269
Views
30
CrossRef citations to date
0
Altmetric
Articles

Difference equation based empirical mode decomposition with application to separation enhancement of multi-fault vibration signals

, , &
Pages 457-467 | Received 05 Sep 2016, Accepted 24 Oct 2016, Published online: 10 Nov 2016

References

  • Y. Bao, H. Wang, and B. Wang, Short-term wind power prediction using differential EMD and relevance vector machine, Neural Comp. Appl. 25 (2014), pp. 283–289.
  • G. Bellini, et al., Final results of Borexino Phase-I on low-energy solar neutrino spectroscopy, Phys. Rev. D 89 (2014), p. 112007.
  • L. Chen, X. Xia, H. Zheng, and M. Qiu, Friction torque behavior as a function of actual contact angle in four-point-contact ball bearing, Appl. Math. Nonlinear Sci. 1 (2016), pp. 53–64.
  • M. Colominas, G. Schlotthauer, and M. Torres, A suitable tool for biomedical signal processing, Biomed. Signal Process. Control 14 (2014), pp. 19–29.
  • M. Dätig and T. Schlurmann, Performance and limitations of the Hilbert--Huang transformation (HHT) with an application to irregular water waves, Ocean Eng. 31 (2004), pp. 1783–1834.
  • E. Deléchelle, J. Lemoine, and O. Niang, Empirical mode decomposition: An analytical approach for sifting process, IEEE Signal Process. Lett. 12 (2005), pp. 764–767.
  • E. Diop, R. Alexandre, and A. Boudraa, A PDE characterization of the intrinsic mode functions, in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Taibei, Taiwan, 2009, pp. 3429–3432.
  • E. Diop, R. Alexandre, and A. Boudraa, A PDE model for 2D intrinsic mode functions, in Proceedings of ICIP, Cairo, Egypt, 2009, pp. 3961–3964.
  • R. Ditommaso, M. Mucciarelli, S. Parolai, and M. Picozzi, Monitoring the structural dynamic response of a masonry tower: Comparing classical and time-frequency analyses, Bull. Earthquake Eng. 10 (2012), pp. 1221–1235.
  • G. Fan, L. Peng, W. Hong, and F. Sun, Electric load forecasting by the SVR model with differential empirical mode decomposition and auto regression, Neurocomputing 173 (2016), pp. 958–970.
  • X. He, Research on empirical mode decomposition and applications on faults diagnosis, Masters thesis, Shanghai Jiaotong University, China, 2005.
  • N. Huang, Z. Shen, S. Long, M.C. Wu, H.H. Shih, Q. Zheng, N.-C. Yen, C.C. Tung, and H.H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. Lond. Ser. A 454 (1998), pp. 903–995.
  • A. Jardine, D. Lin, and D. Banjevic, A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mech. Syst. Signal Process. 20 (2006), pp. 1483–1510.
  • Y. Jiang, Z. Li, C. Zhang, C. Hu, and Z. Peng, On the bi-dimensional variational decomposition applied to nonstationary vibration signals for rolling bearing crack detection in coal cutters, Meas. Sci. Tech. 27 (2016), p. 065103.
  • Y. Jiang, H. Zhu, and Z. Li, A new compound faults detection method for rolling bearings based on empirical wavelet transform and chaotic oscillator, Chaos Soliton. Fract. 89 (2016), pp. 8–19.
  • B. Jing and H. Li, Fault diagnoses of cracked rotor and rub-impact rotor based on DEMD method, Noise Vib. Control 29 (2009), pp. 66–69.
  • Z. Li, Y. Jiang, C. Hu, and Z. Peng, Recent progress on decoupling diagnosis of hybrid failures in gear transmission systems using vibration sensor signal: A review, Measurement 90 (2016), pp. 4–19.
  • Z. Li, Y. Jiang, X. Wang, and Z. Peng, Multi-mode separation and nonlinear feature extraction of hybrid gear failures in coal cutters using adaptive nonstationary vibration analysis, Nonlinear Dyn. 84 (2016), pp. 295–310.
  • M. Li, F. Li, B. Jing, H. Bai, H. Li, and G. Meng, Multi-fault diagnosis of rotor system based on differential-based empirical mode decomposition, JVC 21 (2015), pp. 1821–1837.
  • M. Li and G. Zhang, Characteristics of multi-national carbon emissions based on empirical mode decomposition, in Proceedings of Sixth International Conference on Business Intelligence and Financial Engineering, Hangzhou, China, 2013, pp. 458–462.
  • H. Liu and Z. Xuan, Improving frequency-band separating ability of EMD with a differential operator, J. Vib. Shock 32 (2013), pp. 133–135.
  • R. Martis, U. Acharya, J. Tan, A. Petznick, R. Yanti, C. Chua, E. Ng, and L. Tong, Application of empirical mode decomposition (EMD) for automated detection of epilepsy using EEG signals, Int. J. Neural Syst. 22 (2012), p. 1250027.
  • P. McFadden, A revised model for the extraction of periodic waveforms by time domain averaging, Mech. Syst. Signal Process. 1 (1987), pp. 83–95.
  • P. McFadden, Interpolation techniques for time domain averaging of gear vibration, Mech. Syst. Signal Process. 3 (1989), pp. 87–97.
  • P. McFadden, Window functions for the calculation of the time domain averages of the vibration of the individual planet gears and sun gear in an epicyclic gearbox, J. Vib. Acoust. 116 (1994), pp. 179–187.
  • P. McFadden and J. Smith, Vibration monitoring of rolling element bearings by the high-frequency resonance technique -- A review, Trib. Int. 17 (1984), pp. 3–10.
  • A. Murua and J.M. Sanz-Serna, Vibrational resonance: A study with high-order word-series averaging, Appl. Math. Nonlinear Sci. 1 (2016), pp. 239–246.
  • O. Niang, E. Deléchelle, and J. Lemoine, A spectral approach for sifting process in empirical mode decomposition, IEEE Trans. Signal Process. 58 (2010), pp. 5612–5623.
  • O. Niang, A. Thioune, M. Gueirea, E. Deléchelle, and J. Lemoine, Partial differential equation-based approach for empirical mode decomposition: Application on image analysis, IEEE Trans. Image Process. 21 (2012), pp. 3991–4001.
  • A. Pigorini, A. Casali, S. Casarotto, F. Ferrarelli, G. Baselli, M. Mariotti, M. Massimini, and M. Rosanova, Time-frequency spectral analysis of TMS-evoked EEG oscillations by means of Hilbert-Huang transform, J. Neurosci. Methods. 198 (2011), pp. 236–245.
  • B. Premanode and C. Toumazou, Improving prediction of exchange rates using differential EMD, Expert Sys. Appl. 40 (2013), pp. 377–384.
  • N. Rehman and D. Mandic, Empirical mode decomposition for trivariate signals, IEEE Trans. Signal Process. 58 (2010), pp. 1059–1068.
  • P. Samuel, J. Conroy, and D. Pines, Planetary transmission diagnostics, NASA/CR-2004-213068, NASA Glenn Research Center, 2004.
  • R. Sharma and S. Prasanna, A better decomposition of speech obtained using modified empirical mode decomposition, Digital Signal Process. 58 (2016), pp. 26–39.
  • H. Vincent, S. Hu, and Z. Hou, Damage detection using empirical mode decomposition method and a comparison with wavelet analysis, in Proceddings of Second International Workshop on Structural Health Monitoring, Stanford, CA, 1999, pp. 891–900.
  • S. Wu, J. Chiou, E. Goldman, and A. Boudraa, Solution for mode mixing phenomenon of the empirical mode decomposition, in Proceedings of 3rd International Conference on Advanced Computer Theory and Engineering, Chengdu, China, 2010, pp. 2500–2504.
  • Z. Wu and N.E. Huang, Ensemble empirical mode decomposition: A noise-assisted data analysis method, Adv. Adaptive Data Anal. 1 (2009), pp. 1–41.
  • H. Xiao, J. Zhou, J. Xiao, W. Fu, X. Xia, and W. Zhang, Fault diagnosis for rotating machinery based on multi-differential empirical mode decomposition, J. Vibroengin. 16 (2014), pp. 487–498.
  • A. Yin and X. Wang, Signal restoring based on PDE and its application in end effect processing of EMD, J. Vib. Shock 31 (2012), pp. 6–9.
  • B. Zhu, P. Wang, J. Chevallier, and Y. Wei, Carbon price analysis using empirical mode decomposition, Comput. Econ. 45 (2015), pp. 195–206.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.