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Application of morphological analysis for gear fault detection and trending

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Frequency domain based signal processing methods such as cepstrum analysis, Hilbert Transform based demodulation, cyclostationary analysis, etc have been shown to present a quite effective behaviour in the detection of defects, when applied to the analysis of vibration signals, resulting from gear pairs with one or more defective gears. However, these methods typically require some complex and sophisticated analysis, which renders their application cumbersome for applications requiring unskilled personnel or automated fault detection and trending. Alternatively to these methods, morphological analysis for processing vibration signals has been proposed, addressing the issues of how to quantify the shape and the size of the signals directly in the time domain. Morphological analysis and the resulting morphological index is applied in this paper to a set of twelve successive vibration measurements resulting from a gearbox prior to tooth breakage. As shown, the morphological index is able monitor the evolution of the potential fault, providing a clear warning prior to the breakage of the tooth.
Czasopismo
Rocznik
Tom
Strony
37--42
Opis fizyczny
Bibliogr. 16 poz., rys.
Twórcy
autor
  • National Technical University of Athens, School of Mechanical Engineering, Machine Design and Control Systems Section Athens 15773, Greece, antogian@central.ntua.gr
Bibliografia
  • 1. McFadden P. D.: Detecting fatigue cracks in gears by amplitude and phase modulations of the meshing vibration, ASME Transactions, Journal of Vibration, Acoustics, Stress and Reliability in design, 1986,n 108, 165-170.
  • 2. Randall R. B.: 1987, Frequency Analysis, Bruel & Kjaer, 3rd Ed.
  • 3. Wang W.: Early detection of gear tooth cracking using the resonance demodulation technique, Mechanical Systems and Signal Processing, 2001, 15(5), 887-903.
  • 4. Capdessus C., Sidahmed M., Lacoume J. L.: Mechanical Systems and signal processing, 2000, 14, 371-385, “Cyclostationary processes:Application in gear faults early diagnosis”.
  • 5. Endo H., Randall R. B.: Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter, Mechanical Systems and Signal Processing, 2007, 21, 906-919.
  • 6. Jafarizadeh M. A., Hassannejad R., Ettefagh M. M, Chitsaz S.: Asynchronous input gear damage diagnosis using time averaging and wavelet filtering, Mechanical Systems and Signal Processing, 2008, 22, 172-201.
  • 7. Halim E. B., Choudhury S. M. A. A., Shah S. L., Zuo M. J.: Time domain averaging across all scales: A novel method for detection of gearbox faults, Mechanical Systems and Signal Processing, 2008, 22, 261-278.
  • 8. Maragos P., Schafer R.: Morphological filters - Part I: their set-theoretic analysis and relations to linear shift invariant filters. IEEE Transactions on Acoustics, Speech and Signal Processing ASSP, 35, 1987, 1153-1169.
  • 9. Maragos P.: The Digital Signal Processing Handbook on Morphological Signal and Image Processing. Boca Raton: CRC Press, 1998. p.74.1- 74.26., FL, USA.
  • 10. Meyer F., Maragos P.: Non-linear scale space representations with morphological leveling. Journal of Visual Communication and Image Representation. 2000, 11, 245-265.
  • 11. Nishida S., Nakamura M., Miyazaki M., Suwazono S., Honda M., Nagamine T., Shibasaki H.: Construction of a morphological filter for detecting an event related potential P300 in single sweep EEG record in children. Medical Engineering Physics, 1995, 17, 425-430.
  • 12. Nishida S., Nakamura M., Shindo K., Kanda M., Shibasaki H.: A morphological filter for extracting waveform characteristics of single sweep evoked potentials. Automatica, 1997, 35, 937-943.
  • 13. Nishida S., Nakamura M., Ikeda A., Shibasaki H.: Signal separation of background EEG and spike by using morphological filter. Medical Engineering Physics, 1999, 21, 601-608.
  • 14. Sedaaghi M. H.: ECG wave detection using morphological filters. Applied Signal Proccesing. 1998, 5, 182-194.
  • 15. Nikolaou N. G., Antoniadis I. A.: Application of morphological operators as envelope extractors for impulsive-type periodic signals. Mechanical Systems and Signal Processing, 2003, 17(6), 1147-1162.
  • 16. Patargias T. I., Yiakopoulos C. T., Antoniadis I. A.: Performance assessment of a morphological index in fault prediction and trending of defective rolling element bearings, Nondestructive Testing and Evaluation, 2006, Vol. 22, No 1, pp 39-60.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAR0-0039-0008
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