Domain-Adaptive Prototype-Recalibrated Network with Transductive Learning Paradigm for Intelligent Fault Diagnosis under Various Limited Data Conditions

In real industrial scenarios, intelligent fault diagnosis based on data-driven methods has been widely researched in the past decade. However, data scarcity is widespread in fault diagnosis tasks owning to the difficulties in collecting adequate data. As a result, there is an increasing demand for b...

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Detalles Bibliográficos
Autores principales: Kuang, Jiachen, Tao, Tangfei, Wu, Qingqiang, Han, Chengcheng, Wei, Fan, Chen, Shengchao, Zhou, Wenjie, Yan, Cong, Xu, Guanghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460280/
https://www.ncbi.nlm.nih.gov/pubmed/36080992
http://dx.doi.org/10.3390/s22176535

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460280/
https://www.ncbi.nlm.nih.gov/pubmed/36080992
http://dx.doi.org/10.3390/s22176535

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