Time-varying frequency-shifting signal-assisted empirical mode decomposition method for AM-FM signals

Mechanical Systems and Signal Processing

Volumn 23, Issue 8, 2009, Pages 2458-2469

  Guanlei, Xu ^a   Xiaotong, Wang ^a   Xiaogang, Xu ^a  

^a DALIAN NAVAL ACADEMY   (China)

Author keywords

Assisted signal; Empirical mode decomposition (EMD); Time varying frequency shifting signal (TFS)

Indexed keywords

ASSISTED SIGNAL; AVERAGE NUMBERS; EMPIRICAL MODE DECOMPOSITION; EMPIRICAL MODE DECOMPOSITION (EMD); EMPIRICAL MODE DECOMPOSITION METHOD; EXTREMA DENSITY; FM SIGNALS; FOLLOWING PROBLEM; INTRINSIC MODE FUNCTIONS; LEAST SQUARE METHODS; LOCAL EXTREMUM; MASKING SIGNALS; MONO-COMPONENT; PER UNIT LENGTH; TIME VARYING; TIME-VARYING FREQUENCY; TIME-VARYING FREQUENCY-SHIFTING SIGNAL (TFS);

ACOUSTIC SIGNAL PROCESSING; AMPLITUDE MODULATION;

TIME VARYING SYSTEMS;

EID: 67651064288     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2009.06.006     Document Type: Article

References (19)

1. Huang N.E., Shen Z., Long S.R., Wu M.C., et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London A 454 (1998) 903-995
2. Xu G.L., Wang X.T., Xu X.G., et al. Image enhancement algorithm based on neighborhood limited empirical mode decomposition. Acta Electronica Sinica 34 3 (2006) 99-103
3. Xu G.L., Wang X.T., and Xu X.G. Neighborhood limited empirical mode decomposition and application in image processing. IEEE Proceedings of the ICIG (2007) 149-154
4. Xu G.L., Wang X.T., Xu X.G., and Zhu T. Multi-band image fusion algorithm based on neighborhood limited empirical mode decomposition. Journal of Infrared and Millimeter Waves 25 3 (2006) 225-228
5. Wu Z., and Huang N.E. A study of the characteristics of white noise using the empirical mode decomposition method. Proceedings of the Royal Society of London A 460 (2004) 1597-1611
6. Xu G.L., Wang X.T., Xu X.G., et al. The conditions and principle for the direct decomposition from multi-component to mono-component using EMD. Progress in Natural Science of China 16 10 (2006) 1356-1360 (in Chinese)
7. Huang N.E., Shen Z., and Long S.R. A new view of nonlinear water waves: the Hilbert spectrum. Annual Review of Fluid Mechanics 31 (1999) 417-457
8. R. Deering, J.F. Kaiser, The use of a masking signal to improve empirical mode decomposition, ICASSP 2005, vol. IV, IEEE, pp. 485-488.
9. N. Senroy, S. Suryanarayanan, Two techniques to enhance empirical mode decomposition for power quality applications, in: Power Engineering Society General Meeting, IEEE, Tampa, FL, USA, 2007, pp. 1-6.
10. Senroy N., Suryanarayanan S., and Ribeiro P.F. An improved Hilbert-Huang method for analysis of time-varying waveforms in power quality. IEEE Transactions on Power Systems 22 4 (2007) 1843-1850
11. R.J. Gledhill, Methods for investigating conformational change in biomolecular simulations, A dissertation for the degree of Doctor of Philosophy, Department of Chemistry, The University of Southampton, 2003, 201pp.
12. Flandrin P., Gonçalvès P., and Rilling G. EMD equivalent filter banks, from interpretation to applications. In: Huang N.E., and Shen S.S.P. (Eds). Hilbert-Huang Transform: Introduction and Applications (2005), World Scientific, Singapore 67-87 360pp
13. Z. Wu, Norden E. Huang, Ensemble empirical mode decomposition: a noise assisted data analysis method, COLA Technical Report, 2005. Available from: 〈ftp://grads.iges.org/pub/ctr/ctr_193.pdf〉.
14. Flandrin P., Rilling G., and Gonçalvès P. Empirical mode decomposition as a filter bank. IEEE Signal Processing Letters 11 (2004) 112-114
15. Rilling G., and Flandrin P. One or two frequencies? The empirical mode decomposition answers. IEEE Transactions on Signal Processing 56 1 (2008) 85-95
16. Cheng J., Yu D., and Yang Y. A fault diagnosis approach for roller bearings based on EMD method and AR model. Mechanical Systems and Signal Processing 20 (2006) 350-362
17. Qin Y., Qin S., and Mao Y. Research on iterated Hilbert transform and its application in mechanical fault diagnosis. Mechanical Systems and Signal Processing 22 8 (2008) 1967-1980
18. Yang W. Interpretation of mechanical signals using an improved Hilbert-Huang transform. Mechanical Systems and Signal Processing 22 5 (2008) 1061-1071
19. Feldman M. Time-varying vibration decomposition and analysis based on the Hilbert transform. Journal of Sound and Vibration 295 3-5 (2006) 518-530