Fault Diagnosis of Rotating Machinery: A Highly Efficient and Lightweight Framework Based on a Temporal Convolutional Network and Broad Learning System

Efficient fault diagnosis of rotating machinery is essential for the safe operation of equipment in the manufacturing industry. In this study, a robust and lightweight framework consisting of two lightweight temporal convolutional network (LTCN) backbones and a broad learning system with incremental...

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Detalles Bibliográficos
Autores principales: Wei, Hao, Zhang, Qinghua, Gu, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305043/
https://www.ncbi.nlm.nih.gov/pubmed/37420808
http://dx.doi.org/10.3390/s23125642

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305043/
https://www.ncbi.nlm.nih.gov/pubmed/37420808
http://dx.doi.org/10.3390/s23125642

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