Simultaneously Low Rank and Group Sparse Decomposition for Rolling Bearing Fault Diagnosis

Simultaneously Low Rank and Group Sparse Decomposition for Rolling Bearing Fault Diagnosis

Singular value decomposition (SVD) methods have aroused wide concern to extract the periodic impulses for bearing fault diagnosis. The state-of-the-art SVD methods mainly focus on the low rank property of the Hankel matrix for the fault feature, which cannot achieve satisfied performance when the ba...

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Bibliographic Details
Main Authors: Kai Zheng, Yin Bai, Jingfeng Xiong, Feng Tan, Dewei Yang, Yi Zhang
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Sensors
Subjects:
simultaneously low rank and group sparse
Hankel matrix
singular value decomposition
periodic information index
bearing fault diagnosis
Online Access:https://www.mdpi.com/1424-8220/20/19/5541

Internet

https://www.mdpi.com/1424-8220/20/19/5541

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