A neural-fuzzy approach for fault diagnosis of hybrid dynamical systems: demonstration on three-tank system

• Autorzy: Achbi Mohammed Said , Kechida Sihem , Mhamdi Lotfi , Dhouibi Hedi

Identyfikatory

DOI

10.2478/ama-2021-0001

• Języki publikacji: EN

Abstrakty

EN

This work is part of the diagnostic field of hybrid dynamic systems (HDS) whose objective is to ensure proper operation of industrial facilities. The study is initially oriented to the modelling approach dedicated to hybrid dynamical systems (HDS). The objective is to look for an adequate model encompassing both aspects (continuous and event). Then, fault diagnosis technique is synthesised using artificial intelligence (AI) techniques. The idea is to introduce a hybrid version combining neural networks and fuzzy logic for residual generation and evaluation. The proposed approach is then validated on three tank system. The modelling and diagnosis approaches are developed using MATLAB/Simulink environment.

Słowa kluczowe

EN

hybrid dynamic systems; modelling; residual generation; evaluation; monitoring; fault diagnosis; neural - fuzzy approach

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Acta Mechanica et Automatica
• Rocznik: 2021
• Tom: Vol. 15, no. 1
• Strony: 1--8
• Opis fizyczny: Bibliogr. 49 poz., rys., tab., wykr.

Twórcy

autor

Achbi Mohammed Said

• Laboratoire d’Automatique et Informatique de Guelma (LAIG), Université 8 Mai 1945 Guelma, BP 401, Guelma 24000, Algérie

autor

Kechida Sihem

• Laboratoire d’Automatique et Informatique de Guelma (LAIG), Université 8 Mai 1945 Guelma, BP 401, Guelma 24000, Algérie

autor

Mhamdi Lotfi

• Laboratory of Automatic Signal and Image Processing (LARATSI), National School of Engineers of Monastir, University of Monastir, 5019, Tunisia

autor

Dhouibi Hedi

• Laboratory of Automatic Signal and Image Processing (LARATSI), National School of Engineers of Monastir, University of Monastir, 5019, Tunisia

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