Fault detection and diagnosis in industrial processes with variational autoencoder: a comprehensive study

• Main Authors: Zhu, Jinlin, Jiang, Muyun, Liu, Zhong
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Process Monitoring; Deep Model
• Online Access: https://hdl.handle.net/10356/161306
• Institution: Nanyang Technological University

This work considers industrial process monitoring using a variational autoencoder (VAE). As a powerful deep generative model, the variational autoencoder and its variants have become popular for process monitoring. However, its monitoring ability, especially its fault diagnosis ability, has not been...