Rotor Fault Detection System for Inverter Driven Induction Motors using Currents Signals and an Encoder

  • Kim, Nam-Hun (School Electronics and Information Eng., Cheongju University)
  • 발행 : 2007.10.20

초록

In this paper, an induction motor rotor fault diagnosis system using current signals, which are measured using the axis-transformation method is presented. Inverter-fed motor drives, unlike line-driven motor drives, have stator currents which are rich in harmonics and therefore fault diagnosis using stator current is not trivial. The current signals for rotor fault diagnosis need precise and high resolution information, which means the diagnosis system demands additional hardware such as a low pass filter, high resolution ADC, an encoder and additional hardware. Therefore, the proposed axis-transformation method is expected to contribute to a low cost fault diagnosis system in inverter-fed motor drives without the need for any additional hardware. In order to confirm the validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation, using the Park transformation, is compared with the results obtained from the FFT(Fast Fourier Transform).

키워드

참고문헌

  1. G.B. Kliman, R.A. Koegl, J. Stein, R.D. Endicott, and M.W. Madden, 'Noninvasive detection of broken rotor bars in operating induction motors,' IEEE Trans. Energy Conv., vol. 3, pp. 873-879, Dec. 1988 https://doi.org/10.1109/60.9364
  2. R. Schoen, T. Habetler, F. Kamran, and R. Bartfield, 'Motor bearing damage detection using stator current monitoring,' IEEE Trans. Ind. Appl., vol. 31, no. 6, pp. 1274-1279, Nov./Dec. 1995 https://doi.org/10.1109/28.475697
  3. M.E.H. Benbouzid, 'A review of induction motors signature analysis as a medium for faults detection,' IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 984-993, Oct. 2000 https://doi.org/10.1109/41.873206
  4. S. Nandi, M. Bharadwaj, and H.A. Toliyat, 'Performance Analysis of a Three-Phase Induction Motor Under Mixed Eccentricity Condition,' IEEE Trans. Energy Conv., vol. 17, pp. 392-399, Sep. 2002 https://doi.org/10.1109/TEC.2002.801995
  5. J.F. Watson, N.C. Paterson, and D.G. Dorrell, 'The Use of Finite Element Methods to Improve Techniques for the Early Detection of Faults in 3-phase Induction Motors', IEEE Trans. on Energy Conversion, Vol. 14, No. 3, pp. 655-660, Sep. 1999 https://doi.org/10.1109/60.790931
  6. H.A. Toliyat, M.S. Arefeen, and A.G. Parlos, 'A Method for Dynamic Simulation and Detection of Air-Gap Eccentricity in Induction Machines', IEEE Trans. on Industry Applications, Vol. 32, No. 4, pp. 910-918, Jul./Aug. 1996 https://doi.org/10.1109/28.511649
  7. F. Filippetti, G. Franceschini, C. Tassoni, and P. Vas, 'Recent developments of induction motor drives fault diagnosis using AI techniques,' IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 994-1004, Oct. 2000 https://doi.org/10.1109/41.873207
  8. M. A. Awadallah and M. M. Morcos, 'Application of AI tools in fault diagnosis of electrical machines and drives-an overview,' IEEE Trans. Energy Convers., vol. 18, no. 2, pp. 245-251, Jun. 2003 https://doi.org/10.1109/TEC.2003.811739
  9. J.-S. R. Jang, 'ANFIS: adaptive-network-based fuzzy inference system,' IEEE Trans. Syst., Man, Cybern., vol. 23, no. 3, pp. 665-685, May/Jun. 1993 https://doi.org/10.1109/21.256541
  10. McDermid, W., 'Insulation systems and monitoring for stator winding of large rotating machines,' IEEE Electrical Insulation Magazine, vol. 9, no. 4, pp. 7-15, 1993
  11. Schemp, D.E., 'Predict motor failure with insulation testing,' Plant Engineering, vol. 50, pp. 97-96, 1996
  12. Stone, G.C., 'Partial discharge measurements to access rotation machine insulation condition : A survey,' Conference Record of the IEEE International Symposium on Electical Insulation, pp. 19-23, 1996
  13. J.R. Cameron, W. T. Thomson and A.B. Dow, 'Vibration and Current monitoring for detecting airgap eccentricity in large induction motors', Proceeding of IEE, vol. 133, Pt. B, No. 3, pp. 155-163, May 1986
  14. J. S. hsu, 'Monitoring of defects in induction motors through air-gap torque observation,' IEEE Transaction on Industrial Applications, Vol. 31, No. 5, pp. 1016-1021, Sept./Oct. 1995 https://doi.org/10.1109/28.464514