PL
 |
EN
Preferencje help
Polish version English version Język
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 3

Liczba wyników na stronie
first rewind previous Strona / 1 next fast forward last
Wyniki wyszukiwania
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 1 next fast forward last
1
Content available A neural-fuzzy approach for fault diagnosis of hybrid dynamical systems: demonstration on three-tank system
Achbi Mohammed Said, Kechida Sihem, Mhamdi Lotfi, Dhouibi Hedi
Acta Mechanica et Automatica
|
2021
|
Vol. 15, no. 1
1--8
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.
2
Content available Methodology to knowledge discovery for fault diagnosis of hybrid dynamical systems: demonstration on two tanks system
Achbi Mohammed Said, Mhamdi Lotfi, Kechida Sihem, Dhouibi Hedi
Diagnostyka
|
2020
|
Vol. 21, No. 4
115--122
EN
The work carried out in this article concerns on the implementation off a diagnostic procedure for hybrid dynamic systems (HDS) whose objective is to guarantee the proper functioning of industrial installations. In this context, the main contributions of this work are summarized into three parts: The first part is oriented to the modeling approach dedicated to HDS. The aim is to find an adequate model combining both aspects (continuous and discrete dynamics). The use of Neuro-fuzzy networks makes it possible to build a model of the system and to follow all the modes without it being necessary to identify or discern them. The second part concerns the synthesis of a fault diagnostic technique based on a fuzzy inference system. A Neuro-Fuzzy network based is used for residual generation, while for the residual evaluation, a fuzzy reasoning model is used which can mainly introduce heuristic information into the analysis scheme and takes the appropriate decision regarding the actual behaviour of the process. The proposed approach is successfully applied to monitoring faults of a non-linear three-tank system and the results confirm the effectiveness of this approach.
3
Content available Diagnosis of hybrid systems through bond graph, observers and timed automata
Mhamdi Lotfi, Achbi Mohammed Said, Dhouibi Hedi, Kechida Sihem
Diagnostyka
|
2020
|
Vol. 21, No. 3
113--125
EN
Despite technological advances and progress in industrial systems, the fault diagnosis of a system remains a very important task. In fact an effective diagnosis contributes not only to improved reliability but also to a decrease in maintenance costs. This paper presents an approach to a diagnosis of hybrid systems thanks to the use of Bond Graphs, Observer and Timed Automata. Dynamic models (in normal and failing mode) are generated by an observer based methods as well as through state equations generated by the Bond Graphs model. The procedure of fault localization through a method based on the observer does not allow locating faults with the same signature of failure. Thus the diagnosis technique for the localization of these defects will be based on the time analysis using Timed Automata. The proposed approach is then validated by simulation tests in a two tanks hydraulic system.
first rewind previous Strona / 1 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.