Health Indicator for Low-Speed Axial Bearings Using Variational Autoencoders

Health Indicator for Low-Speed Axial Bearings Using Variational Autoencoders

This paper proposes a method for calculating a health indicator (HI) for low-speed axial rolling element bearing (REB) health assessment by utilizing the latent representation obtained by variational inference using Variational Autoencoders (VAEs), trained on each speed reference in the dataset. Fur...

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Bibliographic Details
Main Authors: Martin Hemmer, Andreas Klausen, Huynh Van Khang, Kjell G. Robbersmyr, Tor I. Waag
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Bearing fault detection
condition monitoring
unsupervised learning
variational autoencoder
conditional variational autoencoder
generative models
Online Access:https://ieeexplore.ieee.org/document/9001012/

Internet

https://ieeexplore.ieee.org/document/9001012/

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