Modelling and Wavelet Based Analysis of Stator Turn to Turn Fault in Induction Motor

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2017 by IJETT Journal
Volume-44 Number-4
Year of Publication : 2017
Authors : Ramees Muhammed M K P
  10.14445/22315381/IJETT-V44P233

MLA 

Ramees Muhammed M K P "Modelling and Wavelet Based Analysis of Stator Turn to Turn Fault in Induction Motor", International Journal of Engineering Trends and Technology (IJETT), V44(3),163-169 February 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
The aim of this paper is to present a new approach for stator phase to phase fault detection in induction machines. This new method uses the infinity Norm of wavelet coefficients, obtained from n¬-level decomposition of each phase current to identify stator phase to phase faults in induction machines. The proposed algorithm can operate independent of the loading conditions. For the analysis, a mathematical model is developed which is valid for steady state and transient conditions. The same has been simulated using MATLAB/SIMULINK software and tested for stator phase to phase fault. Simulation results are provided to support the research. The results prove that it can constitute a useful tool for stator phase to phase fault detection.

 References

[1] R. R. Obaid and T. G. Habetler, “Current-based algorithm for mechanical fault detection in induction motors with arbitrary load conditions,” IEEE Industry Applications Society Annual Meeting, pp. 1347-1351, 2003.
[2] Milrtic A. and Cettolo M., “ Frequency converter influence on induction motor rotor faults detection using motor current signature analysis-Experimental research”, Symposium on Diagnostic for electric machines, Power Electronics and Derives, Atlanta, GA, USA, 24-26 march, pp. 124-128, Aug.2003.
[3] Szabó L., Bíró K.Á., Dobai J.B., "On the Rotor Bar Faults Detection in Induction Machines", Proceedings of the International Scientific Conference Micro CAD, Miskolc (Hungary), Section J (Electrotehnics and Electronics), pp. 81-86,2003.
[4] Hamid A. Toliyat, Mohammed S. Arefeen, and Alexander G. Parlos, “A Method for dynamic simulation of air-gap eccentricity in induction machines”, IEEE Transactions on Industry Applications, Vol. 32, No. 4, pp.910-918, 1996.
[5] W. T. Thomson, D. Rankin, and D. G. Dorrell, “On-line current monitoring to diagnose air-gap eccentricity in large three-phase induction motors-industrial case histories verify the predictions”, IEEE Transactions on Energy Conversion, Vol. 14, No. 4, pp1372-1378, Dec 1999.
[6] Arkan M., Perovic D. K. and Unsworth P., “Online stator fault diagnosis in induction motors”, IEE Proceedings Electric Power Applications, Vol. 148, No. 6, November, pp. 537-547, 2001.
[7] R. M. Tallam, T. G. Habetler, and Ronald G. Harley, “Stator winding turn-fault detection for closed-loop induction motor drives”, IEEE Industry Applications Society Annual Meeting, pp1553-1557, 2002.
[8] Lorand S., Barna D., Agoston, “Rotor faults detection in squirrel cage induction motors by current signature analysis”, International Conference on Automation, Quality and Testing, Robotics, May 13 – 15, Cluj-Napoca, Romania, 2004.
[9] L. Eren, and M. J. Devaney, “Bearing damage detection via wavelet packet decomposition of the stator current,” IEEE Transactions on Instrumentation and Measurement, Vol. 53, No. 2, pp. 431 – 436, April 2004.
[10] J. Cusido; A.Jornet, L. Romeral, J.A. Ortega, A.Garcia, “Wavelet and PSD as a fault detection techniques”, IMTC 2006-Instrumentation and Measurement Technology Conference Sorrento, Italy 24-27 April 2006, pp. 1397-1400.
[11] Jordi Cusidó, Luis Romeral, Juan A. Ortega,Javier A. Rosero, and Antonio García Espinosa, “Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition”, IEEE Transactions on Industrial Applications, VOL. 55, NO. 2, February 2008.
[12] Erick Schmitt, Peter Idowu, Aldo Morales, “Applications Of Wavelets In Induction Machine Fault Detection”,Ingeniare Chilean journal of engineering,vol. 18 Nº 2, 2010, pp. 158-164.
[13] M. Riera-Guasp, J. Antonino-Daviu, J. Roger-Folch, and M. P. Molina, “The use of the wavelet approximation signal as a tool for the diagnosis and quantification of rotor bar failures,” IEEE Trans. Ind. Appl., vol. 44, no. 3, pp. 716–726, May./Jun. 2008.
[14] M. Riera-Guasp, Jose A. Antonino-Daviu, M. Pineda-Sanchez, R. Puche-Panadero, J. Perez-Cruz, “A general approach for the transient detection of slip-dependent fault components based on the discrete wavelet transform,” IEEE Trans. Ind. Electron. vol. 55, no. 12, pp. 4167-4180, Dec. 2008.
[15] Jesper S. Thomsen, and Carsten S. Kallese, ”Stator Fault Modelling of Induction Motors”, International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 1-4244-0194-1/06,2006.
[16] Williamson, S. and Mirzoian, K., “Analysis of cage induction motors with stator windings faults”, IEEE Transactions on Power Apparatus and Systems, Vol. Pas-104, Issue. 7, 1985.
[17] Tallam, Rangarajan M., Habetler, Thomas G., and Harley, RonaldG., “Transient model for induction machines with stator winding turn faults”, IEEE Transactions on Industry Applications, Vol. 38, No. 3, 2002.

Keywords
Condition monitoring, induction motors, wavelet, modeling of induction motor, turn to turn fault.