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Early detection of pitting failure in gears using a spectralkurtosis analysis

Published online by Cambridge University Press:  25 October 2012

Chemseddine Rahmoune  and
Djamel Benazzouz
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Abstract

Conventional methods (i.e. time, frequency and cepstrum) can routinely be used to revealfault-indicating information in the vibration signal. In recent years, wavelet analysis,which can lead to a clear identification of the nature of faults, is widely used todescribe rotating machine condition. The capability of this method in the detection of anyabnormality can be further improved when its low-order frequency moments are considered.This paper presents the use of the fast kurtogram in the early detection and conditionmonitoring of pitting fault. For this purpose, a dynamic model of a simple stage gearbox(with and without defects) is used. Then, the pinion’s vibration displacement is analyzedby using a fast kurtogram method. This method is suitable for such diagnosis and givesvaluable information about the presence and effects of the pitting tooth defect.

Keywords

Pitting failuregearsspectral kurtosisfaults detection
Type
Research Article
Information
Mechanics & Industry , Volume 13 , Issue 4 , 2012 , pp. 245 - 254
Copyright
© AFM, EDP Sciences 2012

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References

White, M.F., Simulation and analysis of machinery fault signals, J. Sound Vib. 93 (1984) 95–116 CrossRefGoogle Scholar
Randall, R.B., A new method of modelling gear faults, Trans. ASME J. Mech. Des. 104 (1981) 259–267 CrossRefGoogle Scholar
McFadden, P.D., Examination of a technique for the early detection of failure in gears by signal processing of the time domain average of the meshing vibration, Mech. Syst. Signal Process. 1 (1987) 173–183 CrossRefGoogle Scholar
Wang, W., Early detection of gear tooth cracking using the resonance demodulation technique, Mech. Syst. Signal Process. 15 (2001) 887–903 CrossRefGoogle Scholar
McFadden, P.D., Detecting fatigue cracks in gears by amplitude and phase demodulation of the meshing vibration, Trans. ASME J. Vib. Acoust. Stress. Reliab. Des. 108 (1986) 165–170 CrossRefGoogle Scholar
Li, Hui, Zhang, Yuping, Zheng, Haiqi, Gear fault detection and diagnosis under speed-up condition based on order cepstrum and radial basis function neural network, J. Mech. Sci. Technol. 23 (2009) 2780–2789 CrossRefGoogle Scholar
Chaari, F., Fakhfakh, T., Haddar, M., Simulation numérique du comportement dynamique d’une transmission par engrenages en présence de défauts de dentures, Mécanique & Industries 6 (2006) 625–633 CrossRefGoogle Scholar
Qin, S.R., Zhong, Y.M., Research on the unified mathematical model for FT, STFT and WT and its application, Mech. Syst. Signal Process. 18 (2004) 1335–1347 CrossRefGoogle Scholar
Zhan, Y.M., Jardine, A.K.S., Adaptive autoregressive modeling of non-stationary vibration signals under distinct gear states. Part 2 : experimental analysis, J. Sound Vib. 3 (2005) 451–476 CrossRefGoogle Scholar
Stander, C.J., Heyns, P.S., Schoombie, W., Using vibration monitoring for local fault detection on gears operating under fluctuating load conditions, Mech. Syst. Signal Process. 16 (2002) 1005–1024 CrossRefGoogle Scholar
Meltzer, G., Ivanov, Y.Y., Fault detection in gear drives with nonstationary rotational speed – Part I : the time–frequency approach, Mech. Syst. Signal Process. 17 (2003) 1033–1047 CrossRefGoogle Scholar
Baydar, N., Ball, A., Detection of gear deterioration under varying load conditions by using the instantaneous power spectrum, Mech. Syst. Signal Process. 14 (2000) 907–921 CrossRefGoogle Scholar
Yesilyurt, I., Fault detection and location in gears by the smoothed instantaneous power spectrum distribution, NDT&E Int. 36 (2003) 535–542 CrossRefGoogle Scholar
Kar, C., Mohanty, A.R., Monitoring gear vibrations through motor current signature analysis and wavelet transform, Mech. Syst. Signal Process. 20 (2006) 158–187 CrossRefGoogle Scholar
Loutridis, S., A local energy density methodology for monitoring the evolution of gear faults, NDT&E Int. 37 (2004) 447–453 CrossRefGoogle Scholar
Ohue, Y., Yoshida, A., Seki, M., Application of the wavelet transform to health monitoring and evaluation of dynamic characteristics, Proc. Inst. Mech. Eng. 218 (2004) 1–12 CrossRefGoogle Scholar
Peng, Z.K., Chu, F.L., Application of the wavelet transform in machine condition monitoring and fault diagnostics : a review with bibliography, Mech. Syst. Signal Process. 18 (2004) 199–221 CrossRefGoogle Scholar
Yesilyurt, I., The application of conditional moments analysis to gearbox fault detection–A comparative study using the spectrogram and scalogram, NDT&E Int. 37 (2004) 309–320 CrossRefGoogle Scholar
Ozturk, H., Sabuncu, M., Yesilyurt, I., Early detection of pitting damage in gears using mean frequency of scalogram, J. Vib. Control 14 (2008) 469–484 CrossRefGoogle Scholar
Hlawatsch, F., Boudreaux-Bartels, G.F., Linear and quadratic time–frequency signal representations, IEEE Signal Process. Mag. 9 (1992) 21–67 CrossRefGoogle Scholar
Antoni, J., Randall, R.B., The spectral kurtosis : application to the vibratory surveillance and diagnostics of rotating machines, Mech. Syst. Signal Proc. 20 (2006) 308–331 CrossRefGoogle Scholar
D.F. Dwyer, Detection of non-Gaussian signals by frequency domain kurtosis estimation, in : Proceedings of the International Conference on Acoustic, Speech, and Signal Processing, Boston 1984, pp. 607–610
Antoni, J., The spectral kurtosis : a useful tool for characterizing non-stationary signals, Mech. Sys. Signal Proc. 20 (2006) 282–307 CrossRefGoogle Scholar
Antoni, J., Fast computation of the kurtogram for the detection of transient faults, Mech. Sys. Signal Proc. 21 (2007) 108–124 CrossRefGoogle Scholar
M. Merzoug, A. Miloudi, K. Brahimi, Comportement dynamique d’une transmission par engrenages – Analyse de la stabilité. XVe Congrès Français de Mécanique, Nancy, France, 2001, pp. 3–7
Choy, F.K., Polyshchuk, V., Zakrajsek, J.J., Handschuh, R.F., Townsend, D.P., Analysis of the effects of surface pitting and wear on the vibrations of a gear transmission system, Tribol. Int. 29 (1996) 77–83 CrossRefGoogle Scholar
J. Antoni, web page; http://www.utc.fr/_antoni/S