The infogram: Entropic evidence of the signature of repetitive transients

Mechanical Systems and Signal Processing

Volumn 74, Issue , 2016, Pages 73-94

  Antoni, Jerome ^a  

^a LABORATOIRE VIBRATIONS ACOUSTIQUE   (France)

Author keywords

Cyclostationarity; Entropy; Infogram; Kurtogram; Spectral kurtosis; Spectral negentropy

Indexed keywords

ENTROPY; HIGHER ORDER STATISTICS; IMPULSE NOISE; THERMODYNAMICS;

CYCLOSTATIONARITY; INFOGRAM; KURTOGRAM; NEGENTROPY; SPECTRAL KURTOSIS;

TRANSIENTS;

EID: 84961170009     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2015.04.034     Document Type: Article

References (44)

1. S.G. Braun Mechanical Signature Analysis, Theory and Applications 1986 Academic Press London
2. S.G. Braun The signature analysis of sonic bearing vibrations EEE Trans. Sonics Ultrason. 27 6 1980 317 327
3. D. Dyer, and R.M. Stewart Detection of rolling element bearing damage by statistical vibration analysis Mech. Des. 100 1978 229 235
4. D.E. Butler The Shock-pulse method for the detection of damaged rolling bearings Non-Destr. Test. 6 2 1973 92 95
5. J.L. Frarey, The history and application of the envelope detector, in: Proceedings of Technology Showcase: Integrated Monitoring Diagnostics and Failure Prevention, Mobile, Alabama, April 22-26, 1996.
6. S.G. Braun, and B. Seth Analysis of repetitive mechanism signatures J. Sound Vib. 70 4 1980 513 522
7. W.A. Gardner, A. Napolitano, and L. Paura Cyclostationarity: half a century of research Signal Process. 86 4 2006 639 697
8. J. Antoni The spectral kurtosis: a useful tool for characterising non-stationary signals Mech. Syst. Sig. Process. 20 2 2006 282 307
9. J. Antoni, and R.B. Randall The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines Mech. Syst. Sig. Process. 20 2 2006 308 331
10. J. Antoni Fast computation of the kurtogram for the detection of transient faults Mech. Syst. Sig. Process. 21 1 2007 108 124
11. Y. Zhang, and R.B. Randall Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram Mech. Syst. Sig. Process. 23 5 2009 1509 1517
12. Y. Wang, Z. He, and Y. Zi Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform Mech. Syst. Sig. Process. 24 1 2010 119 137
13. Y. Wang, and M. Liang An adaptive SK technique and its application for fault detection of rolling element bearings Mech. Syst. Sig. Process. 25 5 2011 1750 1764
14. Y. Lei, J. Lin, Z. He, and Y. Zi Application of an improved kurtogram method for fault diagnosis of rolling element bearings Mech. Syst. Sig. Process. 25 5 2011 1738 1749
15. D. Wang, P.W. Tse, and K.L. Tsui An enhanced Kurtogram method for fault diagnosis of rolling element bearings Mech. Syst. Sig. Process. 35 1-2 2013 176 199
16. B.i. Chen, Z. Zhang, Y. Zi, Z. He, and C. Sun Detecting of transient vibration signatures using an improved fast spatial-spectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery Mech. Syst. Sig. Process. 40 1 2013 1 37
17. P.W. Tse, and Dong Wang Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement - Parts 1: The design of a new sparsogram for fast bearing fault diagnosis Mech. Syst. Sig. Process. 40 2 2013 499 519
18. P.W. Tse, and D. Wang Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement - Parts 2: The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection Mech. Syst. Sig. Process. 40 2 2013 520 544
19. H. Sun, Z. He, Y. Zi, J. Yuan, X. Wang, J. Chen, and S. He Multiwavelet transform and its applications in mechanical fault diagnosis - a review Mech. Syst. Sig. Process. 43 1-2 2014 1 24
20. C. Pachaud, R. Salvetat, and C. Fray Crest factor and kurtosis contributions to identify defects inducing periodical impulsive forces Mech. Syst. Sig. Process. 11 6 1997 903 916
21. T. Barszcz, and A. JabŁoński A novel method for the optimal band selection for vibration signal demodulation and comparison with the kurtogram Mech. Syst. Sig. Process. 25 1 2011 431 451
22. C. Capdessus, M. Sidahmed, and J.L. Lacoume Cyclostationary processes: application in gear faults early diagnosis Mech. Syst. Sig. Process. 14 3 2000 371 385
23. J. Antoni, F. Bonnardot, A. Raad, and M. El Badaoui Cyclostationary modelling of rotating machine vibration signals Mech. Syst. Sig. Process. 18 6 2004 1285 1314
24. J. Antoni Cyclic spectral analysis of rolling-element bearing signals: facts and fictions J. Sound Vib. 304 3-5 2007 497 529
25. J. Antoni Cyclic spectral analysis in practice Mech. Syst. Sig. Process. 21 2 2007 597 630
26. J. Antoni Cyclostationarity by examples Mech. Syst. Sig. Process. 23 4 2009 987 1036
27. J. Urbanek, J. Antoni, and T. Barszcz Detection of signal component modulations using modulation intensity distribution Mech. Syst. Sig. Process. 28 2012 399 413
28. V. Girondin, K.M. Pekpe, H. Morel, and J.-P. Cassar Bearings fault detection in helicopters using frequency readjustment and cyclostationary analysis Mech. Syst. Sig. Process. 38 2 2013 499 514
29. R.B. Randall, J. Antoni, and S. Chobsaard The relationship between spectral correlation and envelope analysis for cyclostationary machine signals, application to ball bearing diagnostics Mech. Syst. Syst. Process. 15 5 2001 945 962
30. P. Borghesani, P. Pennacchi, R. Ricci, and S. Chatterton Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals Mech. Syst. Sig. Process. 40 1 2013 38 55
31. J. Urbanek, T. Barszcz, and J. Antoni Integrated modulation intensity distribution as a practical tool for condition monitoring Appl. Acoust. 77 2014 184 194
32. P. Borghesani, P. Pennacchi, and S. Chatterton The relationship between kurtosis- and envelope-based indexes for the diagnostic of rolling element bearings Mech. Syst. Sig. Process. 43 1-2 2014 25 43
33. L. Brillouin Science and Information Theory second ed. 1962 Academic Press New York, NY
34. Bernard H. Lavenda Statistical Physics. A Probabilistic Approach 1991 Wiley-Interscience Chichester
35. I.I. Hirschman A note on entropy Am. J. Math. 1957 152 156
36. S. Wehner, and A. Winter Entropic uncertainty relations - a survey New J. Phys. - Spec. Issue Quantum Inf. Many-Body Theor. 12 025009 2010
37. D.C. Brody, and B.K. Meister Discrete uncertainty relations J. Phys. A: Math. Gen. 32 26 1999 4921 4930
38. V. DeBrunner, M. Ozaydin, T. Przebinda, J. Havlicek, The optimal solutions to the continuous and discrete-time versions of the Hirschman uncertainty principle, in: IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 1(81), 2000.
39. 2(Z/NZ) IEEE Trans. Signal Process. 53 8 2005 2690 2699
40. J. Antoni, and R.B. Randall A stochastic model for simulation and diagnostics of rolling element bearings with localized faults ASME J. Vibr. Acoust. 125 3 2003 282 289
41. R.B. Randall, and J. Antoni Rolling element bearing diagnostics - a tutorial Mech. Syst. Sig. Process. 25 2 2011 485 520
42. S.G. Braun The synchronous (time domain) average revisited Mech. Syst. Sig. Process. 25 4 2011 1087 1102
43. P. Borghesani, P. Pennacchi, R.B. Randall, N. Sawalhi, and R. Ricci Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions Mech. Syst. Sig. Process. 36 2 2013 370 384
44. J. Obuchowski, A. Wyłomańska, and R. Zimroz Selection of informative frequency band in local damage detection in rotating machinery Mech. Syst. Sig. Process. 48 1-2 2014 138 152