An Improved Method for Detecting Crane Wheel–Rail Faults Based on YOLOv8 and the Swin Transformer

In the realm of special equipment, significant advancements have been achieved in fault detection. Nonetheless, faults originating in the equipment manifest with diverse morphological characteristics and varying scales. Certain faults necessitate the extrapolation from global information owing to th...

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Detalhes bibliográficos

Principais autores:	Yunlong Li, Xiuli Tang, Wusheng Liu, Yuefeng Huang, Zhinong Li
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2024-06-01
coleção:	Sensors
Assuntos:	fault detection Swin Transformer YOLOv8 special equipment feature pyramid network
Acesso em linha:	https://www.mdpi.com/1424-8220/24/13/4086
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