Investigating Machine Learning and Control Theory Approaches for Process Fault Detection: A Comparative Study of KPCA and the Observer-Based Method

Investigating Machine Learning and Control Theory Approaches for Process Fault Detection: A Comparative Study of KPCA and the Observer-Based Method

The paper focuses on the importance of prompt and efficient process fault detection in contemporary manufacturing industries, where product quality and safety protocols are critical. The study compares the efficiencies of two techniques for process fault detection: Kernel Principal Component Analysi...

Full description

Bibliographic Details
Main Authors: Fatma Lajmi, Lotfi Mhamdi, Wiem Abdelbaki, Hedi Dhouibi, Khaled Younes
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Sensors
Subjects:
KPCA
observer-based method
machine learning
unsupervised learning
nonlinear process monitoring
fault detection
Online Access:https://www.mdpi.com/1424-8220/23/15/6899

Internet

https://www.mdpi.com/1424-8220/23/15/6899

Similar Items