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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Bibliografski detalji
Glavni autori: Long Zhang, Lijuan Zhao, Chaobing Wang, Qian Xiao, Haoyang Liu, Hao Zhang, Yanqing Hu
Format: Članak
Jezik:English
Izdano: MDPI AG 2022-08-01
Serija:Sensors
Teme:
compound fault diagnosis
feature extraction
IACMDSR
vibration-based analysis
Online pristup:https://www.mdpi.com/1424-8220/22/17/6330

Internet

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

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