An artificial immune system approach for fault detection in the stator and rotor circuits of induction machines

Electric Power Systems Research

Volumn 81, Issue 1, 2011, Pages 158-169

  Chilengue, Z ^a   Dente, J A ^b   Branco, P J Costa ^b  

^a EDUARDO MONDLANE UNIVERSITY   (Mozambique)

^b INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

Artificial immune systems; Fault diagnosis; Induction machine; Pattern recognition

Indexed keywords

ARTIFICIAL IMMUNE SYSTEM; BEFORE AND AFTER; DETECTION AND DIAGNOSIS; FAULT CONDITIONS; FAULT DIAGNOSIS; IMMUNE SYSTEMS; INDUCTION MACHINE; INDUCTION MACHINES; MACHINE OPERATING; MACHINE OPERATION; OPERATING CONDITION; PATTERN RECOGNITION ALGORITHMS; ROTOR CIRCUITS; STATOR CURRENTS; THREE-PHASE INDUCTION MACHINE;

ASYNCHRONOUS MACHINERY; IMMUNOLOGY; PATTERN RECOGNITION SYSTEMS; STATORS;

FAULT DETECTION;

EID: 77958076238     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.epsr.2010.08.003     Document Type: Article

References (23)

1. F. Briz, M.W. Degner, P. Garcia, and A.B. Diez High-frequency carrier-signal voltage selection for stator winding fault diagnosis in inverter-fed AC machines IEEE Trans. Ind. Electron. 55 12 2008 4181 4190
2. M. Bouzid, G. Champenois, N.M. Bellaaj, L. Signac, and K. Jelassi An effective neural approach for the automatic location of stator interturn faults in induction motor IEEE Trans. Ind. Electron. 55 12 2008 4277 4289
3. S. Bachir, S. Tnani, J.-C. Trigeassou, and G. Champenois Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines IEEE Trans. Ind. Electron. 53 3 2006 963 973
4. M. Blodt, P. Granjon, B. Raison, and G. Rostaing Models for bearing damage detection in induction motors using stator current monitoring IEEE Trans. Ind. Electron. 55 4 2008 1813 1822
5. S.M.A. Cruz, A. Stefani, F. Filippetti, and A.J.M. Cardoso A new model-based technique for the diagnosis of rotor faults in RFOC induction motor drives IEEE Trans. Ind. Electron. 55 12 2008 4218 4228
6. F. Zidani, D. Diallo, M. El Hachemi Benbouzid, and R. Nait-Said A fuzzy-based approach for the diagnosis of fault modes in a voltage-fed PWM inverter induction motor drive IEEE Trans. Ind. Electron. 55 2 2008 586 593
7. M.S. Ballal, Z.J. Khan, H.M. Suryawanshi, and R.L. Sonolikar Adaptive neural fuzzy inference system for the detection of inter-turn insulation and bearing wear faults in induction motor IEEE Trans. Ind. Electron. 54 1 2007 250 258
8. Z. Ye, A. Sadeghian, and B. Wu Mechanical fault diagnostics for induction motor with variable speed drives using Adaptive Neuro-fuzzy Inference System Electric Power Syst. Res. 76 9-10 2006 742 752
9. A. Bellini, F. Filippetti, C. Tassoni, and G.-A. Capolino Advances in diagnostic techniques for induction machines IEEE Trans. Ind. Electron. 55 12 2008 4109 4126
10. H. Su, and K.T. Chong Induction machine condition monitoring using neural network modeling IEEE Trans. Ind. Electron. 54 1 2007 241 249
11. T.G. Amaral, V.F. Pires, J.F. Martins, A.J. Pires, and M.M. Crisostomo Image processing to a neuro-fuzzy classifier for detection and diagnosis of induction motor stator fault Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE 2007 2408 2413
12. J.F. Martins, V.F. Pires, and A.J. Pires Unsupervised neural-network-based algorithm for an on-line diagnosis of three-phase induction motor stator fault IEEE Trans. Ind. Electron. 54 1 2007 259 264
13. A. Bellini, A. Yazidi, F. Filippetti, C. Rossi, and G.-A. Capolino High frequency resolution techniques for rotor fault detection of induction machines IEEE Trans. Ind. Electron. 55 12 2008 4200 4209
14. J.-H. Jung, J.-J. Lee, and B.-H. Kwon Online diagnosis of induction motors using MCSA IEEE Trans. Ind. Electron. 53 6 2006 1842 1852
15. J. Cusido, L. Romeral, J.A. Ortega, J.A. Rosero, and A. Garcia Espinosa Fault detection in induction machines using power spectral density in wavelet decomposition IEEE Trans. Ind. Electron. 55 2 2008 633 643
16. B. Ayhan, H.J. Trussell, Mo-Yuen Chow, and Myung-Hyun Song On the use of a lower sampling rate for broken rotor bar detection with DTFT and AR-based spectrum methods IEEE Trans. Ind. Electron. 55 3 2008 1421 1434
17. S.H. Kia, H., H. Henao, and G.-A. Capolino Diagnosis of broken-bar fault in induction machines using discrete wavelet transform without slip estimation IEEE Trans. Ind. Electron. 45 4 2009 1395 1404
18. S.H. Kia, H. Henao, and G.-A. Capolino A high-resolution frequency estimation method for three-phase induction machine fault detection IEEE Trans. Ind. Electron. 54 4 2007 2305 2314
19. R.M. Zinkernagel On immunological memory Phil. Trans. R. Soc. Lond. B 355 2000 369 371
20. P.J. Delves, and I.M. Roitt The immune system - first of two parts Adv. Immunol. 343 1 2000 37 49
21. P.J. Costa Branco, J.A. Dente, and R. Vilela Mendes Using immunology principles for fault detection IEEE Trans. Ind. Electron. 50 2 2003 362 373
22. S. Özsen, and S. Günes Attribute weighting via genetic algorithms for attributed weighted artificial immune systems (AWAIS) and its application to heart disease and live disorder problems Expert Syst. Appl. 36 1 2009 386 392
23. Z. Gan, M. Zhao, and T.W.S. Chow Induction machine fault detection using clone selection programming Expert Syst. Appl. 36 4 2009 8000 8012