technology and Engineering Practice;Process Safety and Environmental Protection;2024-10

2. WeldNet: a lightweight deep learning model for welding defect recognition;Welding in the World;2024-04-04

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