Titre :

Robust Fault Decision: Application to an Omni Directional Mobile Robot

Auteur(s) :

Chatti, Nizar [Auteur]
LAGIS-MOCIS
Gehin, Anne-Lise [Auteur]
Systèmes Tolérants aux Fautes [STF]
Ould Bouamama, Belkacem [Auteur]
LAGIS-MOCIS

Titre de l’ouvrage :

Mechatronic & Innovative Applications

Éditeur :

Bentham Science

Date de publication :

2012-06-30

ISBN :

978-1-60805-440-4

Mot(s)-clé(s) en anglais :

Bond graphs
Diagnosis
Robust Decision Making
Modeling
Graphical approach
Analytical Redundancy Relations
Supervision
Fuzzy logic
Monitoring
Dynamic behaviour
Fault-indicators
Model-Based diagnosis
Fault detection and isolation
Parameter uncertainties
Mobile robotics

Discipline(s) HAL :

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

Résumé en anglais : [en]

Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems and avoiding the execution of an unsafe behaviour. This chapter deals with Robust Decision Making (RDM) for fault detection of ...
Lire la suite >Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems and avoiding the execution of an unsafe behaviour. This chapter deals with Robust Decision Making (RDM) for fault detection of electromechanical systems by combining the advantages of Bond Graph (BG) modeling and Fuzzy logic reasoning. A fault diagnosis method implemented in two stages is proposed. In the first stage, the residuals are deduced from the BG model allowing the building of a Fault Signature Matrix (FSM) according to the sensitivity of residuals to different parameters. In the second stage, the result of FSM and the robust residual thresholds are used by the fuzzy reasoning mechanism in order to evaluate a degree of detectability for each set of components. Finally, in order to make robust decision according to the detected fault component, an analysis is done between the output variables of the fuzzy system and components having the same signature in the FSM. The performance of the proposed fault diagnosis methodology is demonstrated through experimental data of an omni directional robot.Lire moins >

Langue :

Anglais

Audience :

Non spécifiée

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL