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Development of a Solid-Borne Sound Sensor to Detect Bearing Faults Based on a MEMS Sensor and a PVDF Foil Sensor

  • Jurij KernEmail author
  • Carsten Thun
  • Jernej Herman
Conference paper
Part of the Lecture Notes in Mobility book series (LNMOB)

Abstract

Vibration analysis is an effective method to determine the health of a rotating mechanical machine. A test is set-up with two different sensors, MEMS and PVDF-Foil based. Experimental data is presented and a test to detect undamaged and damaged bearings has been performed. The MEMS sensor shows a good performance with clear indication of failure frequencies. The PVDF Foil in this configuration also shows the ability to detect the difference, but the natural properties leading to mechanical amplification of bearing vibrations are limiting the performances for weak mechanical failures. Monitoring algorithms are employed under standard conditions: RMS value of the signal, Kurtosis, Power spectrum density and Envelope analysis.

Keywords

Condition monitoring Bearing faults PVDF foil MEMS Kurtosis Envelope detection Hub bearing Sensor Vibration detection Power spectrum density 

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References

  1. 1.
    Lacey, S.J.: An overview of Bearing Vibration Analysis, Schaeffler UK (2007)Google Scholar
  2. 2.
    FP7 COSIVU web page, GC.ICT.2012.6-8: -PPP GC 2012, www.cosivu.eu
  3. 3.
    Zhang, H., Tolbert, L.M., Member, S., Ozpineci, B.: Impact of SiC Devices on Hybrid Electric and Plug-In Hybrid Electric Vehicles 47(2), 912–921 (2011)Google Scholar
  4. 4.
    KESS project web page, BMBF-No.: 16N11 780 (2012), www.kess.uni-bremen.de
  5. 5.
    Luber, W., Becker, J.: Application of PVDF foils for the measurements of unsteady pressures on wind tunnel models for the prediction of aircraft vibrations. In: Structural Dynamics - Proceedings of the 28th IMAC 2011. Conference Proceedings of the Society for Experimental Mechanics Series, pp. 1157–1176 (2011)Google Scholar
  6. 6.
    Cremer, L., Heckl, M.: Structure-Borne Sound: Structural Vibrations and Sound Radiation at Audio Frequencies (2005)Google Scholar
  7. 7.
    Randall, R.B.: Vibration Based Condition Monitoring: Industrial, Aerospace and Automotive ApplicationsGoogle Scholar
  8. 8.
    Randall, R.B., Antoni, J.: Rolling element bearing diagnostics—A tutorial. Mech. Syst. Signal Process. 25(2), 485–520 (2011)CrossRefGoogle Scholar
  9. 9.
    Natu, M.: Bearing fault analysis using frequency and wavelet techniques. IJCEM Int. J. Comput. Eng. Manag. 15(6) (2012)Google Scholar
  10. 10.
    Sawalhi, N., Randall, R.B.: Localized fault detection and diagnosis in rolling element bearings: A collection of the state of art processing algorithms. no. Hums (2013)Google Scholar
  11. 11.
    Konstantin-Hansen, H.: Envelope analysis for Diagnostics of Local Faults in Rolling Element Bearings, DenmarkGoogle Scholar
  12. 12.
    Andrejašič, M., Poberaj, I.: MEMS ACCELEROMETERS, Ljubljana (2008)Google Scholar
  13. 13.
    Abouel-seoud, S., Ahmed, I., Khalil, M.: An Experimental Study on the Diagnostic Capability of Vibration Analysis for Wind Turbine Planetary Gearbox. Int. J. Mod. Eng. Res. 2(3) (2012)Google Scholar
  14. 14.
    Dube, A.V., Dhamande, L.S., Kulkarni, P.G.: Vibration Based Condition Assessment Of Rollingelement Bearings With Localized Defects. Int. J. Sci. Technol. Res. 2(4), 149–155 (2013)Google Scholar
  15. 15.
    de Lorenzo, F., Calabro, M.: Kurtosis: A Statistical Approach to Identify Defect in Roller Bearings. In: 2nd International Conference on Marine Research and Transportation, pp. 17–24 (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Elaphe Propulsion Technologies Ltd.KranjSlovenia
  2. 2.Hella Fahrzeugkomponenten GmbHBremenDeutschland
  3. 3.Elaphe Propulsion Technologies Ltd.CeljeSlovenia

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