1 |
S. Wu, T. Chow, 'Induction machine fault detection using SOM-based RBF neural network,' IEEE Trans. Ind. Elect., Vol. 51, No.1, pp. 183-194, 2004
DOI
ScienceOn
|
2 |
Zidani et al., 'Induction motor stator faults diagnosis by a current Concordia pattern-based fuzzy decision system,' IEEE Trans. Energy Conversion, Vol. 18, No.4, pp. 469-475, December 2004
|
3 |
Jang-Hwan Park, Dae-Jong Lee, Myung-Geun Chun, 'Fault Diagnosis for Induction Machines Using Kernel Principal Component Analysis', ISNN2006, LNCS 3973, pp.406-413, 2006
|
4 |
A. M. Trzynadlowski and E. Ritchie, 'Comparative investigation of diagnostic media for induction motors: a case of rotor cage faults,' IEEE Trans. on Industrial Electronics, Vol. 47, No.5, pp. 1092-1099, 2000
DOI
ScienceOn
|
5 |
M. Haji and H. A. Toliyat, 'Pattern recognition a technique for induction machines rotor broken bar detection,' IEEE Trans. on Energy Conversion, Vol. 16, Issue 4, pp. 312-317, 2001
DOI
ScienceOn
|
6 |
W. T. Thomson, M. Fenger, 'Current signature analysis to detect induction motor faults,' IEEE Ind. Applicat. Magazine, pp. 26-34, July/August 2001
|
7 |
Nejjari, M. H. Benbouzid, 'Monitoring and diagnosis of induction motors electrical faults using a current Park's vector pattern learning approach,' IEEE Trans. Ind. Applicat., Vol. 36, No.3, pp. 730 -735, 2000
DOI
ScienceOn
|
8 |
Zhongming Ye, Bin Wu, and Alireza Sadeghian, 'Current Signature Analysis of Induction Motor Mechanical Faults by Wavelet Packet Decomposition,' IEEE Trans.on Industrial Electronics, Vol. 50, No.6, 2003
|