Exploiting generative adversarial networks as an oversampling method for fault diagnosis of an industrial robotic manipulator

Article

Abstract: Data-driven machine learning techniques play an important role in fault diagnosis, safety, and maint

Palabras claves:

Fault diagnosis, Feature Extraction, Generative Adversarial Network, random forest, Unbalance data

Autores:

Diego Cabrera Mendieta, Diego R. Cabrera, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, Pu Z., René-Vinicio Sánchez Loja

Fuentes:

google

scopus