Sensor and Actuator Fault Diagnosis for Robot Joint Based on Deep CNN

This paper proposes a data-driven method-based fault diagnosis method using the deep convolutional neural network (DCNN). The DCNN is used to deal with sensor and actuator faults of robot joints, such as gain error, offset error, and malfunction for both sensors and actuators, and different fault ty...

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Detalles Bibliográficos
Autores principales: Pan, Jinghui, Qu, Lili, Peng, Kaixiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232324/
https://www.ncbi.nlm.nih.gov/pubmed/34203708
http://dx.doi.org/10.3390/e23060751

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232324/
https://www.ncbi.nlm.nih.gov/pubmed/34203708
http://dx.doi.org/10.3390/e23060751

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