Broken rotor bars fault detection in induction motors using FFT: simulation and experimentally study

December 28, 2019

  • Ridha KECHIDA Faculty of Technology, University of El-oued, PO Box 789 El-oued 39000, Algeria
  • Arezki Menacer LGEB Laboratory Department of Electrical Engineering, University of Biskra, Algeria
  • Hakima Cherif Faculty of Technology, University of El-oued, PO Box 789 El-oued 39000, Algeria
Keywords: Induction Motors, Broken Rotor Bars, FFT, Fault Diagnosis.

Abstract

This paper presents the fault detection of broken rotor bars based on the analysis technique, such as the fast Fourier transform (FFT), which utilize the steady-state spectral components of the stator quantities is considered. This technique has been given expected results, the accuracy of this technique depends on the loading conditions and constant speed of the motor. This method shows good theoretical and experimental results.

DOI

Cite as: Kechida, R., Menacer, A., Cherif, H. (2019). Broken Rotor Bars Fault Detection in Induction Motors using FFT: Simula-tion and Experimentally Study. Algerian Journal of Engineering and Technology, 1(1), 019-024.  https://doi.org/10.5281/zenodo.3595143

References

  1. Ayhan, B. Trussell, H.J. Chow, Mo-Yuen. Song, Myung-Hyun (2008). On the use of a lower sampling rate for broke rotor bar detection with DTFT and AR-based spectrum methods. IEEE Trans. Industrial Electronics, 55(3), 1421-1434.
  2. Bachir, S. Tnani, S Trigeassou. J-C. and Champenois, G. (2006). Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines. IEEE Transitions Industrial Electronics, 53(3), 963–973.
  3. Bellini, A. Filippetti, F. Tassoni, C. and Capolino. G.A. (2008). Advances in diagnostic techniques for induction machines. IEEE Transactions on Industrial Electronics, 55(12), 4109-4125.
  4. Silva, A.M.D. Povinelli, R. J. and Demerdash, N. A. O. (2008). Induction machine broken bar and stator short-circuit fault diagnostics based on three-phase stator current envelopes. IEEE Transactions on Industrial Electronics, 55(3), 1310–1318.
  5. Bossio, G. R. De Angelo, C. Bossio, H. J. M. Pezzani, C. M. and García, G.O.(2009). Separating broken rotor bars and load oscillations on im fault diagnosis through the instantaneous active and reactive currents. IEEE Transactions on Industrial Electronics, 56(11), 4571–4580.
  6. Bouzida, A. Touhami, O. Ibtiouen, R. Belouchrani, A. Fadel, M. and Rezzoug, A. (2011). Fault Diagnosis in industrial induction Machines through Discrete Wavelet Transform. IEEE Transactions Industrial Electronics, 58(9), 4385–4395.
  7. Sadeghian, A. Ye, Z. and Wu, B. (2009). Online detection of broken rotor bars in induction motors by wavelet packet decomposition and artificial neural networks. IEEE Transactions Instrumentation and Measurement, 58(7), 2253-2263.
  8. Cusidó, J. Romeral, L. Ortega, J. A. Rosero, J. A. Garcia Espinosa, A. (2008). Fault detection in induction machines using power spectral density in wavelet decomposition. IEEE Trans. Industrial Electronics, 55(3), 633-643.
  9. Zhou, W. Habetler, T. G. and Harley, R.G. (2007). Stator current based bearing fault detection techniques: A general review, IEEE international Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, pp. 7-10.
  10. Blodt, M. Granjon, P. Raison, B. Rostaing, G. (2008). Models for bearing damage detection in induction motors using stator current monitoring. IEEE Transactions on Industrial Electronics, 55(4), 1813-1822.
  11. Douglas, H. Pillay, P and Ziarani, A. K. (2005). Broken rotor bar detection in induction machines with transient operating speeds. IEEE Transactions on Energy Conversion, 20(1), 135-141.
  12. Antonio-Daviu, J.A. Riera-Guasp, M. Floch, J. R. Palomares, M.P.M. (2006). Validation of a new method for the diagnosis of rotor bar failures via wavelet transform in industrial induction machines. IEEE Transactions on Industry Applications, 42(4), 990–996.
  13. Ordaz-Moreno, A. Romero-Troncoso, R.J. Vite-Frias, J.A. Rivera-Gillen, J.R. Garcia-Perez, A. (2008). Automatic online diagnosis algorithm for broken-bar detection on induction motors based on discrete wavelet transform for FPGA implementation. IEEE Transactions on Industrial Electronics, 55(5), 2193-2202.
  14. Cusido, J. Rosero, J. Aldabas, E. Ortega, L. Romeral, J.A. (2006). New fault detection techniques for induction motors. Electrical Power Utilization Quality and, Magazine, 11(1), 39-45.
  15. Caruso, G. Iannuzzi, D. Maceri, F. Pagano, E. Piegari, L. (2008). Torsional eigenfrequency identification of squirrel cage rotors of induction motors. International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 1271–1275.
  16. Benbouzid, M.E.H. (2000). A review of induction motors signature analysis as a medium for faults detection. IEEE Trans Indus Elect, 47(5), 984–993.
  17. Li, W. (2006). Detection of induction motor faults: A comparison of stator current, vibration and acoustic methods. Journal of Vibration and Control. 12(2). 165.

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Published
2019-12-28
How to Cite
KECHIDA, R., Menacer, A., & Cherif, H. (2019). Broken rotor bars fault detection in induction motors using FFT: simulation and experimentally study . Algerian Journal of Engineering and Technology, 1(1), 19-24. Retrieved from http://jetjournal.org/index.php/ajet/article/view/10