Prognosis and Health Management using Energy Activity

Singh, Manarshhjot; Gehin, Anne-Lise; Ould Bouamama, Belkacem

Document type :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1016/j.ifacol.2020.12.2766

Title :

Prognosis and Health Management using Energy Activity

Author(s) :

Singh, Manarshhjot [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
École polytechnique universitaire de Lille [Polytech Lille]
Gehin, Anne-Lise [Auteur]

Ould Bouamama, Belkacem [Auteur]

Journal title :

IFAC-PapersOnLine

Publisher :

Elsevier

Publication date :

2021-04-14

ISSN :

2405-8963

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 >

Language :

Anglais

Popular science :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

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