메뉴 건너뛰기




Volumn 80, Issue , 2016, Pages 392-413

Time–frequency manifold sparse reconstruction: A novel method for bearing fault feature extraction

Author keywords

Bearing fault diagnosis; Orthogonal matching pursuit; Signal reconstruction; Sparse decomposition; Time frequency manifold

Indexed keywords

EXTRACTION; FAULT DETECTION; FEATURE EXTRACTION; IMAGE DENOISING; IMAGE RECONSTRUCTION; INVERSE PROBLEMS; PHASE SPACE METHODS; SIGNAL ANALYSIS; SIGNAL PROCESSING; SIGNAL RECONSTRUCTION;

EID: 84964624225     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2016.04.024     Document Type: Article
Times cited : (74)

References (41)
  • 1
    • 33646534620 scopus 로고    scopus 로고
    • A review on machinery diagnostics and prognostics implementing condition-based maintenance
    • [1] Jardine, A.K.S., Lin, D., Banjevic, D., A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mech. Syst. Signal Process. 20:7 (2006), 1483–1510.
    • (2006) Mech. Syst. Signal Process. , vol.20 , Issue.7 , pp. 1483-1510
    • Jardine, A.K.S.1    Lin, D.2    Banjevic, D.3
  • 2
    • 0033336360 scopus 로고    scopus 로고
    • A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings
    • [2] Tandon, N., Choudhury, A., A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribol. Int. 32:8 (1999), 469–480.
    • (1999) Tribol. Int. , vol.32 , Issue.8 , pp. 469-480
    • Tandon, N.1    Choudhury, A.2
  • 3
    • 33644547646 scopus 로고    scopus 로고
    • Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics
    • [3] Qiu, H., Lee, J., Lin, J., Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics. J. Sound Vib. 289 (2006), 1066–1090.
    • (2006) J. Sound Vib. , vol.289 , pp. 1066-1090
    • Qiu, H.1    Lee, J.2    Lin, J.3
  • 4
    • 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
    • [4] Žvokelj, M., Zupan, S., Prebil, I., Non-linear multivariate and multiscale monitoring and signal denoising strategy using kernel principal component analysis combined with ensemble empirical mode decomposition method. Mech. Syst. Signal Process. 25:7 (2011), 2631–2653.
    • (2011) Mech. Syst. Signal Process. , vol.25 , Issue.7 , pp. 2631-2653
    • Žvokelj, M.1    Zupan, S.2    Prebil, I.3
  • 5
    • 78349308990 scopus 로고    scopus 로고
    • Multiwavelet denoising with improved neighboring coefficients for application on rolling bearing fault diagnosis
    • [5] Wang, X., Zi, Y., He, Z., Multiwavelet denoising with improved neighboring coefficients for application on rolling bearing fault diagnosis. Mech. Syst. Signal Process. 25:1 (2011), 285–304.
    • (2011) Mech. Syst. Signal Process. , vol.25 , Issue.1 , pp. 285-304
    • Wang, X.1    Zi, Y.2    He, Z.3
  • 6
    • 79952297752 scopus 로고    scopus 로고
    • The synchronous (time domain) average revisited
    • [6] Braun, S., The synchronous (time domain) average revisited. Mech. Syst. Signal Process. 25:4 (2011), 1087–1102.
    • (2011) Mech. Syst. Signal Process. , vol.25 , Issue.4 , pp. 1087-1102
    • Braun, S.1
  • 7
    • 33749508107 scopus 로고    scopus 로고
    • Fast computation of the kurtogram for the detection of transient faults
    • [7] Antoni, J., Fast computation of the kurtogram for the detection of transient faults. Mech. Syst. Signal Process. 21:1 (2007), 108–124.
    • (2007) Mech. Syst. Signal Process. , vol.21 , Issue.1 , pp. 108-124
    • Antoni, J.1
  • 8
    • 84919933755 scopus 로고    scopus 로고
    • Vibration spectrum imaging: a novel bearing fault classification approach
    • [8] Amar, M., Gondal, I., Wilson, C., Vibration spectrum imaging: a novel bearing fault classification approach. IEEE Trans. Ind. Electron. 62 (2015), 494–502.
    • (2015) IEEE Trans. Ind. Electron. , vol.62 , pp. 494-502
    • Amar, M.1    Gondal, I.2    Wilson, C.3
  • 9
    • 33646519024 scopus 로고    scopus 로고
    • A roller bearing fault diagnosis method based on EMD energy entropy and ANN
    • [9] Yang, Y., Yu, D.J., Cheng, J.S., A roller bearing fault diagnosis method based on EMD energy entropy and ANN. J. Sound Vib. 294 (2006), 269–277.
    • (2006) J. Sound Vib. , vol.294 , pp. 269-277
    • Yang, Y.1    Yu, D.J.2    Cheng, J.S.3
  • 10
    • 70349272168 scopus 로고    scopus 로고
    • Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform
    • [10] Wang, Y., He, Z., Zi, Y., Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform. Mech. Syst. Signal Process. 24:1 (2010), 119–137.
    • (2010) Mech. Syst. Signal Process. , vol.24 , Issue.1 , pp. 119-137
    • Wang, Y.1    He, Z.2    Zi, Y.3
  • 11
    • 57749205586 scopus 로고    scopus 로고
    • Time–frequency analysis for efficient fault diagnosis and failure prognosis for interior permanent-magnet AC motors
    • [11] Strangas, E.G., Aviyente, S., Zaidi, S.S.H., Time–frequency analysis for efficient fault diagnosis and failure prognosis for interior permanent-magnet AC motors. IEEE Trans. Ind. Electron. 55:12 (2008), 4191–4199.
    • (2008) IEEE Trans. Ind. Electron. , vol.55 , Issue.12 , pp. 4191-4199
    • Strangas, E.G.1    Aviyente, S.2    Zaidi, S.S.H.3
  • 12
    • 84862825547 scopus 로고    scopus 로고
    • Time-frequency manifold as a signature for machine health diagnosis
    • [12] He, Q., Liu, Y., Long, Q., Wang, J., Time-frequency manifold as a signature for machine health diagnosis. IEEE Trans. Instrum. Meas. 61:5 (2012), 1218–1230.
    • (2012) IEEE Trans. Instrum. Meas. , vol.61 , Issue.5 , pp. 1218-1230
    • He, Q.1    Liu, Y.2    Long, Q.3    Wang, J.4
  • 13
    • 84891419450 scopus 로고    scopus 로고
    • Vibration sensor data denoising using a time–frequency manifold for machinery fault diagnosis
    • [13] He, Q., Wang, X., Zhou, Q., Vibration sensor data denoising using a time–frequency manifold for machinery fault diagnosis. Sensors 14:1 (2013), 382–402.
    • (2013) Sensors , vol.14 , Issue.1 , pp. 382-402
    • He, Q.1    Wang, X.2    Zhou, Q.3
  • 14
    • 84875473802 scopus 로고    scopus 로고
    • Time–frequency manifold correlation matching for periodic fault identification in rotating machines
    • [14] He, Q., Wang, X., Time–frequency manifold correlation matching for periodic fault identification in rotating machines. J. Sound Vib. 332:10 (2013), 2611–2626.
    • (2013) J. Sound Vib. , vol.332 , Issue.10 , pp. 2611-2626
    • He, Q.1    Wang, X.2
  • 15
    • 84894107471 scopus 로고    scopus 로고
    • Matching pursuit of an adaptive impulse dictionary for bearing fault diagnosis
    • [15] Cui, L., Wang, J., Lee, S., Matching pursuit of an adaptive impulse dictionary for bearing fault diagnosis. J. Sound Vib. 333:10 (2014), 2840–2862.
    • (2014) J. Sound Vib. , vol.333 , Issue.10 , pp. 2840-2862
    • Cui, L.1    Wang, J.2    Lee, S.3
  • 16
    • 84938702940 scopus 로고    scopus 로고
    • Machinery vibration signal denoising based on learned dictionary and sparse representation
    • [16] Guo, L., Gao, H., Li, J., Huang, H., Zhang, X., Machinery vibration signal denoising based on learned dictionary and sparse representation. J. Phys.: Conf. Ser., 628, 2015, 012124.
    • (2015) J. Phys.: Conf. Ser. , vol.628 , pp. 012124
    • Guo, L.1    Gao, H.2    Li, J.3    Huang, H.4    Zhang, X.5
  • 17
    • 4344678288 scopus 로고    scopus 로고
    • Fault diagnosis of rolling element bearings using basis pursuit
    • [17] Yang, H., Mathew, J., Ma, L., Fault diagnosis of rolling element bearings using basis pursuit. Mech. Syst. Signal Process. 19:2 (2005), 341–356.
    • (2005) Mech. Syst. Signal Process. , vol.19 , Issue.2 , pp. 341-356
    • Yang, H.1    Mathew, J.2    Ma, L.3
  • 18
    • 0031234350 scopus 로고    scopus 로고
    • Time–frequency analysis in gearbox fault detection using the Wigner–Ville distribution and pattern recognition
    • [18] Staszewski, W., Worden, K., Tomlinson, G., Time–frequency analysis in gearbox fault detection using the Wigner–Ville distribution and pattern recognition. Mech. Syst. Signal Process. 11:5 (1997), 673–692.
    • (1997) Mech. Syst. Signal Process. , vol.11 , Issue.5 , pp. 673-692
    • Staszewski, W.1    Worden, K.2    Tomlinson, G.3
  • 19
    • 0003456805 scopus 로고    scopus 로고
    • A Wavelet Tour of Signal Processing
    • 2nd ed. China Machine Press Beijing, China
    • [19] Mallat, S., A Wavelet Tour of Signal Processing. 2nd ed., 2003, China Machine Press, Beijing, China.
    • (2003)
    • Mallat, S.1
  • 20
    • 0029291966 scopus 로고
    • Sparse approximate solutions to linear systems
    • [20] Natarajan, B.K., Sparse approximate solutions to linear systems. SIAM J. Comput. 24:2 (1995), 227–234.
    • (1995) SIAM J. Comput. , vol.24 , Issue.2 , pp. 227-234
    • Natarajan, B.K.1
  • 21
    • 84955701960 scopus 로고    scopus 로고
    • Sparsity-based algorithm for detecting faults in rotating machines
    • [21] He, W., Ding, Y., Zi, Y., Selesnick, I.W., Sparsity-based algorithm for detecting faults in rotating machines. Mech. Syst. Signal Process. 72 (2016), 46–64.
    • (2016) Mech. Syst. Signal Process. , vol.72 , pp. 46-64
    • He, W.1    Ding, Y.2    Zi, Y.3    Selesnick, I.W.4
  • 22
    • 84898081265 scopus 로고    scopus 로고
    • Sparse representation based latent components analysis for machinery weak fault detection
    • [22] Tang, H., Chen, J., Dong, G., Sparse representation based latent components analysis for machinery weak fault detection. Mech. Syst. Signal Process. 46:2 (2014), 373–388.
    • (2014) Mech. Syst. Signal Process. , vol.46 , Issue.2 , pp. 373-388
    • Tang, H.1    Chen, J.2    Dong, G.3
  • 23
    • 84919839730 scopus 로고    scopus 로고
    • Sparse representation of transients in wavelet basis and its application in gearbox fault feature extraction
    • [23] Fan, W., Cai, G.G., Zhu, Z.K., Shen, C.Q., Huang, W.G., Shang, L., Sparse representation of transients in wavelet basis and its application in gearbox fault feature extraction. Mech. Syst. Signal Process. 56 (2015), 230–245.
    • (2015) Mech. Syst. Signal Process. , vol.56 , pp. 230-245
    • Fan, W.1    Cai, G.G.2    Zhu, Z.K.3    Shen, C.Q.4    Huang, W.G.5    Shang, L.6
  • 24
    • 84943364103 scopus 로고    scopus 로고
    • Quantitative fault analysis of roller bearings based on a novel matching pursuit method with a new step-impulse dictionary
    • [24] Cui, L., Wu, N., Ma, C., Wang, H., Quantitative fault analysis of roller bearings based on a novel matching pursuit method with a new step-impulse dictionary. Mech. Syst. Signal Process. 68 (2016), 34–43.
    • (2016) Mech. Syst. Signal Process. , vol.68 , pp. 34-43
    • Cui, L.1    Wu, N.2    Ma, C.3    Wang, H.4
  • 25
    • 84915785643 scopus 로고    scopus 로고
    • Transient signal analysis based on Levenberg–Marquardt method for fault feature extraction of rotating machines
    • [25] Wang, S.B., Cai, G.G., Zhu, Z.K., Huang, W.G., Zhang, X.W., Transient signal analysis based on Levenberg–Marquardt method for fault feature extraction of rotating machines. Mech. Syst. Signal Process. 54 (2015), 16–40.
    • (2015) Mech. Syst. Signal Process. , vol.54 , pp. 16-40
    • Wang, S.B.1    Cai, G.G.2    Zhu, Z.K.3    Huang, W.G.4    Zhang, X.W.5
  • 26
    • 84887863490 scopus 로고    scopus 로고
    • A Doppler transient model based on the Laplace wavelet and spectrum correlation assessment for locomotive bearing fault diagnosis
    • [26] Shen, C., Liu, F., Wang, D., Zhang, A., Kong, F., Tse, P.W., A Doppler transient model based on the Laplace wavelet and spectrum correlation assessment for locomotive bearing fault diagnosis. Sensors 13:11 (2013), 15726–15746.
    • (2013) Sensors , vol.13 , Issue.11 , pp. 15726-15746
    • Shen, C.1    Liu, F.2    Wang, D.3    Zhang, A.4    Kong, F.5    Tse, P.W.6
  • 27
    • 84907200827 scopus 로고    scopus 로고
    • Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm
    • [27] Cui, L., Wu, N., Wang, W., Kang, C., Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm. Sensors 14:9 (2014), 16715–16739.
    • (2014) Sensors , vol.14 , Issue.9 , pp. 16715-16739
    • Cui, L.1    Wu, N.2    Wang, W.3    Kang, C.4
  • 28
    • 84887486721 scopus 로고    scopus 로고
    • Compressed sensing based on dictionary learning for extracting impulse components
    • [28] Chen, X., Du, Z., Li, J., Li, X., Zhang, H., Compressed sensing based on dictionary learning for extracting impulse components. Signal Process. 96 (2014), 94–109.
    • (2014) Signal Process. , vol.96 , pp. 94-109
    • Chen, X.1    Du, Z.2    Li, J.3    Li, X.4    Zhang, H.5
  • 29
    • 0027842081 scopus 로고
    • Matching pursuit with time–frequency dictionaries
    • [29] Mallat, S., Zhang, Z., Matching pursuit with time–frequency dictionaries. IEEE Trans. Signal Process. 41:12 (1993), 3397–3415.
    • (1993) IEEE Trans. Signal Process. , vol.41 , Issue.12 , pp. 3397-3415
    • Mallat, S.1    Zhang, Z.2
  • 31
    • 33751379736 scopus 로고    scopus 로고
    • Image denoising via sparse and redundant representations over learned dictionaries
    • [31] Elad, M., Aharon., M., Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans. Image Process. 15:12 (2006), 3736–3745.
    • (2006) IEEE Trans. Image Process. , vol.15 , Issue.12 , pp. 3736-3745
    • Elad, M.1    Aharon, M.2
  • 32
    • 84890924628 scopus 로고    scopus 로고
    • Self-learning based image decomposition with applications to single image denoising
    • [32] Huang, D., Kang, L., Wang, Y., Lin, C.W., Self-learning based image decomposition with applications to single image denoising. IEEE Trans. Multimed. 16:1 (2014), 83–93.
    • (2014) IEEE Trans. Multimed. , vol.16 , Issue.1 , pp. 83-93
    • Huang, D.1    Kang, L.2    Wang, Y.3    Lin, C.W.4
  • 34
    • 14544307975 scopus 로고    scopus 로고
    • Principal manifolds and nonlinear dimensionality reduction via tangent space alignment
    • [34] Zhang, Z., Zha, H., Principal manifolds and nonlinear dimensionality reduction via tangent space alignment. SIAM J. Sci. Comput. 26:1 (2005), 313–338.
    • (2005) SIAM J. Sci. Comput. , vol.26 , Issue.1 , pp. 313-338
    • Zhang, Z.1    Zha, H.2
  • 35
    • 0031257169 scopus 로고    scopus 로고
    • Characterization of signals by the ridges of their wavelet transforms
    • [35] Carmona, R.A., Hwang, W.L., Torresani, B., Characterization of signals by the ridges of their wavelet transforms. IEEE Trans. Signal Process. 45 (1997), 2586–2590.
    • (1997) IEEE Trans. Signal Process. , vol.45 , pp. 2586-2590
    • Carmona, R.A.1    Hwang, W.L.2    Torresani, B.3
  • 36
    • 1142267431 scopus 로고    scopus 로고
    • Moire´ interferogram phase extraction: a ridge detection algorithm for continuous wavelet transforms
    • [36] Liu, H., Cartwright, A.N., Basaran, C., Moire´ interferogram phase extraction: a ridge detection algorithm for continuous wavelet transforms. Appl. Opt. 43 (2004), 850–857.
    • (2004) Appl. Opt. , vol.43 , pp. 850-857
    • Liu, H.1    Cartwright, A.N.2    Basaran, C.3
  • 37
    • 84881310676 scopus 로고    scopus 로고
    • Automatic fault diagnosis of rotating machines by time-scale manifold ridge analysis
    • [37] Wang, J., He, Q., Kong, F., Automatic fault diagnosis of rotating machines by time-scale manifold ridge analysis. Mech. Syst. Signal Process. 40:1 (2013), 237–256.
    • (2013) Mech. Syst. Signal Process. , vol.40 , Issue.1 , pp. 237-256
    • Wang, J.1    He, Q.2    Kong, F.3
  • 39
    • 84961170009 scopus 로고    scopus 로고
    • The infogram: entropic evidence of the signature of repetitive transients
    • [39] Antoni, J., The infogram: entropic evidence of the signature of repetitive transients. Mech. Syst. Signal Process. 74 (2016), 73–94.
    • (2016) Mech. Syst. Signal Process. , vol.74 , pp. 73-94
    • Antoni, J.1
  • 40
    • 77953264793 scopus 로고    scopus 로고
    • Available online, (accessed on 15.09.15)
    • [40] Bearing Data Center, Available online: (http://csegroups.case.edu/bearingdatacenter/home) (accessed on 15.09.15).
    • Bearing Data Center
  • 41
    • 79251535298 scopus 로고    scopus 로고
    • Machine fault signature analysis by midpoint-based empirical mode decomposition
    • [41] He, Q., Liu, Y., Kong, F., Machine fault signature analysis by midpoint-based empirical mode decomposition. Meas. Sci. Technol., 22(1), 2011, 015702.
    • (2011) Meas. Sci. Technol. , vol.22 , Issue.1 , pp. 015702
    • He, Q.1    Liu, Y.2    Kong, F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.