Deep residual neural-network-based robot joint fault diagnosis method

A data driven method-based robot joint fault diagnosis method using deep residual neural network (DRNN) is proposed, where Resnet-based fault diagnosis method is introduced. The proposed method mainly deals with kinds of fault types, such as gain error, offset error and malfunction for both sensors...

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Detalles Bibliográficos
Autores principales: Pan, Jinghui, Qu, Lili, Peng, Kaixiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561173/
https://www.ncbi.nlm.nih.gov/pubmed/36229502
http://dx.doi.org/10.1038/s41598-022-22171-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561173/
https://www.ncbi.nlm.nih.gov/pubmed/36229502
http://dx.doi.org/10.1038/s41598-022-22171-7

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