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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Detalles Bibliográficos
Autores principales: Zhang, Long, Zhao, Lijuan, Wang, Chaobing, Xiao, Qian, Liu, Haoyang, Zhang, Hao, Hu, Yanqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460066/
https://www.ncbi.nlm.nih.gov/pubmed/36080790
http://dx.doi.org/10.3390/s22176330

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460066/
https://www.ncbi.nlm.nih.gov/pubmed/36080790
http://dx.doi.org/10.3390/s22176330

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