Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder

Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder

With growing dependence of industrial robots, a failure of an industrial robot may interrupt current operation or even overall manufacturing workflows in the entire production line, which can cause significant economic losses. Hence, it is very essential to maintain industrial robots to ensure high-...

Full description

Bibliographic Details
Main Authors: Tingting Chen, Xueping Liu, Bizhong Xia, Wei Wang, Yongzhi Lai
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Anomaly detection
industrial robots
sliding window
variational autoencoder
convolutional neural network
Online Access:https://ieeexplore.ieee.org/document/9023488/

Internet

https://ieeexplore.ieee.org/document/9023488/

Similar Items