Open Access
Mechanics & Industry
Volume 15, Number 6, 2014
Page(s) 467 - 476
Published online 16 September 2014
  1. A.K.S. Jardine, D. Lin, D. Banjevic, A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mech. Syst. Signal Process 20 (2006) 1483–1510 [Google Scholar]
  2. S. Sassi, B. Badri, M. Thomas, Tracking surface degradation of ball bearings by means of new time domain scalar descriptors, Int. J. COMADEM 11 (2008) ISSN1363-7681 36–45 [Google Scholar]
  3. N. Tandon, A. Choudhury, A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings, Tribol. Int. 32 (1999) 469–480 [Google Scholar]
  4. A. Choudhury, N. Tandon, Application of acoustic emission technique for the detection of defects in rolling element bearings, Tribol. Int. 33 (2000) 39–45 [CrossRef] [Google Scholar]
  5. X.Z. Yongyong He, I. Michael, Friswell, Defect diagnosis for rolling element bearings using acoustic emission, J. Vib. Acoust. 131 (2009) (ASME) [Google Scholar]
  6. A. Dadouche, et al., Sensitivity of Air-Coupled Ultrasound and Eddy Current Sensors to Bearing Fault Detection, Tribol. Trans. 51 (2008) 310–323 [CrossRef] [Google Scholar]
  7. J. Shiroishi et al., Bearing condition diagnosis via vibration and acoustic emission measurements, Mech. Syst. Signal Process. 11 (1997) 693–705 [CrossRef] [Google Scholar]
  8. Y.-H. Kim et al., Condition Monitoring of Low Speed Bearings: A Comparative Study of the Ultrasound Technique Versus Vibration Measurements, in Engineering Asset Management, Springer London, 2006, pp. 182–191 [Google Scholar]
  9. M. Kedadouche, M. Thomas, A. Tahan, Monitoring bearings by acoustic emission: a comparative study with vibration techniques for early detection, Proceedings of the 30th Seminar on machinery vibration, Canadian Machinery Vibration Association, Niagara Falls (ON, Canada), 2012, 17 p. [Google Scholar]
  10. X. Chiementin, D. Mba, B. Charnley, S. Lignon, J.-P. Dron, Effect of the denoising on acoustic emission signals, J. Vib. Acoust. 132 (2010) [Google Scholar]
  11. C. Liao, X. Li, D. Liu, Application of reassigned wavelet scalogram in feature extraction based on acoustic emission signal, J. Mech. Eng. 45 (2009) 273–279 [CrossRef] [Google Scholar]
  12. M. Zvokelj, S. Zupan, I. Prebil, Multivariate and multiscale monitoring of large-size low-speed bearings using ensemble empirical mode decomposition method combined with principal component analysis, Mech. Syst. Signal Process. (24) (2010) 1049–1067 [Google Scholar]
  13. B. Kilundu, et al., Cyclostationarity of Acoustic Emissions (AE) for monitoring bearing defects, Mech. Syst. Signal Process. 25 (2011) 2061–2072 [Google Scholar]
  14. J. Antoni, Cyclostationarity by examples, Mech. Syst. Signal Process. 23 (2009) 987–1036 [CrossRef] [Google Scholar]
  15. J. Antoni, F. Bonnardot, A. Raad, M. El Badaoui, Cyclostationary modelling of rotating machine vibration signals, Mech. Syst. Signal Process. (2004) 1285–1314 [Google Scholar]
  16. F. Bonnardot, R.B. Randall, F. Guillet, Extraction of 2nd order cyclostationary sources–application to vibration analysis, Mech. Syst. System Process. 19 (2005) 1230–1244 [CrossRef] [Google Scholar]
  17. R. Boustany, J. Antoni, A subspace method for the blind extraction of a cyclostationary source: application to rolling element bearing diagnostics, Mech. Syst. Syst. Process. 19 (2005) 1245–1259 [Google Scholar]
  18. R. Boustany, J. Antoni, Blind extraction of a cyclostationary signal using reduced-rank cyclic regression-A unifying approach, Mech. Syst. Syst. Process. (2008) 520–541 [Google Scholar]
  19. M. Thomas, J. Masounave, T.M. Dao, C.T. Le Dinh, F. Lafleur, Rolling element bearing degradation and vibration signature relationship, 2e Conférence Internationale sur les méthodes de surveillance et techniques de diagnostics acoustiques et vibratoires, SFM, Senlis, 1995, Vol. 1, pp. 267–277 [Google Scholar]
  20. J.I. Taylor, Identification of bearing defects by spectral analysis, J. Mech. Design 102 (1980) [Google Scholar]
  21. J. Antoni, Cyclic spectral analysis in practice, Mech. Syst. Signal Process. 21 (2007) 597–630 [CrossRef] [Google Scholar]
  22. J. Antoni, Cyclic spectral analysis of rolling element bearing signals: facts and fictions, J. Sound Vib. 304 (2007) 497–529 [CrossRef] [Google Scholar]

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