메뉴 건너뛰기




Volumn 54, Issue , 2015, Pages 457-480

Automatic fault feature extraction of mechanical anomaly on induction motor bearing using ensemble super-wavelet transform

Author keywords

Bearing fault diagnosis; Feature extraction; Induction motor; Q factor; Super wavelet transform

Indexed keywords

BEARINGS (MACHINE PARTS); EXTRACTION; FEATURE EXTRACTION; INDUCTION MOTORS; Q FACTOR MEASUREMENT; WAVELET TRANSFORMS;

EID: 84916216664     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2014.09.007     Document Type: Article
Times cited : (191)

References (46)
  • 1
    • 29244467991 scopus 로고    scopus 로고
    • Condition monitoring and fault diagnosis of electrical motors - A review
    • S. Nandi, H.A. Toliyat, and L. Xiaodong Condition monitoring and fault diagnosis of electrical motors - a review IEEE Trans. Energy Convers. 20 4 2005 719 729
    • (2005) IEEE Trans. Energy Convers. , vol.20 , Issue.4 , pp. 719-729
    • Nandi, S.1    Toliyat, H.A.2    Xiaodong, L.3
  • 2
    • 81855170055 scopus 로고    scopus 로고
    • Induction motors bearing fault detection using pattern recognition techniques
    • J. Zarei Induction motors bearing fault detection using pattern recognition techniques Expert Syst. Appl. 39 1 2012 68 73
    • (2012) Expert Syst. Appl. , vol.39 , Issue.1 , pp. 68-73
    • Zarei, J.1
  • 3
    • 33750528937 scopus 로고    scopus 로고
    • Approximate entropy as a diagnostic tool for machine health monitoring
    • R. Yan, and R.X. Gao Approximate entropy as a diagnostic tool for machine health monitoring Mech. Syst. Sig. Process 21 2 2007 824 839
    • (2007) Mech. Syst. Sig. Process , vol.21 , Issue.2 , pp. 824-839
    • Yan, R.1    Gao, R.X.2
  • 4
    • 79953856339 scopus 로고    scopus 로고
    • Weak fault feature extraction of rolling bearing based on cyclic Wiener filter and envelope spectrum
    • Y. Ming, J. Chen, and G. Dong Weak fault feature extraction of rolling bearing based on cyclic Wiener filter and envelope spectrum Mech. Syst. Signal Process 25 5 2011 1773 1785
    • (2011) Mech. Syst. Signal Process , vol.25 , Issue.5 , pp. 1773-1785
    • Ming, Y.1    Chen, J.2    Dong, G.3
  • 5
    • 78649600770 scopus 로고    scopus 로고
    • Rolling element bearing diagnostics - A tutorial
    • R.B. Randall, and J. Antoni Rolling element bearing diagnostics - a tutorial Mech. Syst. Sig. Process 25 2 2011 485 520
    • (2011) Mech. Syst. Sig. Process , vol.25 , Issue.2 , pp. 485-520
    • Randall, R.B.1    Antoni, J.2
  • 6
    • 0035520683 scopus 로고    scopus 로고
    • A comparative study of acoustic and vibration signals in detection of gear failures using Wigner-Ville distribution
    • N. Baydar, and A. Ball A comparative study of acoustic and vibration signals in detection of gear failures using Wigner-Ville distribution Mech. Syst. Signal Process. 15 6 2001 1091 1107
    • (2001) Mech. Syst. Signal Process. , vol.15 , Issue.6 , pp. 1091-1107
    • Baydar, N.1    Ball, A.2
  • 7
    • 84862780176 scopus 로고    scopus 로고
    • Fast-varying AM-FM components extraction based on an adaptive STFT
    • H. Xie, J. Lin, and Y.G. Lei Fast-varying AM-FM components extraction based on an adaptive STFT Digital Signal Process 22 4 2012 664 670
    • (2012) Digital Signal Process , vol.22 , Issue.4 , pp. 664-670
    • Xie, H.1    Lin, J.2    Lei, Y.G.3
  • 8
    • 58949090453 scopus 로고    scopus 로고
    • Cyclostationarity by examples
    • J. Antoni Cyclostationarity by examples Mech. Syst. Signal Process. 23 4 2009 987 1036
    • (2009) Mech. Syst. Signal Process. , vol.23 , Issue.4 , pp. 987-1036
    • Antoni, J.1
  • 9
    • 5444236478 scopus 로고    scopus 로고
    • The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis
    • N.E. Huang, Z. Shen, and S.R. Long The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis Proc. R. Soc. London Ser. A 454 1998 903 995
    • (1998) Proc. R. Soc. London Ser. A , vol.454 , pp. 903-995
    • Huang, N.E.1    Shen, Z.2    Long, S.R.3
  • 10
    • 27744587461 scopus 로고    scopus 로고
    • The spectral kurtosis: A useful tool for characterizing non-stationary signals
    • J. Antoni The spectral kurtosis: a useful tool for characterizing non-stationary signals Mech. Syst. Signal Process 20 2 2006 282 307
    • (2006) Mech. Syst. Signal Process , vol.20 , Issue.2 , pp. 282-307
    • Antoni, J.1
  • 11
    • 27744553270 scopus 로고    scopus 로고
    • The spectral kurtosis: Application to the vibratory surveillance and diagnostics of rotating machines
    • J. Antoni The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines Mech. Syst. Signal Process 20 2 2006 308 331
    • (2006) Mech. Syst. Signal Process , vol.20 , Issue.2 , pp. 308-331
    • Antoni, J.1
  • 12
    • 33749508107 scopus 로고    scopus 로고
    • Fast computation of the kurtogram for the detection of transient faults
    • J. Antoni Fast computation of the kurtogram for the detection of transient faults Mech. Syst. Sig. Process. 21 1 2007 108 124
    • (2007) Mech. Syst. Sig. Process. , vol.21 , Issue.1 , pp. 108-124
    • Antoni, J.1
  • 13
    • 0041880035 scopus 로고    scopus 로고
    • Gearbox fault diagnosis using adaptive wavelet filter
    • J. Lin, and M. Zuo Gearbox fault diagnosis using adaptive wavelet filter Mech. Syst. Signal Process. 17 6 2003 1259 1269
    • (2003) Mech. Syst. Signal Process. , vol.17 , Issue.6 , pp. 1259-1269
    • Lin, J.1    Zuo, M.2
  • 14
    • 77949654912 scopus 로고    scopus 로고
    • Harmonic wavelet-based data filtering for enhanced machine defect identification
    • R. Yan, and R.X. Gao Harmonic wavelet-based data filtering for enhanced machine defect identification J. Sound Vib. 329 15 2010 3203 3217
    • (2010) J. Sound Vib. , vol.329 , Issue.15 , pp. 3203-3217
    • Yan, R.1    Gao, R.X.2
  • 15
    • 0346306460 scopus 로고    scopus 로고
    • Application of the wavelet transform in machine condition monitoring and fault diagnostics: A review with bibliography
    • Z. Peng, and F. Chu Application of the wavelet transform in machine condition monitoring and fault diagnostics: A review with bibliography Mech. Syst. Signal Process. 18 2 2004 199 221
    • (2004) Mech. Syst. Signal Process. , vol.18 , Issue.2 , pp. 199-221
    • Peng, Z.1    Chu, F.2
  • 16
    • 0033684356 scopus 로고    scopus 로고
    • Wavelet Packet Feature Extraction for Vibration Monitoring
    • G. Yen, and K. Lin Wavelet Packet Feature Extraction for Vibration Monitoring IEEE Trans. Ind. Electron. 47 3 2000 650 667
    • (2000) IEEE Trans. Ind. Electron. , vol.47 , Issue.3 , pp. 650-667
    • Yen, G.1    Lin, K.2
  • 17
    • 4344581685 scopus 로고    scopus 로고
    • Wavelet-based methods for the prognosis of mechanical and electrical failures in electric motors
    • W. Zanardelli, E. Strangas, and H Khalil Wavelet-based methods for the prognosis of mechanical and electrical failures in electric motors Mech. Syst. Signal Process. 19 2 2005 411 426
    • (2005) Mech. Syst. Signal Process. , vol.19 , Issue.2 , pp. 411-426
    • Zanardelli, W.1    Strangas, E.2    Khalil, H.3
  • 18
    • 33845328764 scopus 로고    scopus 로고
    • Bearing fault detection using wavelet packet transform of induction motor stator current
    • J. Zarei, and J. Poshtan Bearing fault detection using wavelet packet transform of induction motor stator current Tribol. Int. 40 5 2007 763 769
    • (2007) Tribol. Int. , vol.40 , Issue.5 , pp. 763-769
    • Zarei, J.1    Poshtan, J.2
  • 19
    • 84860218743 scopus 로고    scopus 로고
    • Novel indices for broken rotor bars fault diagnosis in induction motors using wavelet transform
    • B. Ebrahimi, J. Faiz, and S. Lotfi-Fard Novel indices for broken rotor bars fault diagnosis in induction motors using wavelet transform Mech. Syst. Signal Process. 30 2012 131 145
    • (2012) Mech. Syst. Signal Process. , vol.30 , pp. 131-145
    • Ebrahimi, B.1    Faiz, J.2    Lotfi-Fard, S.3
  • 20
    • 84887433963 scopus 로고    scopus 로고
    • Wavelets for fault diagnosis of rotary machines: A review with applications
    • R. Yan, R.X. Gao, and X. Chen Wavelets for fault diagnosis of rotary machines: a review with applications Signal Process. 96 2013 1 15
    • (2013) Signal Process. , vol.96 , pp. 1-15
    • Yan, R.1    Gao, R.X.2    Chen, X.3
  • 21
    • 79956155898 scopus 로고    scopus 로고
    • Bearing fault detection of induction motor using wavelet and Support Vector Machines (SVMs)
    • P. Konar, and P. Chattopadhyay Bearing fault detection of induction motor using wavelet and Support Vector Machines (SVMs) Appl. Soft Computing. 11 6 2011 4203 4211
    • (2011) Appl. Soft Computing. , vol.11 , Issue.6 , pp. 4203-4211
    • Konar, P.1    Chattopadhyay, P.2
  • 22
    • 33244469958 scopus 로고    scopus 로고
    • Detection of stator short circuits in VSI-fed brushless dc motors using wavelet transform
    • M.A. Awadallah, M.M. Morcos, S. Gopalakrishnan, and T.W. Nehl Detection of stator short circuits in VSI-fed brushless dc motors using wavelet transform IEEE Trans. Energy Convers. 21 1 2006 1 8
    • (2006) IEEE Trans. Energy Convers. , vol.21 , Issue.1 , pp. 1-8
    • Awadallah, M.A.1    Morcos, M.M.2    Gopalakrishnan, S.3    Nehl, T.W.4
  • 24
    • 79952454399 scopus 로고    scopus 로고
    • Condition monitoring of speed controlled induction motors using wavelet packets and discriminant analysis
    • D. Ece, and M. Başaran Condition monitoring of speed controlled induction motors using wavelet packets and discriminant analysis Expert Syst Appl. 38 7 2011 8079 8086
    • (2011) Expert Syst Appl. , vol.38 , Issue.7 , pp. 8079-8086
    • Ece, D.1    Başaran, M.2
  • 25
    • 2942525326 scopus 로고    scopus 로고
    • Bearing fault diagnosis based on wavelet transform and fuzzy inference
    • X. Lou, and K.A. Loparo Bearing fault diagnosis based on wavelet transform and fuzzy inference Mech. Syst. Signal Process. 18 5 2004 1077 1095
    • (2004) Mech. Syst. Signal Process. , vol.18 , Issue.5 , pp. 1077-1095
    • Lou, X.1    Loparo, K.A.2
  • 26
    • 34249716366 scopus 로고    scopus 로고
    • DWT analysis of numerical and experimental data for the diagnosis of dynamic eccentricities in induction motors
    • J. Antonino-Daviu, P. Jover, M. Riera, J. Roger, and A. Arkkio DWT analysis of numerical and experimental data for the diagnosis of dynamic eccentricities in induction motors Mech. Syst. Signal Process. 21 6 2007 2575 2589
    • (2007) Mech. Syst. Signal Process. , vol.21 , Issue.6 , pp. 2575-2589
    • Antonino-Daviu, J.1    Jover, P.2    Riera, M.3    Roger, J.4    Arkkio, A.5
  • 27
    • 67349234200 scopus 로고    scopus 로고
    • Detection of combined faults in induction machines with stator parallel branches through the DWT of the startup current
    • J. Antonino-Daviu, P. Jover, M. Riera, M. Pineda, and A. Arkkio Detection of combined faults in induction machines with stator parallel branches through the DWT of the startup current Mech. Syst. Signal Process. 23 7 2009 2336 2351
    • (2009) Mech. Syst. Signal Process. , vol.23 , Issue.7 , pp. 2336-2351
    • Antonino-Daviu, J.1    Jover, P.2    Riera, M.3    Pineda, M.4    Arkkio, A.5
  • 29
    • 84866598130 scopus 로고    scopus 로고
    • Early classification of bearing faults using morphological operators and fuzzy inference
    • S. Raj, and N. Murali Early classification of bearing faults using morphological operators and fuzzy inference IEEE Trans. Ind. Electron. 60 2 2013 567 574
    • (2013) IEEE Trans. Ind. Electron. , vol.60 , Issue.2 , pp. 567-574
    • Raj, S.1    Murali, N.2
  • 30
    • 84865646191 scopus 로고    scopus 로고
    • Fault feature extraction of gearbox by using overcomplete rational dilation discrete wavelet transform on signals measured from vibration sensors
    • B. Chen, Z. Zhang, C. Sun, B. Li, Y. Zi, and Z. He Fault feature extraction of gearbox by using overcomplete rational dilation discrete wavelet transform on signals measured from vibration sensors Mech. Syst. Signal Process. 33 2012 275 298
    • (2012) Mech. Syst. Signal Process. , vol.33 , pp. 275-298
    • Chen, B.1    Zhang, Z.2    Sun, C.3    Li, B.4    Zi, Y.5    He, Z.6
  • 32
    • 73749086464 scopus 로고    scopus 로고
    • Higher-density dyadic wavelet transform and its application
    • Y. Qin, B.P. Tang, and J.X. Wang Higher-density dyadic wavelet transform and its application Mech. Syst. Signal Process. 24 3 2010 823 834
    • (2010) Mech. Syst. Signal Process. , vol.24 , Issue.3 , pp. 823-834
    • Qin, Y.1    Tang, B.P.2    Wang, J.X.3
  • 33
    • 68249150714 scopus 로고    scopus 로고
    • Frequency-domain design of overcomplete rational-dilation wavelet transforms
    • I. Bayram, and I.W. Selesnick Frequency-domain design of overcomplete rational-dilation wavelet transforms IEEE Trans. Signal Process. 57 8 2009 2957 2972
    • (2009) IEEE Trans. Signal Process. , vol.57 , Issue.8 , pp. 2957-2972
    • Bayram, I.1    Selesnick, I.W.2
  • 34
    • 79960408153 scopus 로고    scopus 로고
    • Wavelet transform with tunable Q-factor
    • I.W. Selesnick Wavelet transform with tunable Q-factor IEEE Trans. Signal Process. 59 8 2011 3560 3575
    • (2011) IEEE Trans. Signal Process. , vol.59 , Issue.8 , pp. 3560-3575
    • Selesnick, I.W.1
  • 35
    • 80055046623 scopus 로고    scopus 로고
    • Sparse signal representations using the tunable Q-factor wavelet transform
    • (81381U-81381U-15)
    • I.W. Selesnick Sparse signal representations using the tunable Q-factor wavelet transform Proc. SPIE 2011 (81381U-81381U-15)
    • (2011) Proc. SPIE
    • Selesnick, I.W.1
  • 36
    • 84885572174 scopus 로고    scopus 로고
    • Sparsity-enabled signal decomposition using tunable Q-factor wavelet transform for fault feature extraction of gearbox
    • G. Cai, X. Chen, and Z. He Sparsity-enabled signal decomposition using tunable Q-factor wavelet transform for fault feature extraction of gearbox Mech. Syst. Signal Process. 2013
    • (2013) Mech. Syst. Signal Process.
    • Cai, G.1    Chen, X.2    He, Z.3
  • 37
    • 84881375460 scopus 로고    scopus 로고
    • Tunable Q-factor wavelet transform denoising with neighboring coefficients and its application to rotating machinery fault diagnosis
    • W. He, Y. Zi, B. Chen, S. Wang, and Z. He Tunable Q-factor wavelet transform denoising with neighboring coefficients and its application to rotating machinery fault diagnosis Sci. China Technol. Sci 56 8 2013 1956 1965
    • (2013) Sci. China Technol. Sci , vol.56 , Issue.8 , pp. 1956-1965
    • He, W.1    Zi, Y.2    Chen, B.3    Wang, S.4    He, Z.5
  • 38
    • 84876708997 scopus 로고    scopus 로고
    • A kurtosis-guided adaptive demodulation technique for bearing fault detection based on tunable-Q wavelet transform
    • J. Luo, J. Yu, and M. Ming A kurtosis-guided adaptive demodulation technique for bearing fault detection based on tunable-Q wavelet transform Meas. Sci. Technol. 24 5 2013
    • (2013) Meas. Sci. Technol. , vol.24 , Issue.5
    • Luo, J.1    Yu, J.2    Ming, M.3
  • 39
    • 84901695542 scopus 로고    scopus 로고
    • Feature extraction of rolling bearing's early weak fault based on EEMD and tunable Q-factor wavelet transform
    • H. Wang, J. Chen, and G. Dong Feature extraction of rolling bearing's early weak fault based on EEMD and tunable Q-factor wavelet transform Mech. Syst. Signal Process. 48 1 2014 103 119
    • (2014) Mech. Syst. Signal Process. , vol.48 , Issue.1 , pp. 103-119
    • Wang, H.1    Chen, J.2    Dong, G.3
  • 40
    • 47749084703 scopus 로고    scopus 로고
    • Research on iterated Hilbert transform and its application in mechanical faults diagnosis
    • Y. Qin, S. Qin, and Y. Mao Research on iterated Hilbert transform and its application in mechanical faults diagnosis Mech. Syst. Signal Process. 22 8 2008 1067 1980
    • (2008) Mech. Syst. Signal Process. , vol.22 , Issue.8 , pp. 1067-1980
    • Qin, Y.1    Qin, S.2    Mao, Y.3
  • 41
    • 63449106876 scopus 로고    scopus 로고
    • Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram
    • Y. Zhang, and R.B. Randall Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram Mech. Syst. Signal Process. 23 5 2009 1509 1517
    • (2009) Mech. Syst. Signal Process. , vol.23 , Issue.5 , pp. 1509-1517
    • Zhang, Y.1    Randall, R.B.2
  • 43
    • 63449086032 scopus 로고    scopus 로고
    • Adaptive multiwavelets via two-scale similarity transforms for rotating machinery fault diagnosis
    • J. Yuan, Z. He, and Y. Zi Adaptive multiwavelets via two-scale similarity transforms for rotating machinery fault diagnosis Mech. Syst. Signal Process. 23 5 2009 1490 1508
    • (2009) Mech. Syst. Signal Process. , vol.23 , Issue.5 , pp. 1490-1508
    • Yuan, J.1    He, Z.2    Zi, Y.3
  • 44
    • 44949230201 scopus 로고    scopus 로고
    • Investigation of engine fault diagnosis using discrete wavelet transform and neural network
    • J.D. Wu, and C.H. Liu Investigation of engine fault diagnosis using discrete wavelet transform and neural network Expert Syst. Appl. 35 3 2008 1200 1213
    • (2008) Expert Syst. Appl. , vol.35 , Issue.3 , pp. 1200-1213
    • Wu, J.D.1    Liu, C.H.2
  • 45
    • 63449084621 scopus 로고    scopus 로고
    • Use of autocorrelation of wavelet coefficients for fault diagnosis
    • J. Rafiee, and P.W. Tse Use of autocorrelation of wavelet coefficients for fault diagnosis Mech. Syst. Signal Process. 23 5 2009 1554 1572
    • (2009) Mech. Syst. Signal Process. , vol.23 , Issue.5 , pp. 1554-1572
    • Rafiee, J.1    Tse, P.W.2
  • 46
    • 77349127319 scopus 로고    scopus 로고
    • Incipient gear box fault diagnosis using discrete wavelet transform (DWT) for feature extraction and classification using artificial neural network (ANN)
    • N. Saravanan, and K.I. Ramachandran Incipient gear box fault diagnosis using discrete wavelet transform (DWT) for feature extraction and classification using artificial neural network (ANN) Expert Syst. Appl. 37 6 2010 4168 4181
    • (2010) Expert Syst. Appl. , vol.37 , Issue.6 , pp. 4168-4181
    • Saravanan, N.1    Ramachandran, K.I.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.