1 |
Markou, M., Singh, S, 'Novelty detection: a review-part 2: neural network based approaches', Signal Processing, 83(12)(2003): 2499-2521
DOI
ScienceOn
|
2 |
Lee, Y. S. et al., 'An acoustic diagnostic technique for use with electric machine insulation', IEEE Transactions on Dielectrics and Electrical Insulation, 9(1994): 1186–1193
DOI
|
3 |
Thollon, F., Jammal, A., & Grellet, G., 'Asynchronous motor cage fault detection through electromagnetic torque measurement', European Transactions on Electrical Power, 3(1993): 375–378
DOI
|
4 |
Lou, X., Loparo, K. A., 'Bearing fault diagnosis based on wavelet transform and fuzzy inference', Mechanical Systems and Signal Processing, 18(6)(2004): 373-390
DOI
ScienceOn
|
5 |
Stone, G. C., Sedding, H. G., & Costello, M. J., 'Application of partial discharge testing to motor and generator stator winding maintenance', IEEE Transactions on Industry Application, 32(1996): 459–464
DOI
ScienceOn
|
6 |
Tax, M. J., Duin, P. W., 'Support vector data description', Machine Learning, 54(2004): 45-66
DOI
ScienceOn
|
7 |
Scholkopf, B., Smola, A.J., Learning with Kernels, MIT Press, Cambridge Massachusetts London, (2002)
|
8 |
Duda, R.O., Hart, P.E. and Stork, D.G., Pattern Classification, 2nd Ed., Wiley-Interscience, (2001)
|
9 |
Markou, M., Singh, S., 'Novelty detection: a review-part 1: statistical approaches. Signal Processing', 83(12) (2003): 2481-2497
DOI
ScienceOn
|
10 |
Thomson, W. T., & Fenger, M., 'Current signature analysis to detect induction motor faults', IEEE Transactions on Industry Applications, 7(2001); 26–34
DOI
ScienceOn
|