Title :
Fuzzy logic application to pre-fault diagnoses of induction motors
Author :
Consoli, A. ; Gennaro, F. ; Raciti, A. ; Testa, A.
Author_Institution :
Dept. of Electr., Electron. & Syst. Eng., Catania Univ., Italy
Abstract :
Induction machines, with power ranging from few kW to several MW, are the most used electric actuators in industry applications. Faults occurring in induction machines can negatively influence worker safety and production processes in terms of time delays and quality of the final product. Some anomalies can be detected early in order to predict fault conditions, so allowing optimizing servicing and machine stopping. The method proposed, based on artificial intelligence techniques, allows operating conditions analysis of induction motors. In particular, the fuzzy set theory is used to perform a spectrum analysis of the stator current in order to identify some types of incoming faults
Keywords :
electric machine analysis computing; fault diagnosis; fuzzy logic; fuzzy set theory; induction motors; machine testing; spectral analysis; stators; AI techniques; artificial intelligence techniques; electric actuators; fuzzy logic application; fuzzy set theory; induction motors; industry applications; operating conditions analysis; pre-fault diagnoses; prefault diagnosis; spectrum analysis; stator current analysis; Actuators; Artificial intelligence; Delay effects; Electrical fault detection; Fuzzy logic; Induction machines; Induction motors; Industry applications; Product safety; Production;
Conference_Titel :
Devices, Circuits and Systems, 1998. Proceedings of the 1998 Second IEEE International Caracas Conference on
Conference_Location :
Isla de Margarita
Print_ISBN :
0-7803-4434-0
DOI :
10.1109/ICCDCS.1998.705843
