Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples
Tóm tắt
Từ khóa
Tài liệu tham khảo
Chu, 2009
Hammond, 1996, The analysis of non-stationary signals using time–frequency methods, J. Sound Vib., 190, 419, 10.1006/jsvi.1996.0072
L. Atlas, G. Bernard, S. Narayanan, Applications of time–frequency analysis to signals from manufacturing and machine monitoring sensors, Proc. IEEE, 1996, 84: 1319–1329
Cohen, 1995
Qian, 1996
Flandrin, 1999
Grochenig, 2000
2002
2003
Hlawatsch, 1992, Linear and quadratic time–frequency signal representations, IEEE Signal Process. Mag., 9, 21, 10.1109/79.127284
Daubechies, 1992
Mallat, 2009
Rioul, 1992, Time–scale energy distributions: a general class extending wavelet transforms, IEEE Trans. Signal Process., 40, 1746, 10.1109/78.143446
Flandrin, 1996, Geometry of affine time–frequency distributions, Appl. Comput. Harmonic Anal., 3, 10, 10.1006/acha.1996.0002
Baraniuk, 1993, Signal-dependent time frequency representation: optimal kernel design, IEEE Trans. Signal Process., 41, 1589, 10.1109/78.212733
Jones, 1995, An adaptive optimal kernel time–frequency representation, IEEE Trans. Signal Process., 43, 2361, 10.1109/78.469854
Auger, 1995, Improving the readability of time–frequency and time–scale representations by the reassignment method, IEEE Trans. Signal Process., 43, 1068, 10.1109/78.382394
Fonollosa, 1993, Wigner higher order moment spectra: definition, properties, computation and application to transient signal analysis, IEEE Trans. Signal Process., 41, 245, 10.1109/TSP.1993.193143
Fonollosa, 1994, Analysis of finite-energy signals using higher-order moments- and spectra-based time–frequency distributions, Signal Process., 36, 315, 10.1016/0165-1684(94)90030-2
Stankovic, 1996, L-class of time–frequency distributions, IEEE Signal Process. Lett., 3, 22, 10.1109/97.475827
L.J. Stankovic, S-class of distributions, in: IEE Proceedings – Vision, Image and Signal Processing, vol. 144(2), 1997. pp.57–64
Daubechies, 1990, The wavelet transform, time–frequency localization and signal analysis, IEEE Trans. Inf. Theory, 36, 961, 10.1109/18.57199
Coifman, 1992, Entropy-based algorithms for best basis selection, IEEE Trans. Inf. Theory, 38, 713, 10.1109/18.119732
Mallat, 1993, Matching pursuit with time–frequency dictionaries, IEEE Trans. Signal Process., 41, 3397, 10.1109/78.258082
Qian, 1994, Signal representation using adaptive normalized Gaussian functions, Signal Process., 36, 1, 10.1016/0165-1684(94)90174-0
Jaggi, 1998, High resolution pursuit for feature extraction, Appl. Comput. Harmonic Anal., 5, 428, 10.1006/acha.1997.0239
Chen, 1998, Atomic decomposition by basis pursuit, SIAM J. Sci. Comput., 20, 33, 10.1137/S1064827596304010
Bultan, 1999, A four-parameter atomic decomposition of chirplets, IEEE Trans. Signal Process., 47, 731, 10.1109/78.747779
Yin, 2002, A fast refinement for adaptive Gaussian chirplet decomposition, IEEE Trans. Signal Process., 50, 1298, 10.1109/TSP.2002.1003055
Zou, 2001, Parametric TFR via windowed exponential frequency modulated atoms, IEEE Signal Process. Lett., 8, 140, 10.1109/97.917696
Zou, 2004, Steady-motion-based Dopplerlet transform Application to the estimation of range and speed of a moving sound source, IEEE J. Ocean. Eng., 29, 887, 10.1109/JOE.2004.833229
Jachan, 2007, Time–frequency ARMA models and parameter estimators for underspread nonstationary random processes, IEEE Trans. Signal Process., 55, 4366, 10.1109/TSP.2007.896265
N.E. Huang, Z. Shen, S.R. Long, et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis, Proc. R. Soc. London Ser. A 1998, 454: 903–995
Huang, 1999, A new view of nonlinear water waves: the Hilbert spectrum, Annu. Rev. Fluid Mech., 31, 417, 10.1146/annurev.fluid.31.1.417
N.E. Huang, M.C. Wu, S.R. Long, et al., A confidence limit for the empirical mode decomposition and Hilbert spectral analysis, Proc. R. Soc. London Ser. A, 2003, 459: 2317–2345
2005
Huang, 2008, A review on Hilbert–Huang transform: method and its applications to geophysical studies, Rev. Geophys., 46, 1, 10.1029/2007RG000228
Wu, 2009, Ensemble empirical mode decomposition: a noise-assisted data analysis method, Adv. Adaptive Data Anal., 1, 1, 10.1142/S1793536909000047
Smith, 2005, The local mean decomposition and its application to EEG perception data, J. R. Soc. Interface, 2, 443, 10.1098/rsif.2005.0058
Maragos, 1993, On amplitude and frequency demodulation using energy operators, IEEE Trans. Signal Process., 41, 1532, 10.1109/78.212729
Maragos, 1993, Energy separation in signal modulations with application to speech analysis, IEEE Trans. Signal Process., 41, 3024, 10.1109/78.277799
Bovik, 1993, AM-FM energy detection and separation in noise using multiband energy operators, IEEE Trans. Signal Process., 41, 3245, 10.1109/78.258071
Potamianos, 1994, A comparison of the energy operator and Hilbert transform approaches for signal and speech demodulation, Signal Process., 37, 95, 10.1016/0165-1684(94)90169-4
He, 2001
Peng, 2004, Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography, Mech. Syst. Signal Process., 18, 199, 10.1016/S0888-3270(03)00075-X
Wang, 1993, Early detection of gear failure by vibration analysis—I: calculation of the time–frequency distribution, Mech. Syst. Signal Process., 7, 193, 10.1006/mssp.1993.1008
Wang, 1993, Early detection of gear failure by vibration analysis—II: interpretation of the time–frequency distribution using image processing techniques, Mech. Syst. Signal Process., 7, 205, 10.1006/mssp.1993.1009
Loughlin, 1997, Cohen-Posch (positive) time–frequency distributions and their application to machine vibration analysis, Mech. Syst. Signal Process., 11, 561, 10.1006/mssp.1997.0096
Oehlmann, 1997, A method for analysing gearbox faults using time–frequency representations, Mech. Syst. Signal Process., 11, 529, 10.1006/mssp.1996.0093
Staszewski, 1997, Time–frequency analysis in gearbox fault detections using the Wigner–Ville distribution and pattern recognition, Mech. Syst. Signal Process., 11, 673, 10.1006/mssp.1997.0102
Williams, 2000, Helicopter transmission fault detection via time–frequency, scale and spectral methods, Mech. Syst. Signal Process., 14, 545, 10.1006/mssp.2000.1296
Zou, 2004, A comparative study on time–frequency feature of cracked rotor by Wigner–Ville distribution and wavelet transform, J. Sound Vib., 276, 1, 10.1016/j.jsv.2003.07.002
Le, 2006, Time–frequency distributions for crack detection in rotors—A fundamental note, J. Sound Vib., 294, 397, 10.1016/j.jsv.2005.11.005
Adewusi, 2001, Wavelet analysis of vibration signals of an overhang rotor with a propagating transverse crack, J. Sound Vib., 246, 777, 10.1006/jsvi.2000.3611
Zheng, 2002, Gear fault diagnosis based on continuous wavelet transform, Mech. Syst. Signal Process., 16, 447, 10.1006/mssp.2002.1482
Yesilyurt, 2004, The application of the conditional moments analysis to gearbox fault detection—a comparative study using the spectrogram and scalogram, NDT&E Int., 37, 309, 10.1016/j.ndteint.2003.10.005
Sun, 2011, Time–frequency signal processing for gas–liquid two phase flow through a horizontal venturi based on adaptive optimal-kernel theory, Chin. J. Chem. Eng., 19, 243, 10.1016/S1004-9541(11)60161-4
Peng, 2002, Vibration signal analysis and feature extraction based on reassigned wavelet scalogram, J. Sound Vib., 253, 1087, 10.1006/jsvi.2001.4085
Peng, 2005, Detection of the rubbing-caused impacts for rotor-stator fault diagnosis using reassigned scalogram, Mech. Syst. Signal Process., 19, 391, 10.1016/j.ymssp.2003.09.007
Ma, 2009, Time–frequency features of two types of coupled rub-impact faults in rotor systems, J. Sound Vib., 321, 1109, 10.1016/j.jsv.2008.09.054
Lee, 1997, Higher-order time–frequency analysis and its application to fault detection in rotating machinery, Mech. Syst. Signal Process., 11, 637, 10.1006/mssp.1997.0098
Lee, 1999, Fault diagnosis of a gearbox using the sliced Wigner fourth order time frequency method smoothed by a new kernel function, KSME Int. J., 13, 940, 10.1007/BF03184761
Liu, 2002, Bearing failure detection using matching pursuit, NDT&E Int., 35, 255, 10.1016/S0963-8695(01)00063-9
Shi, 2004, Adaptive time–frequency decomposition for transient vibration monitoring of rotating machinery, Mech. Syst. Signal Process., 18, 127, 10.1016/S0888-3270(03)00085-2
Cui, 2011, Application of composite dictionary multi-atom matching in gear fault diagnosis, Sensors, 11, 5981, 10.3390/s110605981
Yang, 2005, Fault diagnosis of rolling element bearings using basis pursuit, Mech. Syst. Signal Process., 19, 341, 10.1016/j.ymssp.2004.03.008
Padovese, 2004, Hybrid time–frequency methods for non-stationary mechanical signal analysis, Mech. Syst. Signal Process., 18, 1047, 10.1016/j.ymssp.2003.12.003
Poulimenos, 2006, Parametric time-domain methods for non-stationary random vibration modelling and analysis—A critical survey and comparison, Mech. Syst. Signal Process., 20, 763, 10.1016/j.ymssp.2005.10.003
Yu, 2005, Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings, Mech. Syst. Signal Process., 19, 259, 10.1016/S0888-3270(03)00099-2
Cheng, 2008, Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis, Mech. Mach. Theory, 43, 712, 10.1016/j.mechmachtheory.2007.05.007
Cheng, 2009, Local rub-impact fault diagnosis of the rotor systems based on EMD, Mech. Mach. Theory, 44, 784, 10.1016/j.mechmachtheory.2008.04.006
Peng, 2005, A comparison study of improved Hilbert–Huang transform and wavelet transform: application to fault diagnosis for rolling bearing, Mech. Syst. Signal Process., 19, 974, 10.1016/j.ymssp.2004.01.006
Peng, 2005, An improved Hilbert–Huang transform and its application in vibration signal analysis, J. Sound Vib., 286, 187, 10.1016/j.jsv.2004.10.005
Guo, 2007, Vibration analysis of a cracked rotor using Hilbert–Huang transform, Mech. Syst. Signal Process., 21, 3030, 10.1016/j.ymssp.2007.05.004
Yang, 2008, Interpretation of mechanical signals using an improved Hilbert–Huang transform, Mech. Syst. Signal Process., 22, 1061, 10.1016/j.ymssp.2007.11.024
Yang, 2009, Empirical mode decomposition, an adaptive approach for interpreting shaft vibratory signals of large rotating machinery, J. Sound Vib., 321, 1144, 10.1016/j.jsv.2008.10.012
Wu, 2008, An improved method for restraining the end effect in empirical mode decomposition and its applications to the fault diagnosis of large rotating machinery, J. Sound Vib., 14, 586, 10.1016/j.jsv.2008.01.020
Wu, 2009, Diagnosis of subharmonic faults of large rotating machinery based on EMD, Mech. Syst. Signal Process., 23, 467, 10.1016/j.ymssp.2008.03.007
Gao, 2008, Rotating machine fault diagnosis using empirical mode decomposition, Mech. Syst. Signal Process., 22, 1072, 10.1016/j.ymssp.2007.10.003
Gai, 2006, The processing of rotor startup signals based on empirical mode decomposition, Mech. Syst. Signal Process., 20, 222, 10.1016/j.ymssp.2004.07.001
Ramesh Babu, 2008, Hilbert–Huang transform for detection and monitoring of crack in a transient rotor, Mech. Syst. Signal Process., 22, 905, 10.1016/j.ymssp.2007.10.010
Loutridis, 2004, Damage detection in gear systems using empirical mode decomposition, Eng. Struct., 26, 1833, 10.1016/j.engstruct.2004.07.007
Liu, 2006, Gearbox fault diagnosis using empirical mode decomposition and Hilbert spectrum, Mech. Syst. Signal Process., 20, 718, 10.1016/j.ymssp.2005.02.003
Ricci, 2011, Diagnostics of gear faults based on EMD and automatic selection of intrinsic mode functions, Mech. Syst. Signal Process., 25, 821, 10.1016/j.ymssp.2010.10.002
Li, 2010, EMD-based fault diagnosis for abnormal clearance between contacting components in a diesel engine, Mech. Syst. Signal Process., 24, 193, 10.1016/j.ymssp.2009.06.012
Lei, 2009, Application of the EEMD method to rotor fault diagnosis of rotating machinery, Mech. Syst. Signal Process., 23, 1327, 10.1016/j.ymssp.2008.11.005
Lei, 2009, Fault diagnosis of rotating machinery using an improved HHT based on EEMD and sensitive IMFs, Meas. Sci. Technol., 20, 1, 10.1088/0957-0233/20/12/125701
Zhang, 2010, Performance enhancement of ensemble empirical mode decomposition, Mech. Syst. Signal Process., 24, 2104, 10.1016/j.ymssp.2010.03.003
Zvokelj, 2010, Multivariate and multiscale monitoring of large-size low-speed bearings using ensemble empirical mode decomposition method combined with principal component analysis, Mech. Syst. Signal Process., 24, 1049, 10.1016/j.ymssp.2009.09.002
Zhao, 2012, Multivariate EMD and full spectrum based condition monitoring for rotating machinery, Mech. Syst. Signal Process., 27, 712, 10.1016/j.ymssp.2011.08.001
Wang, 2009, A demodulation method based on improved local mean decomposition and its application in rub-impact fault diagnosis, Meas. Sci. Technol., 20, 025704, 10.1088/0957-0233/20/2/025704
Wang, 2012, Application of local mean decomposition to the surveillance and diagnostics of low-speed helical gearbox, Mech. Mach. Theory, 47, 62, 10.1016/j.mechmachtheory.2011.08.007
Cheng, 2012, A rotating machinery fault diagnosis method based on local mean decomposition, Digital Signal Process., 22, 356, 10.1016/j.dsp.2011.09.008
Yang, 2012, An ensemble local means decomposition method and its application to local rub-impact fault diagnosis of the rotor systems, Measurement, 45, 561, 10.1016/j.measurement.2011.10.010
Cheng, 2007, The application of energy operator demodulation approach based on EMD in machinery fault diagnosis, Mech. Syst. Signal Process., 21, 668, 10.1016/j.ymssp.2005.10.005
Bassiuny, 2007, Flute breakage detection during end milling using Hilbert–Huang transform and smoothed nonlinear energy operator, Int. J. Mach. Tools Manuf., 47, 1011, 10.1016/j.ijmachtools.2006.06.016
Li, 2010, Gear fault detection based on Teager-Huang transform, Int. J. Rotating Mach., 2010, 502064, 10.1155/2010/502064
Liang, 2010, An energy operator approach to joint application of amplitude and frequency-demodulations for bearing fault detection, Mech. Syst. Signal Process., 24, 1473, 10.1016/j.ymssp.2009.12.007
Soltani Bozchalooi, 2010, Teager energy operator for multi-modulation extraction and its application for gearbox fault detection, Smart Mater. Struct., 19, 075008, 10.1088/0964-1726/19/7/075008
Feng, 2007, Nonstationary vibration signal analysis of hydroturbine based on adaptive chirplet decomposition, Struct. Health Monit., 6, 265, 10.1177/1475921707081969
Feng, 2007, Application of atomic decomposition to gear damage detection, J. Sound Vib., 302, 138, 10.1016/j.jsv.2006.11.017
Feng, 2008, Application of adaptive time–frequency analysis to fault diagnosis of machinery, Chin. J. Sci. Instrum., 29, 604
Z. Feng, F. Chu, Analysis of transient pressure fluctuation in hydroturbine draft tube based on Hilbert–Huang transform, in: Proceedings of the 3rd World Congress on Engineering Asset Management and Intelligent Maintenance Systems (WCEAM-IMS 2008), Beijing: 27–30 October, 2008, pp. 463–468