Mechanics & Industry
Volume 18, Number 8, 2017
Experimental Vibration Analysis
Article Number 805
Number of page(s) 14
Published online 21 March 2018
  1. R. Yan, R. Zhao, R.X. Gao, Noise-assisted data processing in measurement science: part one part 40 in a series of tutorials on instrumentation and measurement, IEEE Instrum. Meas. Mag. 15 (2012) 41–44 [CrossRef] [Google Scholar]
  2. S. Marchesiello, A. Fasana, L. Garibaldi, Best parameter choice of stochastic resonance to enhance fault signature in bearings, in: International Conference on Structural Engineering Dynamics, Lagos, Portugal, 2015, pp. 1–7 [Google Scholar]
  3. C.U. Mba, S. Marchesiello, A. Fasana, L. Garibaldi, Vibration based condition monitoring of spur gears in mesh using stochastic resonance, in: Surveillance 8 International Conference, Roanne, France, 2015, pp. 1–15 [Google Scholar]
  4. C.U. Mba, S. Marchesiello, A. Fasana, L. Garibaldi, Fault detection in gears using stochastic resonance, in: Advances in Condition Monitoring of Machinery in Non-Stationary Operations, Springer, Cham, 2018, pp. 55–70 [Google Scholar]
  5. Y.G. Leng, et al., Numerical analysis and engineering application of large parameter stochastic resonance, J. Sound Vibration 292 (2006) 788–801 [CrossRef] [Google Scholar]
  6. Y. Lei, et al., Planetary gearbox fault diagnosis using an adaptive stochastic resonance method, Mech. Syst. Signal Process. 38 (2013) 113–124 [CrossRef] [Google Scholar]
  7., PHM Challenge Competition Data Set, 2009 [Google Scholar]
  8. R. Benzi, A. Sutera, A. Vulpiani, The mechanism of stochastic resonance, J. Phys. A: Math. General 14 (1981) L453 [CrossRef] [MathSciNet] [Google Scholar]
  9. M.D. McDonnell, D. Abbott, What is stochastic resonance? Definitions, misconceptions, debates, and its relevance to biology, PLoS Comput. Biol. 5 (2009) e1000348 [CrossRef] [PubMed] [Google Scholar]
  10. L. Gammaitoni, P. Hänggi, P. Jung, F. Marchesoni, Stochastic resonance, Rev. Modern Phys. 70 (1998) 223 [CrossRef] [Google Scholar]
  11. X.-h. Chen, G. Cheng, X.-l. Shan, X. Hu, Q. Guo, H.-g. Liu, Research of weak fault feature information extraction of planetary gear based on ensemble empirical mode decomposition and adaptive stochastic resonance, Measurement 73 (2015) 55–67 [CrossRef] [Google Scholar]
  12. K. Worden, I. Antoniadou, S. Marchesiello, C. Mba, L. Garibaldi, An illustration of new methods in machine condition monitoring, Part I: stochastic resonance, J. Phys.: Conf. Ser. 842 (2017) 1–10 [CrossRef] [Google Scholar]
  13. X. Zhang et al., An adaptive stochastic resonance method based on grey wolf optimizer algorithm and its application to machinery fault diagnosis, ISA Trans. 71 (2017) 206–214 [CrossRef] [PubMed] [Google Scholar]
  14. P.D. Samuel, D.J. Pines, A review of vibration-based techniques for helicopter transmission diagnostics. J. Sound Vibration 282 (2005) 475–508 [CrossRef] [Google Scholar]
  15. M. Lebold et al., Review of vibration analysis methods for gearbox diagnostics and prognostics. in: Proceedings of the 54th Meeting of the Society for Machinery Failure Prevention Technology, 2000 [Google Scholar]
  16. P. Večeř, M. Kreidl, R. Šmíd, Condition indicators for gearbox condition monitoring systems, Acta Polytech. 45 (2005) 35–43 [Google Scholar]
  17. K. Christian et al., On the use of time synchronous averaging, independent component analysis and support vector machines for bearing fault diagnosis, in: First International Conference On Industrial Risk Engineering, Montreal, 2007 [Google Scholar]
  18. E. Bechhoefer, M. Kingsley, A review of time synchronous average algorithms, in: Annual Conference of the Prognostics and Health Management Society, San Diego, California, 2009, pp. 24–33 [Google Scholar]
  19. R.B. Randall, J. Antoni, Rolling element bearing diagnostics-a tutorial, Mech. Syst. Signal Process. 25 (2011) 485–520 [Google Scholar]
  20. S. Goldman, Vibration spectrum analysis: a practical approach, Industrial Press Inc, 1999 [Google Scholar]

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