Robust Detection of Minute Faults in Uncertain Systems Using Energy Activity

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

Type de document :

Compte-rendu et recension critique d'ouvrage

DOI :

10.3390/pr9101801

Titre :

Robust Detection of Minute Faults in Uncertain Systems Using Energy Activity

Auteur(s) :

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

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ould-Boaumama, Belkacem [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Titre de la revue :

Processes

Pagination :

1801

Éditeur :

MDPI

Date de publication :

2021-10

ISSN :

2227-9717

Discipline(s) HAL :

Sciences de l'ingénieur [physics]/Automatique / Robotique

Résumé en anglais : [en]

Fault detection is one of the key steps in Fault Detection and Isolation (FDI) and, therefore, critical for subsequent prognosis or implementation of Fault Tolerant Control (FTC). It is, therefore, advisable to utilize ...
Lire la suite >Fault detection is one of the key steps in Fault Detection and Isolation (FDI) and, therefore, critical for subsequent prognosis or implementation of Fault Tolerant Control (FTC). It is, therefore, advisable to utilize detection algorithms which are quick and can detect the smallest faults. Model-based detection methods satisfy both these criteria and should be preferred. However, a big limitation for model-based methods is that they require the accurate value of the component parameters, which is difficult to obtain in real situations. This limits the accuracy of model-based methods. This paper proposes a new method for fault detection using Energy Activity (EA) which can detect minute levels of fault in systems with high component uncertainty. Different forms of EA are developed for use as an FDI metric. The proposed forms are simulated using a two-tank system under various types of faults. The results are compared with each other and with the traditional model-based FDI method using Analytical Redundancy Relations (ARRs). The simulations are performed considering model uncertainties to check the inherent performance of the methods. From initial simulations, it is established that the integral form of EA is most suited for fault detection. The integral for if EA is then tested using a real two-tank system considering both the model and measurement uncertainties.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL

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