An enhanced methodology of Fault Detection and Diagnosis based on Digital Twin. Issue 19 (2022)

• Record Type: Journal Article
• Authors: Abdoune, Farah; Nouiri, Maroua; Cardin, Olivier; Castagna, Pierre
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 19(2022)
• Page Start: 43
• Page End: 48
• Publication Date: 2022
• Subjects: Digital Twin -- Fault detection -- Fault diagnosis -- monitoring -- supervision; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.09.181
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Digital Twins (DT) have been used in a variety of industrial sectors and application areas in recent years. To avoid downtime and problems in manufacturing, DTs strive for real-time monitoring and optimization and anticipate the future status of the physical twin. Fault Detection and Diagnosis (FDD) is a maintenance field that has attracted the interest of the control and automation community as a viable means of ensuring the dependability and safety of industrial systems. An enhanced FDD methodology thought DT can provide significant benefits. The main contribution of this research focuses on the exploration of DT for FDD methodology and provides also a guideline of different alternatives in each step and highlights the importance of DT.