Open Access
MATEC Web of Conferences
Volume 20, 2015
AVE2014 - 4ième Colloque Analyse Vibratoire Expérimentale / Experimental Vibration Analysis
Article Number 07001
Number of page(s) 7
Section Vibration-based condition monitoring
Published online 27 January 2015
  1. Wang WJ and McFadden PD. Early detection of gear failure by vibration analysis –I. Calculation of the time-frequency distribution. MSSP, 7(3): 193–203 (1993)
  2. Wang WJ and McFadden PD. Early detection of gear failure by vibration analysis –II. Interpretation of the time–frequency distribution using image processing techniques. MSSP; 7(3): 205–15 (1993)
  3. Safizadeh M.S., Lakis A.A. and Thomas M., Gear Fault Diagnosis using time-frequency methods, proceedings of 20th seminar on machinery vibration, Canadian Machinery Vibration Association, Quebec, 7.19-7.29 (2002)
  4. Safizadeh M.S., Lakis A.A. and Thomas M., Using Short-Time Fourier Transform in Machinery diagnosis, Proceedings of WSEAS (Brazil) 494–200, (2005)
  5. Z.K. Peng, F.L. Chu, Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography, Mechanical Systems and Signal Processing 18, 199–221 (2004)
  6. R. Yan, R. X. Gao and X. Chen, Wavelets for fault diagnosis of rotary machines: A review with applications, Signal Processing 961–15 (2014)
  7. Baydar N and Ball A.> Detection of gear deterioration under varying load conditions by using the instantaneous power spectrum. Mechanical Systems and Signal Processing; 14(6): 907–21 (2000)
  8. Baydar N, Chen Q, Ball A, Kruger U. Detection of incipient tooth defect in helical gears using multivariate statistics. MSSP 15(2): 303–21 (2001)
  9. Baydar N., Ball A. A comparative study of acoustic and vibration signals in detection of gear failures using Wigner–Ville distribution. Mechanical Systems and Signal Processing 15(6): 1091–1107 (2001)
  10. Baydar N. and Ball A. Detection of gear failures via vibration and acoustic signal using wavelet transform. Mechanical Systems and Signal Processing, 17(4): 787–804 (2003) [CrossRef]
  11. Yesilyurt I., The application of the conditional moments analysis to gearbox fault detection—a comparative study using the spectrogram and scalogram, NDT&E International 37, 309–320 (2004)
  12. Yan, R., and Gao, R. X., “Approximate Entropy as a Diagnostic Tool for Machine Health Monitoring,” Mechanical Systems and Signal Processing 21, 824–839 (2007) [CrossRef]
  13. He Y. and X. Zhang. Approximate Entropy Analysis of the Acoustic Emission From Defects in Rolling Element Bearings, Journal of Vibration and Acoustics, 134 / 061012-1 (2012)
  14. Fu, L., He, Z. Y., Mai, R. K., and Qian, Q. Q., Application of Approximate Entropy to Fault Signal Analysis in Electric Power System, Proceedings of the Chinese Society of Electric Engineering, 28(28), 68–73 (2008)
  15. Xu, Y. G., Li, L. J., and He, Z. J. Approximate Entropy and its Applications in Mechanical Fault Diagnosis, Chin. J. Inf. Control, 31(6), 547–551 (2002)
  16. R. Yan and R. X. Gao, Complexity as a Measure for Machine Health Evaluation, IEEE transactions on instrumentation and measurement, 53(4), 1327–1334 (2004) [CrossRef]
  17. Wang J., L. Cui, H. Wang and P. Chen, Improved Complexity Based on Time-Frequency Analysis in Bearing Quantitative Diagnosis, Advances in Mechanical Engineering, Article ID 258506, 11 pages (2013)
  18. Kedadouche M., Kidar T., Thomas M. and Tahan A., Combining EMD and Lempel-Ziv Complexity for early detection of gear cracks, Surveillance 7, Chartres, France, pp 100–110, 28-29 (2013)
  19. Lempel A. and Ziv J., On the complexity of finite sequences, IEEE Trans. Inform. Theory,Jan. IT22, 75–81 (1976) [CrossRef]
  20. El Badaoui, M.: Contribution of vibratory diagnostic of gearbox by Cepstral analysis, Ph.D. thesis, Jean Monnet University of St Etienne (FR), p. 141 (1999) (in French)
  21. Pareya A., El Badaoui M., Guillet F., Tandon N. Dynamic modelling of spur gear pair and application of empirical mode decomposition-based statistical analysis for early detection of localized tooth defect, Journal of Sound and Vibration 294, 547–561 (2006) [CrossRef]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.