Generalized empirical mode decomposition and its applications to rolling element bearing fault diagnosis

Mechanical Systems and Signal Processing

Volumn 40, Issue 1, 2013, Pages 136-153

  Zheng, Jinde ^a   Cheng, Junsheng ^a   Yang, Yu ^a  

^a HUNAN UNIVERSITY   (China)

Author keywords

EMD; Empirical envelope demodulation; Fault diagnosis; Generalized empirical mode decomposition; Intrinsic time scale decomposition; Non stationary signal

Indexed keywords

EMD; EMPIRICAL ENVELOPE; EMPIRICAL MODE DECOMPOSITION; INTRINSIC TIME-SCALE DECOMPOSITIONS; NONSTATIONARY SIGNALS;

BEARINGS (MACHINE PARTS); FAILURE ANALYSIS; OPTICAL VARIABLES MEASUREMENT;

DEMODULATION;

EID: 84881311030     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2013.04.005     Document Type: Article

References (26)

1. N.E. Huang, S. Zheng, and S.R. Long The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis Proc. R. Soc. A, London 454 1998 903 995
2. N.E. Huang, and Z. Wu A review on Hilbert-Huang transform: method and its applications to geophysical studies Adv. Adaptive Data Anal. 1 2009 1 23
3. G. Xu, X. Wang, and X. Xu Improved EMD for the analysis of FM signals Mech. Syst. Signal Process. 33 2012 181 196
4. D. Yu, J. Cheng, and Y. Yang Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings Mech. Syst. Signal Process. 19 2005 259 270
5. Q. Chen, N.E. Huang, and S. Riemenschneider A B-spline approach for empirical mode decompositions Adv. Comput. Math. 24 2006 171 195
6. M.C. Peel, T.A. McMahon, and G.G.S. Pegram Assessing the performance of rational spline-based empirical mode decomposition using a global annual precipitation dataset Proc. R. Soc. A 465 2009 1919 1937
7. G.G.S. Pegram, M.C. Peel, and T.A. McMahon Empirical mode decomposition using rational splines: an application to rainfall time series Proc. R. Soc. A 464 2007 1483 1501
8. M.G. Frei, and I. Osorio Intrinsic time-scale decomposition: Time-frequency-energy analysis and real-time filtering of non-stationary signals Proc. R. Soc. A 463 2007 321 342
9. L. Li, and H.B. Ji Signal feature extraction based on an improved EMD method Measurement 42 2009 796 803
10. L. Cohen Time Frequency Analysis: Theory and Applications 1995 Prentice Hall Press
11. Z. Wu, N.E. Huang, and S.R. Long On the frequency Adv. Adaptive Data Anal. 1 2 2009 177 229
12. F. Gianfelici, G. Biagetti, and P. Crippa Multicomponent AM-FM representations: an asymptotically exact approach IEEE Trans. Audio, Speech, Lang. Process. 15 3 2007 823 837
13. Y. Qin, S. Qin, and Y. Mao Research on iterated Hilbert transform and its application in mechanical fault diagnosis Mech. Syst. Signal Process. 22 2008 1967 1980
14. P. Marages, and J.F. Kaiser Energy separation in signal modulation to speech analysis IEEE Trans. Signal Process. 41 10 1993 3024 3051
15. M. Liang, and I.S. Bozchalooi An energy operator approach to joint application of amplitude and frequency-demodulations for bearing fault detection Mech. Syst. Signal Process. 24 2010 1473 1494
16. S. Olhede, and T. WaldenA A generalized demodulation approachto time-frequency projections for multicom-ponent signals Proc. R. Soc. A 461 2059 2005 2159 2179
17. J.S. Cheng, J.D. Zheng, and Y. Yang Empirical envelope demodulation approach based on local characteristic-scale decomposition and its applications to mechanical fault diagnosis J. Mech. Eng. 48 19 2012 87 94
18. Q. Gai Research and Application on the Theory of Local Wave Time-Frequency Analysis Method 2001 Dalian University of Technology Dalian China 52 54
19. S. Peng, and W.L. Hwang Adaptive signal decomposition based on local narrow band signals IEEE Trans. Signal Process. 56 7 2008 2669 2676
20. B. Xuan, Q. Xie, and S. Peng EMD sifting based on band width IEEE Signal Process. Lett. 14 8 2007 537 540
21. Q. Xie, B. Xuan, and S. Peng Bandwidth empirical mode decomposition and its application Int. J. Wavelets, Multiresolution Inf. Process. 6 6 2008 777 798
22. M. Feldman Hilbert transform in vibration analysis Mech. Syst. Signal Process. 25 2011 735 802
23. G. Rilling, P. Flandrin, P. Goncalves, One empirical mode decomposition and its algorithms, in: Proceedings of IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP'03), Grado, Italy, 2003, 〈http://perso.ens- lyon.fr/paulo.goncalves/pub/emd-eurasip03.pdf〉.
24. M. Feldman Theoretical analysis and comparison of the Hilbert transform decomposition methods Mech. Syst. Signal Process. 22 2008 509 519
25. L. Zhang, G. Xiong, and H. Liu Bearing fault diagnosis using multi-scale entropy and adaptive neuro-fuzzy inference Expert Syst. Appl. 37 2010 6077 6085
26. Bearing Data Center, Case Western Reserve University, 〈http://csegroups.case.edu/bearingdatacenter/pages/download-data- file〉.