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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...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Qing Zhang, Junshen Zhang, Ye Wang, Lie Chen
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2022-09-01
Schriftenreihe:Machines
Schlagworte:
stacked denoising auto-encoder
visualization
feature extraction
feature evaluation
rolling bearing
Online-Zugang:https://www.mdpi.com/2075-1702/10/10/849
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