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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Hlavní autoři:	Haoguang Wang, Wangzhe Du, Guanhua Xu, Yangfan Sun, Hongyao Shen
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2024-05-01
Edice:	Scientific Reports
Témata:	Crack detection Rail transit Deep learning Computer vision Fluorescent magnetic particle inspection Composite magnetization
On-line přístup:	https://doi.org/10.1038/s41598-024-61396-6
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