Lissajous Curve of an Auxiliary Winding Voltage Park Components for Doubly-Fed Induction Machine Electrical Faults Diagnosis

Article Preview

Abstract:

In this paper, a new method for doubly-fed induction machine electrical faults diagnosis is presented. It is based on the so-called the Lissajous curve of an auxiliary winding voltage Park components. For this purpose, time domain mathematical model of a three phase doubly-fed induction machine and expressions of the inserted winding voltage and its Park components are presented. Simulation results curried out for non defected and defected machine show the effectiveness of the proposed method.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 860-863)

Pages:

2223-2231

Citation:

Online since:

December 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] B. Jha, and K. Ram Mohan Rao: Doubly Fed Induction Generator Analysis Through Wavelet Technique, Journal of Engineering Sciences and Technology Review , Vol. 2, No. 1, pp.63-67, June (2009).

DOI: 10.25103/jestr.021.12

Google Scholar

[2] Y. Amirat, V. Choqueuse and M. Benbouzid: Wind Turbine Bearing Failure Detection Using Generator Stator Current Homopolar Component Ensemble Empirical Mode Decomposition. IECON (2012).

DOI: 10.1109/iecon.2012.6389263

Google Scholar

[3] H. Nejjari, and M. El Hachemi Benbouzid: Monitoring and Diagnosing of Induction Motors Electrical Fault Using a Current Park's Pattern Learning Approach. IEEE Transactions on Industry Applications. Vol 36, No 3, pp.730-735, May (2000).

DOI: 10.1109/28.845047

Google Scholar

[4] F. Zidani, M. El Hachemi Benbouzid, D. Diallo, and M.S. Nait Said: Induction Motor Stator Faults Diagnosis by a Current Concordia Pattern-Based Fuzzy Decision System. IEEE Transaction on Energy Conversion, Vol 18, N° 4, pp: 469-475. December (2003).

DOI: 10.1109/tec.2003.815832

Google Scholar

[5] M. El Hachemi Benbouzid: A Review of Induction Motors Signature Analysis as a Medium for Faults Detection. IEEE Transactions on Industrial Electronics. Vol. 47, N° 5, pp: 984-993. October (2000).

DOI: 10.1109/41.873206

Google Scholar

[6] W.T. Thomson, and M. Fenger: Current Signature Analysis to Detect Induction Motor Faults. IEEE Industry Applications Magazine, pp: 26-34. July- August (2001).

DOI: 10.1109/2943.930988

Google Scholar

[7] W.T. Thomson, and M. Fenger: Case Histories of Current Signature Analysis to Detect Faults in Induction Motor Drives. IEEE Industry Applications Magazine, Vol 7, N° 4, pp: 6-34. July- August (2001).

DOI: 10.1109/2943.930988

Google Scholar

[8] L. El Menzhi, and A. Saad: Induction Motor Electrical Fault Diagnosis Using Voltage Spectrum of an Auxiliary Winding. ICEMS (2007). Seoul South Korea, Vol 8, Issue, No 11, pp.1028-1032, October (2007).

DOI: 10.1109/icems12746.2007.4411959

Google Scholar

[9] L. El Menzhi, and A. Saad: Induction Motor Fault Diagnosis Using voltage Spectrum of Auxiliary Winding and Lissajous Curve of its Park Components. Advanced Materials Research Journal, Vols, 805-806 (2013), pp: 963-979.

DOI: 10.4028/www.scientific.net/amr.805-806.963

Google Scholar

[10] L. El Menzhi, and A. Saad: Induction Generator Electrical Fault Diagnosis Using Voltage Spectrum of an Auxiliary Winding. ICEMS (2013). Busan South Korea, October (2013).

DOI: 10.1109/icems12746.2007.4411959

Google Scholar

[11] A. Menacer, M. Nait Said, H. Benakcha, and S. Drid: Stator Current Analysis of Incipient Fault into Asynchronous Motor Rotor Bars Using Fourier Fast Transform. Journal of Electrical Engineering, Vol, 55, N°, 5-6 pp: 122-130. Published (2004).

DOI: 10.1109/epepemc.2006.283287

Google Scholar