FLUX-BASED FAULT DETECTION IN ROTORS OF INDUCTION MOTORS, USING FINITE ELEMENTS AND NEURAL NETWORK

Milad N. Azari, Hossein A. Khazaeli, and Mehdi Samami

References

  1. [1] K.M. Siddiqui, K. Sahay, and V.K. Giri, Health monitoring and fault diagnosis in induction motor, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(1), 2014. (An ISO 3297: 2007 Certified Organization), 6549–6565.
  2. [2] W. Zaabi, Y. Bensalem, and H. Trabelsi, Fault analysis of induction machine using finite element method (FEM), 15th International Con. on Sciences and Techniques of Automatic Control STA’2014-PID3446-DFC& Computer Engineering, Hammamet, Tunisia, December 2014, 21–23.
  3. [3] X. Ying, Performance evaluation and thermal fields analysis of induction motor with broken bars located at different relative positions, IEEE Transaction on Magnetic, 46(5), 2010, 1243–1250.
  4. [4] M.N. Uddin and M.M. Rahman, Online current and vibration signal monitoring based fault detection of bowed rotor induction motor, IEEE Energy Conversion Congress and Exposition (ECCE), Montreal, QC, September 2015, 2988–2994.
  5. [5] W.D. Li and C.K. Mechefske, Detection of induction motor faults: A comparison of stator current vibration and acoustic methods, Journal of Vibration and Control, 12(2), 2006, 165–188.
  6. [6] A. Sadoughi, M. Ebrahimi, M. Moalem, and S. Sadri, Intelligent diagnosis of broken bars in induction motors based on new features in vibration spectrum, Proc. IEEE SDEMPED, 2007, 106–111.
  7. [7] S. Shin, J. Kim, S.B. Lee, C. Lim, and E.J. Wiedenbrug, Evaluation of the influence of rotor magnetic anisotropy on condition monitoring od two-pole induction motors, IEEE Transactions on Industry Applications, 51(4), 2015, 2896–2904.
  8. [8] G. Mirzaeva and K.I. Saad, Advanced diagnosis of rotor faults and eccentricity in induction motors based on internal flux measurement, IEEE Transactions on Industry Applications, 54(3), 2018, 2981–2991.
  9. [9] A.M. da Silva, R.J. Povinelli, and N.A.O. Demerdash, Induction machine broken bar and stator short-circuit fault diagnostics based on three-phase stator current envelopes, IEEE Transactions on Industrial Electronics, 55(3), 2008, 1310–1318.
  10. [10] J. Pons-Llinares, J.A. Antonino-Daviu, M. Riera-Guasp, M. Pineda Sanchez, and V. Climente-Alarcon, Induction motor diagnosis based on a transient current analytic wavelet transform via frequency b-splines, IEEE Transactions on Industrial Electronics, 58(5), 2011, 1530–1544.
  11. [11] A. Soualhi, G. Clerc, and H. Razik, Detection and diagnosis of faults in induction motor using an improved artificial ant clustering technique, IEEE Transactions on Industrial Electronics, 60(9), 2013, 4053–4062.
  12. [12] W. Thomson and R.J. Gilmore, Motor current signature analysis to detect faults in induction motor drives – fundamentals, data interpretation, and industrial case histories (Nigg, Aberdeen, Scotland: Discipline Technical Authority (Electrical Engineering) AMEC upstream Oil & Gas), 2003.
  13. [13] A.M. da Silva, Induction motor fault diagnostic and monitoring methods, Master of Electrical and Computer Engineering Milwaukee, Wisconsin, May 2006.
  14. [14] A.E. Fitzgerald, Electrical machinery, 6th ed. (New York, USA: Mc-Graw Hill Higher Education), 2005.
  15. [15] M.N. Azari and M. Mirsalim, Performance analysis of line start permanent magnet motor with slots on solid rotor using finite element method, Electric Power Components and Systems, 41, 2013, 1159–1172.
  16. [16] P. Pao-la-or, S. Peaiyoung, T. Kulworawanichpong, and S. Sujitjorn, Magnetic field simulation of an induction motor using nonlinear time-stepping finite element method, School of Electrical Engineering, Suranaree University of Technology, Thailand.
  17. [17] E. Vassent, G. Meunier, and A. Foggia, Simulation of induction machines-using complex magnetodynamic finite element method coupled with the circuit equations, IEEE Transactions on Magnetics, 27(5), 1991, 4246–4249.
  18. [18] X. Ying, Investigation of broken rotor bar faults in three-phase squirrel-cage induction motors (INTECH: Finite Element Analysis-From Biomedical Applications to Industrial Developments, 2012), 477–496.
  19. [19] M. Pineda-Sanchez, M. Riera-Guasp, J.A. Antonino-Daviu, J. Roger-Folch, J. Perez-Cruz, and R. Puche-Panadero, Diagnosis of induction motor faults in the fractional Fouries domain, IEEE Transactions on Instrumentation and Measurement, 59(8), 2010, 2065–2075.
  20. [20] R. Supangat, N. Ertugrul, W.L. Soong, D.A. Gray, and C. Hansen, Broken rotor bar fault detection in induction motors using starting current analysis (Australia: University of Adelaide School of Electrical and Electronic Engineering Adelaide), 2005.
  21. [21] H. Yaghobi, H.R. Mashhadi, K. Ansari, Application of radial basis neural networks in fault diagnosis of synchronous generator, Journal of Iranian Association of Electrical and Electronics Engineering, 10(2), 2013, 23–36.
  22. [22] S.V. Shojaedini, M. Mokhtari Koohi, and R. Kasbgar, A new wavelet based spatio-temporal method for magnification of subtle motions in video, IJE Transactions C: Aspects, 29(3), 2016, 313–320.
  23. [23] L. Feng and L. Lin, Comparative analysis of image denoising methods based on wavelet transform and threshold functions, IJE Transactions B: Applications, 30(2), 2017, 199–206.
  24. [24] S.M. Hosseini, Introducing a new hybrid method with second generation wavelet transform and Sandia frequency shift for islanding detection of inverter-based distributed, Journal of Iranian Association of Electrical and Electronics Engineers, 3(1), 2016, 21–34.
  25. [25] S.M. Shashidhara and P. Sangameswara Raju, Trade off analysis of wavelet transform techniques for the detection of broken rotor bars in induction motors, Advance in Electronic and Electric Engineering, 3(8), 2013, 1019–1030.

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