Title :
Modeling and detection of eccentricity fault in Switched Reluctance Motor
Author :
Ilhem, Bouchareb ; Amar, Bentounsi ; Abdesselam, Lebaroud ; Mouhamed, Bouchahdane ; Fares, Rebbahi ; Bachir, Batoun
Author_Institution :
Dept. of Electr. Eng., Univ. Mentouri Constantine, Constantine, Algeria
Abstract :
This paper presents the effects of dynamic air-gap eccentricity (DE) on the performances of a 6/4 Switched Reluctance Machine (SRM) through finite Element Analysis by means of Finite Element Method Magnetics (FEMM). The Time-Frequency Representation (TFR) is carried out to study the effect of DE on the output torque signal. Time-frequency representation is an appropriate tool for detecting the mechanical failures from the torque analysis. Relatively few works study the influence of eccentricity on the dynamic response of SRM. Various time-frequency methods as Wigner-Ville distribution (WVD) and Short Time Fourier Transform (STFT) are used and illustrated to fault detection. TFR method allows an accurate detection independent from the type of fault. Finally, simulation results of healthy and faulty cases are presented.
Keywords :
Fourier transforms; Wigner distribution; dynamic response; finite element analysis; machine insulation; reluctance motors; time-frequency analysis; FEMM; STFT; TFR; WVD; Wigner-Ville distribution; dynamic air-gap eccentricity; dynamic response; eccentricity fault detection; eccentricity fault modeling; finite element analysis; finite element method magnetics; mechanical failure detection; short time fourier transform; switched reluctance motor; time-frequency representation; torque analysis; torque signal; Finite element methods; Induction motors; Reluctance motors; Rotors; Switches; Torque; Eccentricity; detection; finite-element analysis; switched reluctance motor; time-frequency representation;
Conference_Titel :
Environment and Electrical Engineering (EEEIC), 2011 10th International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4244-8779-0
DOI :
10.1109/EEEIC.2011.5874721