Biphase randomization wavelet bicoherence for mechanical fault diagnosis

Measurement: Journal of the International Measurement Confederation

Volumn 49, Issue 1, 2014, Pages 407-420

  Li, Yong ^a   Lin, Jing ^b   Wang, Xiufeng ^a   Lei, Yaguo ^b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Fault diagnosis; Quadratic phase coupling; Wavelet bicoherence

Indexed keywords

ALGORITHMS; FAILURE ANALYSIS; NEONATAL MONITORING;

BICOHERENCE; COHERENCE TIME; ENSEMBLE AVERAGES; MECHANICAL FAULT DIAGNOSIS; NONLINEAR BEHAVIOR; PHASE COUPLING; QUADRATIC PHASE COUPLINGS; RANDOMIZATION ALGORITHM;

RANDOM PROCESSES;

EID: 84891843701     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2013.12.012     Document Type: Article

References (28)

1. D.R. Brillinger An introduction to polyspectra Ann. Math. Stat. 1965 1351 1374
2. M. Hinich, and C. Clay The application of the discrete Fourier transform in the estimation of power spectra, coherence, and bispectra of geophysical data Rev. Geophys. 6 1968 347 363
3. M.A.K. Elsayed Wavelet bicoherence analysis of wind-wave interaction Ocean Eng. 33 2006 458 470 (Pubitemid 43045880)
4. P. Huber, B. Kleiner, T. Gasser, and G. Dumermuth Statistical methods for investigating phase relations in stationary stochastic processes Audio Electroacoustics IEEE Trans. 19 1971 78 86
5. T.P. Barnett, L.C. Johnson, P. Naitoh, N. Hicks, and C. Nute Bispectrum analysis of electroencephalogram signals during waking and sleeping Science 172 1971 401 402
6. M. Godfrey An exploratory study of the bi-spectrum of economic time series J. Roy. Stat. Soc.: Ser. C (Appl. Stat.) 14 1965 48 69
7. K. Lii, M. Rosenblatt, and A. VAN Bispectral measurements in turbulence J. Fluid Mech. 77 1976 45 62
8. L. Jiang, Y. Liu, X. Li, and S. Tang Using bispectral distribution as a feature for rotating machinery fault diagnosis Measurement 44 2011 1284 1292
9. B. Chen, Z. He, X. Chen, H. Cao, G. Cai, and Y. Zi A demodulating approach based on local mean decomposition and its applications in mechanical fault diagnosis Meas. Sci. Technol. 22 2011 055704
10. A. Rivola, and P.R. White Bispectral analysis of the bilinear oscillator with application to the detection of fatigue cracks J. Sound Vib. 216 1998 889 910 (Pubitemid 128386979)
11. L. Gelman, P. White, and J. Hammond Fatigue crack diagnostics: a comparison of the use of the complex bicoherence and its magnitude Mech. Syst. Signal Process. 19 2005 913 918 (Pubitemid 40556442)
12. F. Gu, Y. Shao, N. Hu, A. Naid, and A.D. Ball Electrical motor current signal analysis using a modified bispectrum for fault diagnosis of downstream mechanical equipment Mech. Syst. Signal Process. 25 2011 360 372
13. F. Combet, L. Gelman, and G. LaPayne Novel detection of local tooth damage in gears by the wavelet bicoherence Mech. Syst. Signal Process. 26 2012 218 228
14. J. Fackrell, S. McLaughlin, P. White, Practical issues concerning the use of the bicoherence for the detection of quadratic phase coupling, in: Proceedings of the IEEE Workshop on HOS (IEEE, 1995), 1995, pp. 1-5.
15. Y. Larsen, A. Hanssen, Wavelet-polyspectra: analysis of non-stationary and non-Gaussian/non-linear signals, in: Statistical Signal and Array Processing, 2000. Proceedings of the Tenth IEEE Workshop on, IEEE, 2000, pp. 539-543.
16. B.P. van Milligen, E. Sanchez, T. Estrada, C. Hidalgo, B. Branas, B. Carreras, and L. Garcia Wavelet bicoherence: a new turbulence analysis tool Phys. Plasmas 2 1995 3017 3032
17. K. Taekhyun, E.J. Powers, W.M. Grady, A. Arapostathis, A Novel QPC detector for the health monitoring of rotating machines, in: Instrumentation and Measurement Technology Conference Proceedings, 2007. IMTC 2007. IEEE, 2007, pp. 1-6.
18. Y.C. Kim, and E.J. Powers Digital bispectral analysis and its applications to nonlinear wave interactions Plasma Sci. IEEE Trans. 7 1979 120 131
19. C.R.P. Courtney, S.A. Neild, P.D. Wilcox, and B.W. Drinkwater Application of the bispectrum for detection of small nonlinearities excited sinusoidally J. Sound Vib. 329 2010 4279 4293
20. J. Lin Feature extraction of machine sound using wavelet and its application in fault diagnosis NDT and E Int. 34 2001 25 30 (Pubitemid 32088754)
21. X. Li, X. Yao, J. Fox, and J.G. Jefferys Interaction dynamics of neuronal oscillations analysed using wavelet transforms J. Neurosci. Methods 160 2007 178 185 (Pubitemid 46123560)
22. X. Li, D. Li, L.J. Voss, and J.W. Sleigh The comodulation measure of neuronal oscillations with general harmonic wavelet bicoherence and application to sleep analysis NeuroImage 48 2009 501 514
23. Y.-C. Choi, and Y.-H. Kim Fault detection in a ball bearing system using minimum variance cepstrum Meas. Sci. Technol. 18 2007 1433
24. W. Su, F. Wang, H. Zhu, Z. Zhang, and Z. Guo Rolling element bearing faults diagnosis based on optimal Morlet wavelet filter and autocorrelation enhancement Mech. Syst. Signal Process. 24 2010 1458 1472
25. Y. Zhou, J. Chen, G.M. Dong, W.B. Xiao, and Z.Y. Wang Application of the horizontal slice of cyclic bispectrum in rolling element bearings diagnosis Mech. Syst. Signal Process. 26 2012 229 243
26. I.S. Bozchalooi, and M. Liang Parameter-free bearing fault detection based on maximum likelihood estimation and differentiation Meas. Sci. Technol. 20 2009 065102
27. R.B. Randall, and J. Antoni Rolling element bearing diagnostics - a tutorial Mech. Syst. Signal Process. 25 2011 485 520
28. Y. Lei, D. Kong, J. Lin, and M.J. Zuo Fault detection of planetary gearboxes using new diagnostic parameters Meas. Sci. Technol. 23 2012 055605