Low Cost Rotor Fault Detection System for Inverter Driven Induction Motor



Kim, Nam-Hun;Choi, Chang-Ho

  • 발행 : 2007.12.31


In this paper, the induction motor rotor fault diagnosis system using current signals, which are measured using axis-transformation method, and speed, which is estimated using current information, are presented. In inverter-fed motor drives unlike line-driven motor drives the stator currents have numerous harmonics components and therefore fault diagnosis using stator currents is very difficult. The current and speed signal for rotor fault diagnosis needs to be precise. Also, high resolution information, which means the diagnosis system, demands additional hardware such as low pass filter, high resolution ADC, encoder and etc. Therefore, the proposed axis-transformation and speed estimation method are expected to contribute to low cost fault diagnosis systems in inverter-fed motor drives without the need for an encoder and any additional hardware. In order to confirm validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation using Park transformation and speed estimation method are compared with the results obtained from fast Fourier transforms.


Currents signal;Fault diagnosis;Induction motor;Inverter driven system;Rotor fault


  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. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. Schemp, D.E., 'Predict motor failure with insulation testing,' Plant Engineering, vol. 50, pp. 97-96, 1996
  10. Stone, G.C., 'Partial discharge measurements to access rotation machine insulation condition: A survey,' Conference Record of the IEEE International Symposium on Electrical Insulation, pp. 19-23, 1996
  11. 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
  12. 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
  13. 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
  14. 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

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