Visualized Stacked Denoising Auto-Encoder Model for Extracting and Evaluating the State Features of Rolling Bearings

Extracting intuitive operating state features from vibration signals without prior knowledge is a prospective requirement for health monitoring and fault diagnosis in bearings. In this paper, a visualized stacked denoising auto-encoder (VSDAE) model is proposed for the unsupervised extraction and qu...

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Autors principals:	Qing Zhang, Junshen Zhang, Ye Wang, Lie Chen
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2022-09-01
Col·lecció:	Machines
Matèries:	stacked denoising auto-encoder visualization feature extraction feature evaluation rolling bearing
Accés en línia:	https://www.mdpi.com/2075-1702/10/10/849
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