Health Status Recognition Method for Rotating Machinery Based on Multi-Scale Hybrid Features and Improved Convolutional Neural Networks

Rotating machinery is susceptible to harsh environmental interference, and fault signal features are challenging to extract, leading to difficulties in health status recognition. This paper proposes multi-scale hybrid features and improved convolutional neural networks (MSCCNN) health status identif...

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Detalles Bibliográficos
Autores principales: Cao, Xiangang, Guo, Xingyu, Duan, Yong, Zhang, Fuqiang, Fan, Hongwei, Xu, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301142/
https://www.ncbi.nlm.nih.gov/pubmed/37420853
http://dx.doi.org/10.3390/s23125688

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301142/
https://www.ncbi.nlm.nih.gov/pubmed/37420853
http://dx.doi.org/10.3390/s23125688

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