A multilevel recovery diagnosis model for rolling bearing faults from imbalanced and partially missing monitoring data

A multilevel recovery diagnosis model for rolling bearing faults from imbalanced and partially missing monitoring data

As an indispensable part of large Computer Numerical Control machine tool, rolling bearing faults diagnosis is particularly important. However, due to the imbalanced distribution and partially missing of collected monitoring data, such diagnostic issue generally emerging in manufacturing industry is...

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Bibliographic Details
Main Authors: Jing Yang, Guo Xie, Yanxi Yang, Qijun Li, Cheng Yang
Format: Article
Language:English
Published: AIMS Press 2023-01-01
Series:Mathematical Biosciences and Engineering
Subjects:
regulable resampling
multilevel recovery
sparse autoencoder
rolling bearing
fault diagnosis
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023242?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2023242?viewType=HTML

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