Table of Contents Author Guidelines Submit a Manuscript
Shock and Vibration
Volume 2017, Article ID 6987250, 10 pages
https://doi.org/10.1155/2017/6987250
Research Article

An Adaptive Spectral Kurtosis Method Based on Optimal Filter

Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin Polytechnic University, Tianjin 300387, China

Correspondence should be addressed to Yanli Yang; moc.361@508070lyy

Received 1 June 2017; Revised 29 September 2017; Accepted 8 October 2017; Published 5 November 2017

Academic Editor: Carlo Rainieri

Copyright © 2017 Yanli Yang and Ting Yu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. Dyer and R. M. Stewart, “Detection of Rolling Element Bearing Damage by Statistical Vibration Analysis,” Journal of Mechanical Design, vol. 100, no. 2, p. 229, 1978. View at Publisher · View at Google Scholar
  2. R. F. Dwyer, “Detection of non-Gaussian signals by frequency domain kurtosis estimation,” in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '83), pp. 607–610, Boston, Mass, USA, 1984. View at Scopus
  3. J. Antoni, “The spectral kurtosis: a useful tool for characterising non-stationary signals,” Mechanical Systems and Signal Processing, vol. 20, no. 2, pp. 282–307, 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. J. Antoni and R. B. Randall, “The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines,” Mechanical Systems and Signal Processing, vol. 20, no. 2, pp. 308–331, 2006. View at Publisher · View at Google Scholar · View at Scopus
  5. F. Jia, Y. Lei, H. Shan, and J. Lin, “Early fault diagnosis of bearings using an improved spectral kurtosis by maximum correlated kurtosis deconvolution,” Sensors, vol. 15, no. 11, pp. 29363–29377, 2015. View at Publisher · View at Google Scholar · View at Scopus
  6. Y. Li, L. Wang, and J. Guan, “A Spectrum Detection Approach for Bearing Fault Signal Based on Spectral Kurtosis,” Shock and Vibration, vol. 2017, pp. 1–9, 2017. View at Publisher · View at Google Scholar
  7. J. Xiang, Y. Zhong, and H. Gao, “Rolling element bearing fault detection using PPCA and spectral kurtosis,” Measurement, vol. 75, pp. 180–191, 2015. View at Publisher · View at Google Scholar · View at Scopus
  8. T. Barszcz and A. JabŁoński, “A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram,” Mechanical Systems and Signal Processing, vol. 25, no. 1, pp. 431–451, 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. Y. Wang and M. Liang, “An adaptive SK technique and its application for fault detection of rolling element bearings,” Mechanical Systems and Signal Processing, vol. 25, no. 5, pp. 1750–1764, 2011. View at Publisher · View at Google Scholar · View at Scopus
  10. X. Zhang, J. Kang, L. Xiao, J. Zhao, and H. Teng, “A new improved Kurtogram and its application to bearing fault diagnosis,” Shock and Vibration, vol. 2015, Article ID 385412, 22 pages, 2015. View at Publisher · View at Google Scholar
  11. Y. Wang and M. Liang, “Identification of multiple transient faults based on the adaptive spectral kurtosis method,” Journal of Sound and Vibration, vol. 331, no. 2, pp. 470–486, 2012. View at Publisher · View at Google Scholar · View at Scopus
  12. H. Liu, W. Huang, S. Wang, and Z. Zhu, “Adaptive spectral kurtosis filtering based on Morlet wavelet and its application for signal transients detection,” Signal Processing, vol. 96, pp. 118–124, 2014. View at Publisher · View at Google Scholar · View at Scopus
  13. J. S. Luo, D. J. Yu, and M. Liang, “A kurtosis-guided adaptive demodulation technique for bearing fault detection based on tunable-Q wavelet transform,” Measurement Science and Technology, vol. 24, no. 5, Article ID 055009, 2013. View at Publisher · View at Google Scholar · View at Scopus
  14. W. A. Smith, Z. Fan, Z. Peng, H. Li, and R. B. Randall, “Optimised Spectral Kurtosis for bearing diagnostics under electromagnetic interference,” Mechanical Systems and Signal Processing, 2015. View at Publisher · View at Google Scholar · View at Scopus
  15. Y. Yanli and D. Jiahao, “Analysis on frequency resolution of EMD based on B-spline interpolation,” AEÜ - International Journal of Electronics and Communications, 2015. View at Publisher · View at Google Scholar · View at Scopus
  16. Y. Yang, “A Signal Theoretic Approach for Envelope Analysis of Real-Valued Signals,” IEEE Access, vol. 5, pp. 5623–5630, 2017. View at Publisher · View at Google Scholar
  17. X. Wang and K. Turitsyn, “Data-Driven Diagnostics of Mechanism and Source of Sustained Oscillations,” IEEE Transactions on Power Systems, vol. 31, no. 5, pp. 4036–4046, 2016. View at Publisher · View at Google Scholar · View at Scopus
  18. D. Ho and R. B. Randall, “Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals,” Mechanical Systems and Signal Processing, vol. 14, no. 5, pp. 763–788, 2000. View at Publisher · View at Google Scholar · View at Scopus