DocumentCode
658088
Title
Sensor and actuator fault detection and isolation based on artificial neural networks and fuzzy logic applicated on induction motor
Author
Adouni, Amel ; Ben Hamed, Mouna ; Flah, Aymen ; Sbita, Lassaad
Author_Institution
Electr. Dept., Nat. Eng. Sch. of Gabes, Gabes, Tunisia
fYear
2013
fDate
6-8 May 2013
Firstpage
917
Lastpage
922
Abstract
This paper presents a scheme for fault detection and isolation (FDI). It deals with sensors and actuator fault of an induction machine. This scheme is established with artificial intelligent techniques in order to resolve two big troubles. The first is the detection problem. It is resolved with the neural network and the second is the isolation difficulty, it solved using the fuzzy logic. The proposed FDI approach is implemented on Matlab/Simulink software and tested under three types of fault (current, speed sensor fault and inverter fault). The obtained results improving the importance of this method. Then, the actuator and sensor fault are detected and isolated successfully.
Keywords
fault diagnosis; fuzzy logic; induction motors; neural nets; sensors; Matlab/Simulink software; actuator fault detection; artificial intelligent techniques; artificial neural networks; fault isolation; fuzzy logic; induction machine; induction motor; sensor fault; Actuators; Analytical models; Circuit faults; Fuzzy logic; Induction motors; Inverters; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Decision and Information Technologies (CoDIT), 2013 International Conference on
Conference_Location
Hammamet
Print_ISBN
978-1-4673-5547-6
Type
conf
DOI
10.1109/CoDIT.2013.6689665
Filename
6689665
Link To Document