Aalto Gear Fault datasets for deep-learning based diagnosisMendeley DataMendeley DataMendeley Data

Accurate system health state prediction through deep learning requires extensive and varied data. However, real-world data scarcity poses a challenge for developing robust fault diagnosis models. This study introduces two extensive datasets, Aalto Shim Dataset and Aalto Gear Fault Dataset, collected...

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Autores principales:	Zacharias Dahl, Aleksanteri Hämäläinen, Aku Karhinen, Jesse Miettinen, Andre Böhme, Samuel Lillqvist, Sampo Haikonen, Raine Viitala
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Elsevier 2024-12-01
Colección:	Data in Brief
Materias:	Torsional vibration Lateral vibration Vibration dataset Condition monitoring Intelligent fault diagnosis Deep learning
Acceso en línea:	http://www.sciencedirect.com/science/article/pii/S2352340924011338
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