Research progress of industrial robot fault diagnosis based on deep learning

Abstract

In light of the challenges posed by the low efficiency and accuracy of conventional industrial robot fault diagnosis methods, industrial robot fault diagnosis methods based on deep learning have become a current research hot spot. This paper will focus on the research progress of convolutional neural networks, deep belief networks, generative adversarial networks, and other models of deep learning in industrial robot fault diagnosis, and analyze the future development trend of deep learning in industrial robot fault diagnosis more precisely, aiming to better provide methodological guidance for the subsequent research of industrial robot fault diagnosis.