M. Benbouzid, A review of induction motors signature analysis as a medium for faults detection, IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200), pp.984-994, 2000.
DOI : 10.1109/IECON.1998.724016

J. Jung, J. Lee, and B. Kwon, Online Diagnosis of Induction Motors Using MCSA, IEEE Transactions on Industrial Electronics, vol.53, issue.6, pp.1842-1852, 2006.
DOI : 10.1109/TIE.2006.885131

A. Menacer, S. Moreau, G. Champenois, M. Said, and A. Benakcha, Experimental Detextion of Rotor Failures of Induction Machines by Stator Current Spectrum Analysis in Function of the Broken rotor Bars Position and the Load, The International Conference on Computer as a Tool, pp.1752-1758, 2007.

Z. Peng and F. Chu, Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography, Mechanical Systems and Signal Processing, vol.18, issue.2, pp.199-221, 2004.
DOI : 10.1016/S0888-3270(03)00075-X

A. K. Jardine, D. Lin, and D. Banjevic, A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mechanical Systems and Signal Processing, vol.20, issue.7, pp.1483-1510, 2006.
DOI : 10.1016/j.ymssp.2005.09.012

P. Jayaswal, A. K. Wadhwani, and K. B. Mulchandani, Review Article Machine Fault Signature Analysis, International Journal of Rotating Machinery
DOI : 10.1155/2008/583982
URL : http://doi.org/10.1155/2008/583982

M. Mehrjou, N. Mariun, M. Marhaban, and N. Misron, Rotor fault condition monitoring techniques for squirrel-cage induction machine???A review, Mechanical Systems and Signal Processing, vol.25, issue.8, pp.2827-2848, 2011.
DOI : 10.1016/j.ymssp.2011.05.007

L. A. García-escudero, O. Duque-perez, D. Morinigo-sotelo, and M. Perez-alonso, Robust condition monitoring for early detection of broken rotor bars in induction motors, Expert Systems with Applications, vol.38, issue.3, pp.2653-2660, 2011.
DOI : 10.1016/j.eswa.2010.08.055

V. T. Tran and B. Yang, An intelligent condition-based maintenance platform for rotating machinery, Expert Systems with Applications, vol.39, issue.3, pp.2977-2988, 2012.
DOI : 10.1016/j.eswa.2011.08.159

G. Didier, E. Ternisien, O. Caspary, and H. Razik, A new approach to detect broken rotor bars in induction machines by current spectrum analysis, Mechanical Systems and Signal Processing, vol.21, issue.2, pp.1127-1142, 2007.
DOI : 10.1016/j.ymssp.2006.03.002
URL : https://hal.archives-ouvertes.fr/hal-00115405

P. Zhang, S. Ding, G. Wang, and D. Zhou, A frequency domain approach to fault detection in sampled-data systems, Automatica, vol.39, issue.7, pp.1303-1307, 2003.
DOI : 10.1016/S0005-1098(03)00106-7

G. Dalpiaz and A. Rivola, CONDITION MONITORING AND DIAGNOSTICS IN AUTOMATIC MACHINES: COMPARISON OF VIBRATION ANALYSIS TECHNIQUES, Mechanical Systems and Signal Processing, vol.11, issue.1, pp.53-73, 1997.
DOI : 10.1006/mssp.1996.0067

V. Trigeassou, B. Devanneaux, J. Dagues, and . Faucher, Comparison of modelling methods and of diagnostic of asynchronous motor in case of defects, 9th IEEE International Power Electronics Congress, pp.101-108, 2004.

C. Cristalli, N. Paone, and R. Rodríguez, Mechanical fault detection of electric motors by laser vibrometer and accelerometer measurements, Mechanical Systems and Signal Processing, vol.20, issue.6, pp.1350-1361, 2006.
DOI : 10.1016/j.ymssp.2005.11.013

A. Siddique, G. Yadava, and B. Singh, A Review of Stator Fault Monitoring Techniques of Induction Motors, IEEE Transactions on Energy Conversion, vol.20, issue.1, pp.106-114, 2005.
DOI : 10.1109/TEC.2004.837304

K. Worden, W. J. Staszewski, and J. J. Hensman, Natural computing for mechanical systems research: A tutorial overview, Mechanical Systems and Signal Processing, vol.25, issue.1, pp.4-111, 2011.
DOI : 10.1016/j.ymssp.2010.07.013

A. Widodo and B. Yang, Support vector machine in machine condition monitoring and fault diagnosis, Mechanical Systems and Signal Processing, vol.21, issue.6, pp.2560-2574, 2007.
DOI : 10.1016/j.ymssp.2006.12.007

Y. Lei, J. Lin, Z. He, and M. J. Zuo, A review on empirical mode decomposition in fault diagnosis of rotating machinery, Mechanical Systems and Signal Processing, vol.35, issue.1-2, pp.1-2
DOI : 10.1016/j.ymssp.2012.09.015

N. Hamzaoui, C. Boisson, and C. Lesueur, VIBRO???ACOUSTIC ANALYSIS AND IDENTIFICATION OF DEFECTS IN ROTATING MACHINERY, PART I: THEORETICAL MODEL, Journal of Sound and Vibration, vol.216, issue.4, pp.553-570, 1998.
DOI : 10.1006/jsvi.1995.1713

R. Randall, Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications, 2011.
DOI : 10.1002/9780470977668

G. Didier, E. Ternisien, O. Caspary, and H. Razik, Fault detection of broken rotor bars in induction motor using a global fault index, IEEE Transactions on Industry Applications, vol.42, issue.1, pp.79-88, 2006.
DOI : 10.1109/TIA.2005.861368
URL : https://hal.archives-ouvertes.fr/hal-00095758

M. Eltabach, J. Antoni, G. Shanina, S. Sieg-zieba, and X. , Broken rotor bars detection by a new non-invasive diagnostic procedure, Mechanical Systems and Signal Processing, vol.23, issue.4, pp.1398-1412, 2009.
DOI : 10.1016/j.ymssp.2008.08.016

M. Eltabach, J. Antoni, and M. Najjar, Quantitative analysis of noninvasive diagnostic procedures for induction motor drives, Mechanical Systems and Signal Processing, vol.21, issue.7, pp.2838-2856, 2007.
DOI : 10.1016/j.ymssp.2007.03.006

A. Bellini, F. Filippetti, C. Tassoni, and G. Capolino, Advances in Diagnostic Techniques for Induction Machines, IEEE Transactions on Industrial Electronics, vol.55, issue.12, pp.4109-4126, 2008.
DOI : 10.1109/TIE.2008.2007527

A. Silva, Induction motor fault diagnostic and monitoring methods, 2006.

E. Elbouchikhi, V. Choqueuse, M. Benbouzid, and J. Charpentier, Induction machine fault detection enhancement using a stator current high resolution spectrum, 38th Annual Conference on IEEE Industrial Electronics Society (IECON), pp.3913-3918, 2012.

G. King, M. Tarbouchi, and D. Mcgaughey, Current signature analysis of induction machine rotor faults using the fast orthogonal search algorithm, 5th IET International Conference on Power Electronics, Machines and Drives (PEMD 2010), p.215, 2010.
DOI : 10.1049/cp.2010.0007

D. R. Mcgaughey, M. Tarbouchi, K. Nutt, and A. Chikhani, Speed Sensorless Estimation of AC Induction Motors Using the Fast Orthogonal Search Algorithm, IEEE Transactions on Energy Conversion, vol.21, issue.1, pp.112-120, 2006.
DOI : 10.1109/TEC.2005.853766

K. H. Chon, Accurate identification of periodic oscillations buried in white or colored noise using fast orthogonal search, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. No.99CH37015), pp.622-629, 2001.
DOI : 10.1109/IEMBS.1999.804152

A. Bracale, G. Carpinelli, L. Piegari, and P. Tricoli, A High Resolution Method for On Line Diagnosis of Induction Motors Faults, 2007 IEEE Lausanne Power Tech, pp.994-998, 2007.
DOI : 10.1109/PCT.2007.4538451

S. Kia, H. Henao, and G. Capolino, A High-Resolution Frequency Estimation Method for Three-Phase Induction Machine Fault Detection, IEEE Transactions on Industrial Electronics, vol.54, issue.4, pp.2305-2314, 2007.
DOI : 10.1109/TIE.2007.899826

G. Bouleux, A. Ibrahim, F. Guillet, and R. Boyer, A subspace-based rejection method for detecting bearing fault in asynchronous motor, 2008 International Conference on Condition Monitoring and Diagnosis, pp.171-174, 2008.
DOI : 10.1109/CMD.2008.4580256

G. Bouleux, T. Kidar, and F. Guillet, An improper random vector approach for ESPRIT and unitary ESPRIT frequency estimation, International Workshop on Systems, Signal Processing and their Applications, WOSSPA, pp.299-302, 2011.
DOI : 10.1109/WOSSPA.2011.5931478

P. Wirfalt, G. Bouleux, M. Jansson, and P. Stoica, Subspace-based frequency estimation utilizing prior information, 2011 IEEE Statistical Signal Processing Workshop (SSP), pp.533-536, 2011.
DOI : 10.1109/SSP.2011.5967751
URL : http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-45017

M. Kristensson, M. Jansson, B. Ottersten, G. Bouleux, P. Stoica et al., Further results and insights on subspace based sinusoidal frequency estimation An Optimal Prior knowledge-based DOA Estimation Method, European Signal Processing Conference, p.17, 2009.
DOI : 10.1109/78.969505

H. Chen, S. V. Huffel, D. V. Ormondt, and R. De-beer, Parameter Estimation with Prior Knowledge of Known Signal Poles for the Quantification of NMR Spectroscopy Data in the Time Domain, Journal of Magnetic Resonance, Series A, vol.119, issue.2, pp.225-234, 1996.
DOI : 10.1006/jmra.1996.0077

R. Behrens and L. Scharf, Signal processing applications of oblique projection operators, IEEE Transactions on Signal Processing, vol.42, issue.6, pp.1413-1424, 1994.
DOI : 10.1109/78.286957
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.331.6329

S. V. Huffel and J. Vanderwalle, The total least squares problem : computational aspects and analysis, 1991.
DOI : 10.1137/1.9781611971002