Wound rotor induction machine (WRIM) has been extensively used in different applications such as medium-power wind turbine and traction systems. Since, these machines works under harsh and difficult conditions, condition monitoring of such system are crucial. Different electrical and mechanical signatures of machines were used for electrical and mechanical fault detection in electrical machines such as vibration, acoustic emission, stray flux and stator current signature. In recent years, stator current signature analysis due to simplicity, cost-effectiveness and availability has been considered for fault detection process in comparison with pervious conventional methods such as acoustic and vibration. In this paper, high-resolution technique based on chirp-Z transform is used for rotor asymmetry fault (RAF) detection in induction machines through stator current signature analysis. In this regard, Teager-Kaiser energy operator (TKEO) technique for demodulation fault characteristic frequency is used as pre-processing stage to avoid leakage of supply frequency. The method has better accuracy due to better spectral resolution and resolvability. Furthermore, computational complexity in the proposed method will be reduced in compare to the pervious conventional ones which have used Fast Fourier transform (FFT). The proposed technique is tested through synthetic and experimental stator current of WRIM in healthy and faulty conditions with different rotational speeds and fault severities. The results show the validity of proposed method in rotor asymmetry fault detection through stator current signature of WRIM.
Ghadirinezhd, R., & Hoseintabar, M. (2024). High-Resolution Rotor Fault Diagnosis of Wound Rotor Induction Machine Based on Stator Current Signature analyse. AUT Journal of Electrical Engineering, 56(Issue 1 (Special Issue)), 4-4. doi: 10.22060/eej.2023.21583.5483
MLA
Reza Ghadirinezhd; Mohammad Hoseintabar. "High-Resolution Rotor Fault Diagnosis of Wound Rotor Induction Machine Based on Stator Current Signature analyse". AUT Journal of Electrical Engineering, 56, Issue 1 (Special Issue), 2024, 4-4. doi: 10.22060/eej.2023.21583.5483
HARVARD
Ghadirinezhd, R., Hoseintabar, M. (2024). 'High-Resolution Rotor Fault Diagnosis of Wound Rotor Induction Machine Based on Stator Current Signature analyse', AUT Journal of Electrical Engineering, 56(Issue 1 (Special Issue)), pp. 4-4. doi: 10.22060/eej.2023.21583.5483
VANCOUVER
Ghadirinezhd, R., Hoseintabar, M. High-Resolution Rotor Fault Diagnosis of Wound Rotor Induction Machine Based on Stator Current Signature analyse. AUT Journal of Electrical Engineering, 2024; 56(Issue 1 (Special Issue)): 4-4. doi: 10.22060/eej.2023.21583.5483