Fault detection strategy combining NARMAX model and Bhattacharyya distance for process monitoring

DOI10.1016/j.jfranklin.2021.01.001zbMath1458.93171OpenAlexW3119558406MaRDI QIDQ1996655

Lakhdar Aggoun, Yahya Chetouani

Publication date: 25 February 2021

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.01.001

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Control/observation systems involving computers (process control, etc.) (93C83)

Cites Work

• Unnamed Item
• Unnamed Item
• Adaptive control. Algorithms, analysis and applications.
• Model-based fault diagnosis techniques. Design schemes, algorithms and tools
• A neural network approach for the real-time detection of faults
• Block-oriented nonlinear system identification
• Diagnosis and Fault-Tolerant Control
• Nonlinear System Identification
• A linear parameter varying fault detection and isolation method for internal combustion spark ignition engines
• Fault-Diagnosis Applications
• Fault detection and isolation of electrical induction motors via LPV fault observers: A case study
• Encyclopedia of Distances
• A new look at the statistical model identification

This page was built for publication: Fault detection strategy combining NARMAX model and Bhattacharyya distance for process monitoring