-
1
-
-
0021377369
-
VIBRATION MONITORING OF ROLLING ELEMENT BEARINGS BY THE HIGH-FREQUENCY RESONANCE TECHNIQUE - A REVIEW.
-
DOI 10.1016/0301-679X(84)90076-8
-
McFadden, P. D. and Smith, J. D. Vibration monitoring of rolling element bearings by the high-frequency resonance technique - a review. Tribol. Int., 1984, 17(1), 3-10. (Pubitemid 14561780)
-
(1984)
Tribology International
, vol.17
, Issue.1
, pp. 3-10
-
-
McFadden, P.D.1
Smith, J.D.2
-
2
-
-
0033336360
-
A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings
-
Tandon, N. and Choudhury, A. A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribol. Int., 1999, 32(8), 469-180.
-
(1999)
Tribol. Int.
, vol.32
, Issue.8
, pp. 469-180
-
-
Tandon, N.1
Choudhury, A.2
-
3
-
-
4344560583
-
Neural- network-based system for novel fault detection in rotating machinery
-
Crupi, V., Guglielmino, E., and Milazzo, G. Neural- network-based system for novel fault detection in rotating machinery.j. Vibr. Control, 2004, 10(8), 1137-1150.
-
(2004)
J. Vibr. Control
, vol.10
, Issue.8
, pp. 1137-1150
-
-
Crupi, V.1
Guglielmino, E.2
Milazzo, G.3
-
4
-
-
29444460051
-
Artificial neural networks and genetic algorithm for bearing fault detection
-
DOI 10.1007/s00500-005-0481-0
-
Samanta, B., Al-Balushi, K. R., and Al-Araimi, S. A. Artificial neural networks and genetic algorithm for bearing fault detection. Soft Comput., 2006, 10(3), 264-271. (Pubitemid 43008740)
-
(2006)
Soft Computing
, vol.10
, Issue.3
, pp. 264-271
-
-
Samanta, B.1
Al-Balushi, K.R.2
Al-Araimi, S.A.3
-
5
-
-
24644491376
-
HMM-based fault detection and diagnosis scheme for rolling element bearings
-
DOI 10.1115/1.1924636
-
Ocak, H. and Loparo, K. A. HMM-based fault detection and diagnosis scheme for rolling element bearings. j. Vibr. Acoust., 2005,127(4), 299-306. (Pubitemid 41263726)
-
(2005)
Journal of Vibration and Acoustics, Transactions of the ASME
, vol.127
, Issue.4
, pp. 299-306
-
-
Ocak, H.1
Loparo, K.A.2
-
6
-
-
34748819869
-
Early classifications of bearing faults using hidden Markov models, Gaussian mixture models, Mel-frequency cepstral coefficients and fractals
-
Nelwamondo, F. V., Marwala, T., and Mahola, U. Early classifications of bearing faults using hidden Markov models, Gaussian mixture models, Mel-frequency cepstral coefficients and fractals. Int. J. Innov. Comput. I, 2006,2(6), 1281-1299.
-
(2006)
Int. J. Innov. Comput. i
, vol.2
, Issue.6
, pp. 1281-1299
-
-
Nelwamondo, F.V.1
Marwala, T.2
Mahola, U.3
-
7
-
-
34548035641
-
Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine
-
DOI 10.1016/j.ymssp.2007.02.003, PII S0888327007000349
-
Abbasion, S., Rafsanjani, A., Farshidianfar, A., and Irani, N. Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine. Mech. Syst. Signal Process., 2007, 21(7), 2933-2945. (Pubitemid 47284786)
-
(2007)
Mechanical Systems and Signal Processing
, vol.21
, Issue.7
, pp. 2933-2945
-
-
Abbasion, S.1
Rafsanjani, A.2
Farshidianfar, A.3
Irani, N.4
-
8
-
-
14044252742
-
One-class support vector machines - An application in machine fault detection and classification
-
DOI 10.1016/j.cie.2005.01.009, PII S0360835205000100
-
Shin, H. J., Eom, D. H., and Kim, S. S. One-class support vector machines - an application in machine fault detection and classification. Comput. Ind. Eng., 2005, 48(2), 395-408. (Pubitemid 40274932)
-
(2005)
Computers and Industrial Engineering
, vol.48
, Issue.2
, pp. 395-408
-
-
Shin, H.J.1
Eom, D.-H.2
Kim, S.-S.3
-
9
-
-
34249661124
-
Support vector machine in machine condition monitoring and fault diagnosis
-
DOI 10.1016/j.ymssp.2006.12.007, PII S0888327007000027
-
Widodo, A. and Yang, B. S. Support vector machine in machine condition monitoring and fault diagnosis. Mech. Syst. Signal Process., 2007, 21(6), 2560-2574. (Pubitemid 46829756)
-
(2007)
Mechanical Systems and Signal Processing
, vol.21
, Issue.6
, pp. 2560-2574
-
-
Widodo, A.1
Yang, B.-S.2
-
10
-
-
33646534620
-
A review on machinery diagnostics and prognostics implementing condition-based maintenance
-
Jardine, A. K. S., Lin, D. M., and Banjevic, D. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mech. Syst. Signal Process., 2006, 20(7), 1483-1510.
-
(2006)
Mech. Syst. Signal Process.
, vol.20
, Issue.7
, pp. 1483-1510
-
-
Jardine, A.K.S.1
Lin, D.M.2
Banjevic, D.3
-
11
-
-
5044252073
-
Robust performance degradation assessment methods for enhanced rolling element bearing prognostics
-
Qiu, H., Lee, J., Lin, J., and Yu, G. Robust performance degradation assessment methods for enhanced rolling element bearing prognostics. Adv. Eng. Inf., 2003, 17(3-4), 127-140.
-
(2003)
Adv. Eng. Inf.
, vol.17
, Issue.3-4
, pp. 127-140
-
-
Qiu, H.1
Lee, J.2
Lin, J.3
Yu, G.4
-
12
-
-
34548745146
-
Validating prognostic algorithms: A case study using comprehensive bearing fault data
-
Big Sky Montana
-
Lybeck, N., Marble, S., and Morton, B. Validating prognostic algorithms: a case study using comprehensive bearing fault data. In Proceedings of the IEEE Aerospace Conference, Big Sky Montana, 2007, pp. 1-9.
-
(2007)
Proceedings of the IEEE Aerospace Conference
, pp. 1-9
-
-
Lybeck, N.1
Marble, S.2
Morton, B.3
-
13
-
-
0030261802
-
Measurement of machine performance degradation using a neural network model
-
DOI 10.1016/0166-3615(96)00013-9, PII S0166361596000139
-
Lee, J. Measurement of machine performance degradation using a neural network model. Comput. Ind., 1996, 30(3), 193-209. (Pubitemid 126392583)
-
(1996)
Computers in Industry
, vol.30
, Issue.3
, pp. 193-209
-
-
Lee, J.1
-
14
-
-
0037250820
-
Condition assessment of power transformer onload tap changers using wavelet analysis and self-organizing map: Field evaluation
-
Pengju, K. and Birtwhistle, D. Condition assessment of power transformer onload tap changers using wavelet analysis and self-organizing map: field evaluation. IEEE Trans. Power Deliu, 2003,18(1), 78-84.
-
(2003)
IEEE Trans. Power Deliu
, vol.18
, Issue.1
, pp. 78-84
-
-
Pengju, K.1
Birtwhistle, D.2
-
15
-
-
33749663808
-
Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods
-
DOI 10.1016/j.ymssp.2005.11.008, PII S0888327005002165
-
Huang, R. Q., Xi, L. F, Li, X. L., Liu, C. R., Qiu, H., and Lee, J. Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods. Mech. Syst. Signal Process., 2007, 21(1), 193-207. (Pubitemid 44550081)
-
(2007)
Mechanical Systems and Signal Processing
, vol.21
, Issue.1
, pp. 193-207
-
-
Huang, R.1
Xi, L.2
Li, X.3
Richard Liu, C.4
Qiu, H.5
Lee, J.6
-
16
-
-
9744242805
-
A prognostic algorithm for machine performance assessment and its application
-
Yan, J., Ko̧, M., and Lee, J. A prognostic algorithm for machine performance assessment and its application. Prod. Plan. Control, 2004,15, 796-801.
-
(2004)
Prod. Plan. Control
, vol.15
, pp. 796-801
-
-
Yan, J.1
Ko̧, M.2
Lee, J.3
-
17
-
-
27944498274
-
Degradation assessment and fault modes classification using logistic regression
-
DOI 10.1115/1.1962019
-
Yan, J. H. and Lee, J. Degradation assessment and fault modes classification using logistic regression. j. Manuf. Sci. Eng., Trans. ASME, 2005, 127(4), 912-914. (Pubitemid 41680982)
-
(2005)
Journal of Manufacturing Science and Engineering, Transactions of the ASME
, vol.127
, Issue.4
, pp. 912-914
-
-
Yan, J.1
Lee, J.2
-
18
-
-
33947210318
-
Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics
-
DOI 10.1016/j.jsv.2007.01.001, PII S0022460X07000260
-
Ocak, H., Loparo, K. A., and Discenzo, F. M. Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: a method for bearing prognostics.j. Sound Vibr., 2007, 302(4-5), 951-961. (Pubitemid 46435577)
-
(2007)
Journal of Sound and Vibration
, vol.302
, Issue.4-5
, pp. 951-961
-
-
Ocak, H.1
Loparo, K.A.2
Discenzo, F.M.3
-
19
-
-
58049182562
-
Robust bearing performance degradation assessment method based on improved wavelet packet-support vector data description
-
Pan, Y., Chen, J.,and Guo, L. Robust bearing performance degradation assessment method based on improved wavelet packet-support vector data description. Mech. Syst. Signal Process., 2009, 23(3), 669-681.
-
(2009)
Mech. Syst. Signal Process.
, vol.23
, Issue.3
, pp. 669-681
-
-
Pan, Y.1
Chen, J.2
Guo, L.3
-
20
-
-
0033220728
-
Support vector domain description
-
DOI 10.1016/S0167-8655(99)00087-2
-
Tax, D. M. J. and Duin, R. P. W. Support vector domain description. Pattern Recognit. Lett, 1999, 20(11-13), 1191-1199. (Pubitemid 32261897)
-
(1999)
Pattern Recognition Letters
, vol.20
, Issue.11-13
, pp. 1191-1199
-
-
Tax, D.M.J.1
Duin, R.P.W.2
-
22
-
-
0032388955
-
The lifting scheme: A construction of second generation wavelets
-
Sweldens, W. The lifting scheme: a construction of second generation wavelets. SLAM J. Math. Anal., 1998, 29(2), 511-546.
-
(1998)
SLAM J. Math. Anal.
, vol.29
, Issue.2
, pp. 511-546
-
-
Sweldens, W.1
-
23
-
-
79955720650
-
-
dd-tools, August
-
Tax, D. M. J. and Ewi, F. dd-tools, August 2007, available from http://www-ict.ewi.tudelft.nl/~davidt/ dd-tools.html
-
(2007)
-
-
Tax, D.M.J.1
Ewi, F.2
-
24
-
-
0022012225
-
ROLLING BEARING VIBRATIONS - THE EFFECTS OF GEOMETRICAL IMPERFECTIONS AND WEAR.
-
DOI 10.1016/0022-460X(85)90256-1
-
Sunnersjo, C. S. Rolling bearing vibrations-the effects of geometrical imperfections and wear.j. Sound Vibr, 1985, 98(4), 455-474. (Pubitemid 15512490)
-
(1985)
Journal of Sound and Vibration
, vol.98
, Issue.4
, pp. 455-474
-
-
Sunnersjo, C.S.1
-
25
-
-
0035273597
-
Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings
-
DOI 10.1006/mssp.2000.1330
-
Rubini, R. and Meneghetti, U. Application of the envelope and wavelet transform analyses for the diagnosis incipient faults in ball bearings. Mech. Syst. Signal Process., 2001,15(2), 287-302. (Pubitemid 32409308)
-
(2001)
Mechanical Systems and Signal Processing
, vol.15
, Issue.2
, pp. 287-302
-
-
Rubini, R.1
Meneghetti, U.2
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