Adaptive redundant multiwavelet denoising with improved neighboring coefficients for gearbox fault detection

Mechanical Systems and Signal Processing

Volumn 38, Issue 2, 2013, Pages 549-568

  Chen, Jinglong ^a   Zi, Yanyang ^a   He, Zhengjia ^a   Wang, Xiaodong ^b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b CNPC TUBULAR GOODS RESEARCH INSTITUTE   (China)

Author keywords

Adaptive redundant multiwavelet; Denoising; Gearbox fault detection; Improved neighboring coefficients

Indexed keywords

DE-NOISING; ENVELOPE SPECTRUM ENTROPIES; GEARBOX VIBRATION SIGNAL; IMPROVED NEIGHBORING COEFFICIENTS; MULTI-WAVELET TRANSFORM; MULTIWAVELET; SPATIAL DEPENDENCIES; WAVELET COEFFICIENTS;

WAVELET TRANSFORMS;

FAULT DETECTION;

EID: 84878285921     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2013.03.005     Document Type: Article

References (29)

1. N.E. Huang, Z. Shen, and S.R. Long The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis Math. Phys. Eng. Sci. 454 1998 903 995
2. B. Liu, S. Riemenschneider, and Y. Xu Gearbox fault diagnosis using empirical mode decomposition and Hilbert spectrum Mech. Syst. Signal Process. 20 3 2005 718 734
3. J.S. Cheng, Y. Yang, and D.J. Yu The envelope order spectrum based on generalized demodulation time-frequency analysis and its application to gear fault diagnosis Mech. Syst. Signal Process. 24 2 2010 508 521
4. B. Li, J.M. Li, and Z.J. He Fault feature enhancement of gearbox in combined machinery center by using adaptive cascade stochastic resonance Science China Technological Sciences 54 2011 3203 3210
5. Y.G. Leng, T.Y. Wang, and Y. Guo Engineering signal processing based on bistable stochastic resonance Mech. Syst. Signal Process. 21 1 2007 138 150
6. J. Antoni The spectral kurtosis: a useful tool for characterizing non-stationary signals Mech. Syst. Signal Process. 20 2006 282 307
7. J. Antoni Fast computation of the kurtogram for the detection of transient faults Mech. Syst. Signal Process. 21 2007 108 124
8. W.X. Yang, and P.W. Tse Development of an advanced noise reduction method for vibration analysis based on singular value decomposition NDT&E Int. 36 2003 419 432
9. X.D. Wang, Y.Y. Zi, and Z.J. He Multiwavelet denoising with improved neighboring coefficients for application on rolling bearing fault diagnosis Mech. Syst. Signal Process. 25 2011 285 304
10. H.K. Jiang, Z.J. He, and C.D. Duan Gearbox fault diagnosis using adaptive redundant lifting scheme Mech. Syst. Signal Process. 20 2006 1992 2006
11. J. Yuan, Z.J. He, and Y.Y. Zi Gear fault detection using customized multiwavelet lifting schemes Mech. Syst. Signal Process. 24 2010 1509 1528
12. Z. Li, and Z.J. He Customized wavelet denoising using intra-scale and inter-scale dependency for bearing fault detection J. Sound Vibration 313 2008 342 359
13. G.C. Donovan, J.S. Geronimo, and D.P. Hardin Construction of orthogonal wavelets using fractal interpolation functions SIAM J. Math. Anal. 27 3 1996 1158 1192
14. Y. Qian, C.J. Huang, and C. Chen A multi-wavelet based algorithm for extracting diversiform partial discharge signal Autom. Electr. Power Syst. 7 2007 75 80
15. W. Sweldens The lifting scheme: a custom design construction of biorthogonal wavelets Appl. Comput. Harmonic Anal. 2 1996 186 200
16. X.D. Wang, Y.Y. Zi, and Z.J. He Multiwavelet construction via adaptive symmetric lifting scheme and its applications for rotating machinery fault diagnosis Meas. Sci. Technol. 20 2009 045103
17. Z.A. Amir, and A.Z. Valery Multiwavelet frames in signal space originated from hermite splines IEEE Trans. Signal Process. 55 3 2007 797 808
18. D.L. Donoho De-noising by soft-thresholding IEEE Trans. Inform. Theory 41 1995 613 627
19. T.T. Cai, and B.W. Silverman Incorporating information on neighboring coefficients in wavelet estimation Sankhya Ser. B 63 2001 127 148
20. A. Zifan, M.H. Moradi, and S. Gharibzadeh Microarray image enhancement by denoising using decimated and undecimated multiwavelet transforms Signal Image Video Process. 4 2009 177 185
21. X.G. Xia, J.S. Geronimo, D.P. Hardin, B.W. Suter, Why and how prefiltering for discrete multiwavelet transforms, in: 1996 IEEE International Conference on Acoustustics, Speech, and Signal Process, vol. 3 (1996) pp. 1578-1581.
22. L. Qu, and Z. He Mechanical Diagnostics 1986 Shanghai Science and Technology Press China
23. J.H. Kapur, and H.K. Kesavan Entropy Optimization Principles With Application 1992 Academic Press New York
24. S. Mallat A wavelet Tour of Signal Processing Second Edition 2003 Academic Press China
25. Y. Xu, J.B. Weaver, D.M. Healy, and J. Lu Wavelet transform domain filters: a spatially selective noise filteration technique IEEE Trans. Image Process. 3 1994 747 758
26. M.S. Crouse, R.D. Nowak, and R.G. Baraniuk Wavelet-based signal processing using hidden Markov models IEEE Trans. Signal Process. 46 4 1998 886 902
27. J. Liu, and P. Moulin Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients IEEE Trans. Image Process. 10 11 2001 1647 1658
28. G.Y. Chen, and T.D. Bui Multiwavelets denoising using neighboring coefficients IEEE Signal Process. Lett. 10 7 2003 211 214
29. V. Strela, G. Strang, Finite element multiwavelets, in: Proceedings of the IEEE-SP Interntional Symposium on (1994) pp. 32-35.