A novel deep learning approach for intelligent bearing fault diagnosis under extremely small samples

Rotor bearing health is crucial for ensuring the operational stability of rotating equipment. Deep learning-based fault diagnosis methods have achieved widespread success due to their superior fault identification capability. However, conventional deep learning methods that rely on large quantities...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Netherlands), 2024-04, Vol.54 (7), p.5306-5316
Hauptverfasser:	Ding, Peixuan, Xu, Yi, Qin, Pan, Sun, Xi-Ming
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Computer Science Deep learning Fault diagnosis Feature extraction Machines Manufacturing Mechanical Engineering Processes Signal transmission
Online-Zugang:	Volltext
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