Prognosis and Health Management using ...
Document type :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Article dans une revue scientifique
Title :
Prognosis and Health Management using Energy Activity
Author(s) :
Singh, Manarshhjot [Auteur]
École polytechnique universitaire de Lille [Polytech Lille]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
University of Lille
Gehin, Anne-Lise [Auteur]
Ould Bouamama, Belkacem [Auteur]
École polytechnique universitaire de Lille [Polytech Lille]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
University of Lille
Gehin, Anne-Lise [Auteur]

Ould Bouamama, Belkacem [Auteur]
Conference title :
IFAC World Congress
City :
Berlin (virtual)
Country :
Allemagne
Start date of the conference :
2020-07-12
Publisher :
Elsevier
Publication date :
2021-04-14
HAL domain(s) :
Sciences de l'ingénieur [physics]/Autre
English abstract : [en]
Accurate detection of faults in a dynamic system is very beneficial as this information can be used in a wide variety of ways by the machine operators or designers. This advantage becomes many folds when regarding the ...
Show more >Accurate detection of faults in a dynamic system is very beneficial as this information can be used in a wide variety of ways by the machine operators or designers. This advantage becomes many folds when regarding the future condition i.e. time to failure, named remaining useful life, is available in addition to that of the present condition. Thus, prognosis is one of the most useful tools to improve the working of a machine as many critical decisions can be made. Prognosis can be critical for applications that risk loss of life and property. In this paper, a hybrid method, utilizing bond graph and artificial intelligence, is proposed for system health estimation (SHE) and prognosis. The Bond Graph model is used to calculate Energy Activity, which is used as a common metric for both SHE and prognosis. The proposed method is checked by simulation on a spring mass damper system undergoing a fault.Show less >
Show more >Accurate detection of faults in a dynamic system is very beneficial as this information can be used in a wide variety of ways by the machine operators or designers. This advantage becomes many folds when regarding the future condition i.e. time to failure, named remaining useful life, is available in addition to that of the present condition. Thus, prognosis is one of the most useful tools to improve the working of a machine as many critical decisions can be made. Prognosis can be critical for applications that risk loss of life and property. In this paper, a hybrid method, utilizing bond graph and artificial intelligence, is proposed for system health estimation (SHE) and prognosis. The Bond Graph model is used to calculate Energy Activity, which is used as a common metric for both SHE and prognosis. The proposed method is checked by simulation on a spring mass damper system undergoing a fault.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
Files
- https://hal.archives-ouvertes.fr/hal-03104877/document
- Open access
- Access the document
- https://doi.org/10.1016/j.ifacol.2020.12.2766
- Open access
- Access the document
- https://doi.org/10.1016/j.ifacol.2020.12.2766
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-03104877/document
- Open access
- Access the document
- https://doi.org/10.1016/j.ifacol.2020.12.2766
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-03104877/document
- Open access
- Access the document
- https://doi.org/10.1016/j.ifacol.2020.12.2766
- Open access
- Access the document
- https://doi.org/10.1016/j.ifacol.2020.12.2766
- Open access
- Access the document