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access icon free Emulating single point bearing faults with the use of an active magnetic bearing

The propagation of evolving mechanical faults in rotating electric machinery and their corresponding signatures in the machines’ electrical signals is still not elucidated thoroughly. This deficiency implies serious obstructions in the development of using those signals as a complete and reliable condition monitoring technology. This study presents a new method to translate single point outer and inner race bearing faults into specific movements of the rotor with respect to the stator. The method contains the excitation of a simplified mass-spring-damper bearing model by analytical constructed fault-related force functions. Furthermore, a novel approach in order to emulate those obtained specific fault-related rotor movements with the use an experimental test setup is described, dimensioned, simulated and validated. Replacing the drive-end bearing of the induction machine under test by an active magnetic bearing creates the opportunity to continuously manipulate the rotor's position. The estimated single point bearing fault-related rotor movements serve as set-point for the magnetic bearing, resulting in the achievement of a single point bearing fault emulator with high relevance and reproducibility. This study includes experimental results of an emulated single point outer race bearing fault on an 11 kW induction machine.

References

    1. 1)
      • 21. Dorrell, D.G., Shek, J.K.H., Hsieh, M.F.: ‘The development of an indexing method for the comparison of unbalanced magnetic pull in electrical machines’, IEEE Trans. Ind. Appl., 2016, 52, (1), pp. 145153.
    2. 2)
      • 9. Stack, J.R., Habetler, T.G., Harley, R.G.: ‘Fault classification and fault signature production for rolling element bearings in electric machines’, IEEE Trans. Ind. Appl., 2004, 40, (3), pp. 735739.
    3. 3)
      • 19. Schweitzer, G., Maslen, E.H.: ‘Magnetic bearings’ (Springer Science and Business Media, 2009).
    4. 4)
      • 1. Schoen, R.R., Habetler, T.G., Kamran, F., et al: ‘Motor bearing damage detection using stator current monitoring’, IEEE Trans. Ind. Appl., 1995, 31, (6), pp. 12741279.
    5. 5)
      • 14. Corne, B., Knockaert, J., Desmet, J.: ‘Emulating bearing faults – a novel approach’. Int. Conf. on Electrical Machines (ICEM), 2016, p. 7.
    6. 6)
      • 23. Chaowu Jin, J. Z., Xu, Y., Cheng, C.: ‘Active magnetic bearings stiffness and damping identification from frequency characteristics of control system’, 2016.
    7. 7)
      • 8. Corne, B., Debruyne, C., Baets, P.D., et al: ‘Stator current measurements as a condition monitoring technology – the-state-of-the-art’. 2014 Int. Conf. on Electrical Machines (ICEM), September 2014, pp. 16591665.
    8. 8)
      • 17. Radman, K., Bulic, N., Gruber, W.: ‘Geometry optimization of a bearingless flux-switching slice motor’. 2015 IEEE Int. Electric Machines Drives Conf., May 2015, pp. 16951701.
    9. 9)
      • 13. Brandt, A.: ‘Noise and vibration analysis: signal analysis and experimental procedures’ (John Wiley and Sons, Ltd, 2011).
    10. 10)
      • 12. Immovilli, F., Bianchini, C., Cocconcelli, M., et al: ‘Bearing fault model for induction motor with externally induced vibration’, IEEE Trans. Ind. Electron., 2013, 60, (8), pp. 34083418.
    11. 11)
      • 10. Shah, D.S., Patel, V.N.: ‘A review of dynamic modeling and fault identifications methods for rolling element bearing’, Procedia Technol., 2014, 14, pp. 447456. 2nd Int. Conf. on Innovations in Automation and Mechatronics Engineering, 2014.
    12. 12)
      • 3. Prieto, M.D., Cirrincione, G., Espinosa, A.G., et al: ‘Bearing fault detection by a novel condition-monitoring scheme based on statistical-time features and neural networks’, IEEE Trans. Ind. Electron., 2013, 60, (8), pp. 33983407.
    13. 13)
      • 11. Corne, B., Vervisch, B., Debruyne, C., et al: ‘Comparing mcsa with vibration analysis in order to detect bearing faults – a case study’. 2015 IEEE Int. Electric Machines Drives Conf., May 2015, pp. 13661372.
    14. 14)
      • 16. Hillyard, J.: ‘Magnetic bearings, joint advanced student school’ (Technical University of Munich, 2006), no. April.
    15. 15)
      • 4. Saadaoui, W., Jelassi, K.: ‘Induction motor bearing damage detection using stator current analysis’. Int. Conf. on Power Engineering, Energy and Electrical Drives, 2011, May 2011, pp. 16.
    16. 16)
      • 20. Tenhunen, A., Benedetti, T., Holopainen, T.P., et al: ‘Electromagnetic forces in cage induction motors with rotor eccentricity’. IEEE Int. Electric Machines and Drives Conf., 2003, IEMDC'03, vol. 3, June 2003, pp. 16161622.
    17. 17)
      • 6. Devaney, M.J., Eren, L.: ‘Detecting motor bearing faults’, IEEE Instrum. Meas. Mag., 2004, 7, (4), pp. 3050.
    18. 18)
      • 5. Zhou, W., Lu, B., Habetler, T.G., et al: ‘Incipient bearing fault detection via motor stator current noise cancellation using wiener filter’, IEEE Trans. Ind. Appl., 2009, 45, (4), pp. 13091317.
    19. 19)
      • 7. Frosini, L., Bassi, E.: ‘Stator current and motor efficiency as indicators for different types of bearing faults in induction motors’, IEEE Trans. Ind. Electron., 2010, 57, (1), pp. 244251.
    20. 20)
      • 2. Eren, L., Devaney, M.J.: ‘Bearing damage detection via wavelet packet decomposition of the stator current’, IEEE Trans. Instrum. Meas., 2004, 53, (2), pp. 431436.
    21. 21)
      • 22. Chiba, A., Fukao, T., Ichikawa, O., et al: ‘Magnetic bearings and bearingless drive’ (Newnes, 2005).
    22. 22)
      • 15. Ahrens, M., Kucera, L.: ‘Analytical calculation of fields, forces and losses of a radial magnetic bearing with a rotating rotor considering eddy currents’. 5th Int. Symp. on Magnetic Bearings, 1996.
    23. 23)
      • 18. Anantachaisilp, P., Lin, Z.: ‘An experimental study on pid tuning methods for active magnetic bearing systems’, Int. J. Adv. Mechatronic Syst., 2013, 5, (2), pp. 146154.
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