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Volumn 16, Issue 2, 2014, Pages 761-769

Intelligent fault classification of rolling bearings using neural network and discrete wavelet transform

Author keywords

Discrete wavelet transform; Fault diagnosis; Neural network; Nondestructive tests

Indexed keywords

BEARINGS (MACHINE PARTS); DISCRETE WAVELET TRANSFORMS; FAILURE ANALYSIS; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; WAVELET ANALYSIS;

EID: 84904127824     PISSN: 13928716     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (11)

References (13)
  • 1
    • 0348197187 scopus 로고    scopus 로고
    • Classification of gear faults using cumulants and the radial basis function network
    • Wuxing L., Tse Peter W., Guicai Z., Tielin S. Classification of gear faults using cumulants and the radial basis function network. Mechanical Systems and Signal Processing, Vol. 18, 2004, p. 381-389.
    • (2004) Mechanical Systems and Signal Processing , vol.18 , pp. 381-389
    • Wuxing, L.1    Tse, P.W.2    Guicai, Z.3    Tielin, S.4
  • 2
    • 2942525326 scopus 로고    scopus 로고
    • Bearing fault diagnosis based on wavelet transform and fuzzy inference
    • Lou X., Loparo K. A. Bearing fault diagnosis based on wavelet transform and fuzzy inference. Mechanical Systems and Signal Processing, Vol. 18, 2004, p. 1077-1095.
    • (2004) Mechanical Systems and Signal Processing , vol.18 , pp. 1077-1095
    • Lou, X.1    Loparo, K.A.2
  • 3
    • 0347526092 scopus 로고    scopus 로고
    • Artificial neural network and support vector machines with genetic algorithm for bearing fault detection
    • Samanta B., Al-Balushi K. R., Al-Araimi S. A. Artificial neural network and support vector machines with genetic algorithm for bearing fault detection. Engineering Application of Artificial Intelligence, Vol. 16, 2003, p. 657-665.
    • (2003) Engineering Application of Artificial Intelligence , vol.16 , pp. 657-665
    • Samanta, B.1    Al-Balushi, K.R.2    Al-Araimi, S.A.3
  • 4
    • 2942561579 scopus 로고    scopus 로고
    • Third-order spectral techniques for the diagnosis of motor bearing condition using artificial neural network
    • Yang D. M., Stronach A. F., MaCconnell P., Penman J. Third-order spectral techniques for the diagnosis of motor bearing condition using artificial neural network. Mechanical Systems and Signal Processing, Vol. 16, Issue 2-3, 2002, p. 391-411.
    • (2002) Mechanical Systems and Signal Processing , vol.16 , Issue.2-3 , pp. 391-411
    • Yang, D.M.1    Stronach, A.F.2    MaCconnell, P.3    Penman, J.4
  • 6
    • 0346306460 scopus 로고    scopus 로고
    • Application of the wavelet transform in machine condition monitoring and fault diagnostics: A review with bibliography
    • Peng Z. K., Chu F. L. Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography. Mechanical Systems and Signal Processing, Vol. 18, 2004, p. 199-221.
    • (2004) Mechanical Systems and Signal Processing , vol.18 , pp. 199-221
    • Peng, Z.K.1    Chu, F.L.2
  • 9
    • 0012020346 scopus 로고    scopus 로고
    • Wavelet analysis and envelope detection for rolling element bearing fault diagnosis-their effectiveness and flexibilities
    • Tse P. W., Peng Y. H., Yam R. Wavelet analysis and envelope detection for rolling element bearing fault diagnosis-their effectiveness and flexibilities. Vibration and Acoustics, Vol. 123, 2001, p. 303-310.
    • (2001) Vibration and Acoustics , vol.123 , pp. 303-310
    • Tse, P.W.1    Peng, Y.H.2    Yam, R.3
  • 11
    • 70350129432 scopus 로고    scopus 로고
    • Fault diagnosis of spur bevel gear box using artificial neural network (ANN), and proximal support vector machine (PSVM)
    • Saravanan N., Kumar Siddabattuni V. N. S., Ramachandran K. I. Fault diagnosis of spur bevel gear box using artificial neural network (ANN), and proximal support vector machine (PSVM). Applied Soft Computing, Vol. 10, 2010, p. 344-360.
    • (2010) Applied Soft Computing , vol.10 , pp. 344-360
    • Saravanan, N.1    Kumar, S.V.N.S.2    Ramachandran, K.I.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.