Multiple Enhanced Sparse Representation via IACMDSR Model for Bearing Compound Fault Diagnosis

Multiple Enhanced Sparse Representation via IACMDSR Model for Bearing Compound Fault Diagnosis

For the sake of addressing the issue of extracting multiple features embedded in a noise-heavy vibration signal for bearing compound fault diagnosis, a novel model based on improved adaptive chirp mode decomposition (IACMD) and sparse representation, namely IACMDSR, is developed in this paper. First...

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Bibliographic Details
Main Authors: Long Zhang, Lijuan Zhao, Chaobing Wang, Qian Xiao, Haoyang Liu, Hao Zhang, Yanqing Hu
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Sensors
Subjects:
compound fault diagnosis
feature extraction
IACMDSR
vibration-based analysis
Online Access:https://www.mdpi.com/1424-8220/22/17/6330

Internet

https://www.mdpi.com/1424-8220/22/17/6330

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