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Automated crack detection of train rivets using fluorescent magnetic particle inspection and instance segmentation

Abstract The railway rivet is one of the most important and easily damaged parts of the connection. If rivets develop cracks during the production process, their load-bearing capacity will be reduced, thereby increasing the risk of failure. Fluorescent magnetic particle flaw detection (FMPFD) is a w...

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Principais autores: Haoguang Wang, Wangzhe Du, Guanhua Xu, Yangfan Sun, Hongyao Shen
Format: Artigo
Sprog:Inglês
Udgivet: Nature Portfolio 2024-05-01
Serier:Scientific Reports
Fag:
Crack detection
Rail transit
Deep learning
Computer vision
Fluorescent magnetic particle inspection
Composite magnetization
Online adgang:https://doi.org/10.1038/s41598-024-61396-6
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