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

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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Bibliographic Details
Main Authors: Qing Zhang, Junshen Zhang, Ye Wang, Lie Chen
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Machines
Subjects:
stacked denoising auto-encoder
visualization
feature extraction
feature evaluation
rolling bearing
Online Access:https://www.mdpi.com/2075-1702/10/10/849

Internet

https://www.mdpi.com/2075-1702/10/10/849

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