Diagnostic of sensors for induction machine powered by photovoltaic generator based on fuzzy logic techniques

Abstract

This paper concerns the development of the detection of faults the sensors of an induction by estimation methods for systems modeled in the form of state representation. The sensors monitors in our case are those of speed. To achieve our objective, many of the techniques of artificial intelligence have been used to fault diagnosis of rotating machinery, where several selection techniques have been explored during the construction of the detection process. We develop and combine the model reference adaptive system (MRAS) method with fuzzy logic approach to achieve our objectives. This type of estimation is applied to replace the speed sensor in the system; this is done in order to give more robustness of the overall process, the second one is to study and develop an intelligent adaptation method based on the fuzzy logic algorithms, keeping the same performances. The new presented approach improves the performances of our system compared to the usual methods. Finally, the validity of the proposed scheme is demonstrated by a series of computer simulations and the obtained results show that the designed system can achieve satisfactory performances.