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Volumn 41, Issue 1-2, 2013, Pages 510-525

Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition

Author keywords

Anomaly detection; Bearings; Empirical Mode Decomposition; Ensemble detector; Hilbert Huang transform; One class classification

Indexed keywords

ANOMALY DETECTION; BEARING FAULT DETECTION; EMPIRICAL MODE DECOMPOSITION; HILBERT HUANG TRANSFORMS; LOADING CONDITION; NORMAL CONDITION; ONE-CLASS CLASSIFICATION; SIGNALLING SYSTEMS;

EID: 84885579397     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2013.02.020     Document Type: Article
Times cited : (156)

References (59)
  • 1
    • 78751666101 scopus 로고    scopus 로고
    • A survey of condition monitoring and protection methods for medium voltage induction motors
    • P. Zhang, Y. Du, T.G. Habetler, and B. Lu A survey of condition monitoring and protection methods for medium voltage induction motors IEEE Trans. Energy Convers. 47 1 2011 34 46
    • (2011) IEEE Trans. Energy Convers. , vol.47 , Issue.1 , pp. 34-46
    • Zhang, P.1    Du, Y.2    Habetler, T.G.3    Lu, B.4
  • 2
    • 0036554724 scopus 로고    scopus 로고
    • Differential diagnosis of gear and bearing faults
    • J. Antoni, and R.B. Randall Differential diagnosis of gear and bearing faults J. Vib. Acoust. 124 2 2002 165 171
    • (2002) J. Vib. Acoust. , vol.124 , Issue.2 , pp. 165-171
    • Antoni, J.1    Randall, R.B.2
  • 3
    • 84885637208 scopus 로고    scopus 로고
    • Utilising the wavelet transform in condition-based maintenance: A review with applications, advances in wavelet theory and their applications in engineering
    • last accessed 08.29
    • T. Loutas, and V. Kostopoulos Utilising the wavelet transform in condition-based maintenance: a review with applications, advances in wavelet theory and their applications in engineering Phys. Technol. 2012 last accessed 08.29 http://www.intechopen.com/books/advances-in-wavelet-theory-and-their- applications-in-engineering-physics-and-technology/utilising-the-wavelet- transform-in-condition-based-maintenancea
    • (2012) Phys. Technol.
    • Loutas, T.1    Kostopoulos, V.2
  • 4
    • 34548035641 scopus 로고    scopus 로고
    • Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine
    • S. Abbasion, A. Rafsanjani, A. Farshidianfar, and N. Irani Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine Mech. Syst. Sig. Process. 21 7 2007 2933 2945
    • (2007) Mech. Syst. Sig. Process. , vol.21 , Issue.7 , pp. 2933-2945
    • Abbasion, S.1    Rafsanjani, A.2    Farshidianfar, A.3    Irani, N.4
  • 5
    • 33947210318 scopus 로고    scopus 로고
    • Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics
    • H. Ocak, K.A. Loparo, and F.M. Discenzo Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: a method for bearing prognostics J. Sound Vib. 302 4-5 2007 951 961
    • (2007) J. Sound Vib. , vol.302 , Issue.45 , pp. 951-961
    • Ocak, H.1    Loparo, K.A.2    Discenzo, F.M.3
  • 7
    • 64049098473 scopus 로고    scopus 로고
    • Application of an intelligent classification method to mechanical fault diagnosis
    • Y. Lei, Z. He, and Y. Zi Application of an intelligent classification method to mechanical fault diagnosis Expert Syst. Appl. 36 6 2009 9941 9948
    • (2009) Expert Syst. Appl. , vol.36 , Issue.6 , pp. 9941-9948
    • Lei, Y.1    He, Z.2    Zi, Y.3
  • 8
    • 58949088453 scopus 로고    scopus 로고
    • Application of the EEMD method to rotor fault diagnosis of rotating machinery
    • Y. Lei, Z. He, and Y. Zi Application of the EEMD method to rotor fault diagnosis of rotating machinery Mech. Syst. Sig. Process. 23 2009 1327 1338
    • (2009) Mech. Syst. Sig. Process. , vol.23 , pp. 1327-1338
    • Lei, Y.1    He, Z.2    Zi, Y.3
  • 9
    • 4344660716 scopus 로고    scopus 로고
    • Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings
    • D. Yu, J. Cheng, and Y. Yang Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings Mech. Syst. Sig. Process. 19 2005 259 270
    • (2005) Mech. Syst. Sig. Process. , vol.19 , pp. 259-270
    • Yu, D.1    Cheng, J.2    Yang, Y.3
  • 10
    • 33645321115 scopus 로고    scopus 로고
    • Empirical mode decomposition based time-frequency analysis for the effective detection of tool breakage
    • Y. Peng Empirical mode decomposition based time-frequency analysis for the effective detection of tool breakage J. Manuf. Sci. Eng. Trans. ASME 128 2006 154 166
    • (2006) J. Manuf. Sci. Eng. Trans. ASME , vol.128 , pp. 154-166
    • Peng, Y.1
  • 12
    • 77949491282 scopus 로고    scopus 로고
    • Multivariate and multiscale monitoring of large-size low-speed bearings using ensemble empirical mode decomposition method combined with principal component analysis
    • M. Žvokelj, S. Zupan, and I. Prebil Multivariate and multiscale monitoring of large-size low-speed bearings using ensemble empirical mode decomposition method combined with principal component analysis Mech. Syst. Sig. Process. 24 4 2010 1049 1067
    • (2010) Mech. Syst. Sig. Process. , vol.24 , Issue.4 , pp. 1049-1067
    • Žvokelj, M.1    Zupan, S.2    Prebil, I.3
  • 13
    • 79960045420 scopus 로고    scopus 로고
    • Non-linear multivariate and multiscale monitoring and signal denoising strategy using kernel principal component analysis combined with ensemble empirical mode decomposition method
    • M. Žvokelj, S. Zupan, and I. Prebil Non-linear multivariate and multiscale monitoring and signal denoising strategy using kernel principal component analysis combined with ensemble empirical mode decomposition method Mech. Syst. Sig. Process. 25 7 2011 2631 2653
    • (2011) Mech. Syst. Sig. Process. , vol.25 , Issue.7 , pp. 2631-2653
    • Žvokelj, M.1    Zupan, S.2    Prebil, I.3
  • 14
    • 84870855305 scopus 로고    scopus 로고
    • Rotor fault diagnosis in asynchronous machines via analysis of the start-up transient into intrinsic mode functions
    • G. Georgoulas, I. Tsoumas, E. Mitronikas, C.D. Stylios, and A. Safacas Rotor fault diagnosis in asynchronous machines via analysis of the start-up transient into intrinsic mode functions Proc. ICEM 2012
    • (2012) Proc. ICEM
    • Georgoulas, G.1    Tsoumas, I.2    Mitronikas, E.3    Stylios, C.D.4    Safacas, A.5
  • 16
    • 0033489494 scopus 로고    scopus 로고
    • A new view of nonlinear water waves: The Hilbert Spectrum
    • N.E. Huang, Z. Shen, and S.R. Long A new view of nonlinear water waves: the Hilbert Spectrum Annu. Rev. Fluid Mech. 31 1999 417 457
    • (1999) Annu. Rev. Fluid Mech. , vol.31 , pp. 417-457
    • Huang, N.E.1    Shen, Z.2    Long, S.R.3
  • 18
    • 2542525254 scopus 로고    scopus 로고
    • A study of the characteristics of white noise using the empirical mode decomposition method
    • Z. Wu, and N.E. Huang A study of the characteristics of white noise using the empirical mode decomposition method Proc. R. Soc. London, Ser. A: Math., Phys. Eng. Sci. 460 2046 2004 1597 1611
    • (2004) Proc. R. Soc. London, Ser. A: Math., Phys. Eng. Sci. , vol.460 , Issue.2046 , pp. 1597-1611
    • Wu, Z.1    Huang, N.E.2
  • 20
    • 63749099834 scopus 로고    scopus 로고
    • Signal feature extraction based on an improved EMD method
    • L. Li, and H.B. Ji Signal feature extraction based on an improved EMD method Measurement 42 2009 796 803
    • (2009) Measurement , vol.42 , pp. 796-803
    • Li, L.1    Ji, H.B.2
  • 22
    • 31044443577 scopus 로고    scopus 로고
    • Research on intrinsic mode function (IMF) criterion in EMD method
    • C. Junsheng, Y. Dejie, and Y. Yu Research on intrinsic mode function (IMF) criterion in EMD method Mech. Syst. Sig. Process. 20 2006 817 824
    • (2006) Mech. Syst. Sig. Process. , vol.20 , pp. 817-824
    • Junsheng, C.1    Dejie, Y.2    Yu, Y.3
  • 24
    • 84885658444 scopus 로고    scopus 로고
    • (last accessed 08.29.2012)
    • The EMD toolbox http://perso.ens-lyon.fr/patrick.flandrin/emd.htmla (last accessed 08.29.2012).
    • The EMD Toolbox
  • 26
    • 0142063407 scopus 로고    scopus 로고
    • Novelty detection: A review-part 1: Statistical approaches
    • M. Markou, and S. Singh Novelty detection: a review-part 1: statistical approaches Sig. Process. 83 12 2003 2481 2497
    • (2003) Sig. Process. , vol.83 , Issue.12 , pp. 2481-2497
    • Markou, M.1    Singh, S.2
  • 27
    • 0142126712 scopus 로고    scopus 로고
    • Novelty detection: A review-part 2: Neural network based approaches
    • M. Markou, and S. Singh Novelty detection: a review-part 2: neural network based approaches Sig. Process. 83 12 2003 2499 2521
    • (2003) Sig. Process. , vol.83 , Issue.12 , pp. 2499-2521
    • Markou, M.1    Singh, S.2
  • 32
    • 75149176174 scopus 로고    scopus 로고
    • Ensembled-based classifiers
    • L. Rokach Ensembled-based classifiers Arttificial Intell. Rev. 33 2010 1 39
    • (2010) Arttificial Intell. Rev. , vol.33 , pp. 1-39
    • Rokach, L.1
  • 35
    • 69449097857 scopus 로고    scopus 로고
    • Taxonomy for characterizing ensemble methods in classification tasks: A review and annotated bibliography
    • L. Rokach Taxonomy for characterizing ensemble methods in classification tasks: a review and annotated bibliography Comput. Stat. Data Anal. 53 12 2009 4046 4072
    • (2009) Comput. Stat. Data Anal. , vol.53 , Issue.12 , pp. 4046-4072
    • Rokach, L.1
  • 36
    • 33748611921 scopus 로고    scopus 로고
    • Ensemble based systems in decision making
    • R. Polikar Ensemble based systems in decision making IEEE Circuits Syst. Mag. 6 3 2006 21 45
    • (2006) IEEE Circuits Syst. Mag. , vol.6 , Issue.3 , pp. 21-45
    • Polikar, R.1
  • 38
    • 84885649603 scopus 로고    scopus 로고
    • (last accessed 08.29.2012)
    • The Data Description Toolbox, http://homepage.tudelft.nl/n9d04/dd-tools. htmla (last accessed 08.29.2012).
    • The Data Description Toolbox
  • 45
    • 84870460298 scopus 로고    scopus 로고
    • Case Western Reserve University (last accessed 08.29.2012)
    • K.A. Loparo, Bearing Vibration Dataset, Case Western Reserve University http://csegroups.case.edu/bearingdatacenter/pages/welcome-case-western-reserve- university-bearing-data-center-websitea (last accessed 08.29.2012).
    • Bearing Vibration Dataset
    • Loparo, K.A.1
  • 46
    • 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. Sig. Process. 18 5 2004 1077 1095
    • (2004) Mech. Syst. Sig. Process. , vol.18 , Issue.5 , pp. 1077-1095
    • Lou, X.1    Loparo, K.A.2
  • 50
  • 51
    • 32544454675 scopus 로고    scopus 로고
    • Experimental comparison of one-class classifiers for online signature verification
    • L. Nanni Experimental comparison of one-class classifiers for online signature verification Neurocomputing 69 7 2006 869 873
    • (2006) Neurocomputing , vol.69 , Issue.7 , pp. 869-873
    • Nanni, L.1
  • 52
    • 80052979522 scopus 로고    scopus 로고
    • Pruned random subspace method for one-class classifiers
    • V. Cheplygina, and D.M.J. Tax Pruned random subspace method for one-class classifiers Lect. Notes Comput. Sci. 6713 2011 96 105
    • (2011) Lect. Notes Comput. Sci. , vol.6713 , pp. 96-105
    • Cheplygina, V.1    Tax, D.M.J.2
  • 53
  • 54
    • 0242515926 scopus 로고    scopus 로고
    • Attribute bagging: Improving accuracy of classifier ensembles by using random feature subsets
    • R. Bryll, R. Gutierrez-Osuna, and F. Quek Attribute bagging: improving accuracy of classifier ensembles by using random feature subsets Pattern Recognit. 36 2003 1291 1302
    • (2003) Pattern Recognit. , vol.36 , pp. 1291-1302
    • Bryll, R.1    Gutierrez-Osuna, R.2    Quek, F.3
  • 59
    • 84942213019 scopus 로고
    • The best two independent measurements are not the two best
    • T.M. Cover The best two independent measurements are not the two best IEEE Trans. Syst. Man Cybern. 1 1974 116 117
    • (1974) IEEE Trans. Syst. Man Cybern. , vol.1 , pp. 116-117
    • Cover, T.M.1


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