Diagnostic des Défaillances de Génératrices Asynchrones d’Éoliennes Offshores et d’Hydroliennes
Étude Comparatives des Techniques de Traitement de Signaux Stationnaires
OPEN ACCESS
Improvement of the reliability and availability of offshore wind and marine current turbine requires the minimization and the ability to predict maintenance operations. In variable speed operation or in transients, advanced signal processing techniques are required to detect and diagnose failures using stator currents. In this context, several recent studies have suggested the use of time-frequency and time-scale representations for that purpose. The most common techniques used are: the spectrogram, the wavelet transform, the Wigner-Ville representation, and the Hilbert-Huang transform. This paper proposes then a comparative study of these techniques for failure detection in induction generators.
Résumé
L’amélioration de la disponibilité et de la fiabilité des éoliennes offshores et des systèmes de récupération de l’énergie des courants marins nécessite de minimiser et de prévoir les opérations de maintenance. En fonctionnement à vitesse variable ou en régime transitoire, des techniques de traitement du signal avancées sont requises pour réaliser la détection et le diagnostic des défaillances à partir des courants statoriques. Dans ce contexte, plusieurs études récentes ont proposé l’utilisation de techniques temps-fréquence et tempséchelle pour le diagnostic. Les techniques les plus utilisées sont : le spectrogramme, la transformée en ondelettes (scalogramme), la représentation de Wigner-Ville et la transformée de Hilbert-Huang. Cet article propose une étude comparative de ces techniques pour la détection de défauts survenant dans une génératrice asynchrone à cage connectée à un réseau triphasé fonctionnant en régime nominal.
induction generator, phase/amplitude modulated signals, non-stationary signals, time-frequency/time-scale representations.
Mots-Clés
génératrice asynchrone, signaux modulés en phase/amplitude, signaux non stationnaires, représentations temps- fréquence/temps-échelle.
Amirat Y., Benbouzid M., Al-Ahmar E., Bensaker B., Turri S. (2009). A brief status on condition monitoring and fault diagnosis in wind energy conversion systems. Renewable & Sustainable Energy Reviews, vol. 3, n° 9, December, p. 2629-2636.
Amirat Y., Choqueuse V., Benbouzid M.E.H. (2010).Condition monitoring of wind turbines based on amplitude demodulation. in Proceedings of the IEEE ECCE’10, Atlanta (USA), September, p. 2417-2421.
Antonio-Daviu J. A., Riera-Guasp M., Folch J., Palomares M. P. M. (2006). Validation of new method for the diagnosis of rotor bar failures via wavelet transform in industrial induction machines. IEEE Trans. Industry Applications, vol. 42, n°. 4, July/August.
Antonino-Daviu J. A., Riera-Guasp M., Pineda-Sanchez M., Pérez R. B. (2009). A critical comparison between DWT and Hilbert-Huang-based methods for the diagnosis of rotor bar failures in induction machines. IEEE Trans. Industry Applications, vol. 45, n° 5, September/October.
Auger F., Flandrin P., Goncalves P., Lemoine O. (1997). Time-frequency toolbox, for use with Matlab. CNRS, GDR ISIS, Tech. Rep. Benbouzid M. (2000). A review of induction motors signature analysis as a medium for faults detection. IEEE Transactions on Industrial Electronics, vol. 47, n° 5, p. 984-993.
Benelghali S., Benbouzid M.E.H., Charpentier J.F. (2007). Marine tidal current electric power generation technology: State of the art and current status. Proceedings of IEEE IEMD’07, Antalya (Turkey), vol. 2, May, p. 1407-1412.
Blödt M., Regnier J., Faucher J. (2009). Distinguishing load torque oscillations and eccentricity faults in induction motors using stator current Wigner distributions. IEEE Trans. Industry Applications, vol. 45, n° 6, November/December, p. 1991-2000.
Blödt M., Chabert M., Faucher J., Dagues B. (2005). Mechanical load fault detection in induction motors by stator current time-frequency analysis. in Proc. IEEE IEMDC, San Antonio, TX, May p. 1881-1888.
Bonnett A. H., Yung C. (2008). Increased efficiency versus increased reliability. IEEE Industry Applications Magazine, vol. 14, n° 1, janvier/février.
Cexus J. C. (2005). Analyse des signaux non-stationnaires par Transformation de Huang, opérateur de Teager-Kaiser, et transformation de Huang-Teager (THT), Thèse de Doctorat de l’Université de Rennes 1, décembre.
Cohen L. (1995). Time–Frequency Analysis. Englewood Cliffs, NJ: Prentice-Hall.
Cohen L. (1989). Time-frequency Distributions. A review. Proceeding of the IEEE, vol. 77, July, p. 941-981.
Cusido J., Romeral L., Ortega J. A., Rosero J. A., Garcia Espinosa A. (2008). Fault detection in induction machines using power spectral density in wavelet decomposition. IEEE Trans. Industrial Electronics, vol. 55, n° 2, February.
Dorrell D.G. (1994). The influence of rotor eccentricity on the output torque of cage induction motors. Proc. ICEM, Paris, France, vol. 1, p. 35-40.
Dorrell D.G., Thomson W.T., Roach S. (1997). Analysis of airgap flux, current and vibration signals as a function of the combinaison of static and dynamic airgap eccentricity in 3-phase induction motors. IEEE Trans. Ind. Appl., vol. 33, n° 1, Jan./Feb., p. 24-34.
El Bouchikhi E. H., Choqueuse V., Benbouzid M. E. H., Charpentier J., Barakat G. (2011). A comparative study of time-frequency representations for fault detection in wind turbine. Proc. IEEE Ind. Electron. Soc., Melbourne, Australia, Nov., p. 3584-3589.
El Bouchikhi E. H., Choqueuse V., Benbouzid M. E. H. (2012). Current frequency spectral subtraction and its contribution to induction machines’ bearings condition monitoring. IEEE Trans. on Energy Conversion, n° 99.
Faulstich S., Hahn B., Tavner P.J. (2010). Wind turbine downtime and its importance for offshore deployment. Wind Energy, DOI: 10.1002/we.421, July.
Flandrin P. (1999). Time Frequency / Time-Scale Analysis. San Diego, CA: Academic. Gray C. S., Watson S. J. (2010). Physics of failure approach to wind turbine condition based maintenance, Wind Energy, DOI: 10.1002/we.360, August 2010.
Harris F. (1978). On the use of windows for harmonic analysis with the discrete Fourier transform. Proc. of the IEEE, vol. 66, n° 1, January, p. 51-83.
Houdouin G., Barakat G., Dakyo B., Destobbeleer E., Nichita C. (2002). A Coupled magnetic circuit based global method for the simulation of squirrel cage induction machines under rotor and stator faults. in Proc. of ELECTRIMACS’02, Montreal (Canada), August.
Huang N., Shen Z., Long S., Wu M., Shih H., Zheng Q., Yen N., Tung C., Liu H. (1998). The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis. Proc. Roy. Soc. London, vol. 454, p. 903-995.
Joksimovic G., Durovic M., Penman J., Arthur N. (2000). Dynamic simulation of dynamic eccentricity in induction machines-winding function approach. IEEE Trans. Energy Conversion, vol. 15, n° 2, June, p. 143-148.
Kay S.M. (1998). Modern Spectral Estimation: Theory and Application, Prentice Hall, Englewood Cliffs, New Jersey.
Kay S. M., Marple S. L. (1981). Spectrum Analysis-A Modern Perspective. Proceeding of the IEEE, vol. 69, n° 11.
Kusiak A., Li W. (2010). The prediction and diagnosis of wind turbine faults. Renewable Energy, vol. 36, n° 1, January, p. 16-23.
Mecklenbräuker W., Hlawatsch F. (Eds) (1997). The Wigner Distribution. Theory and Applications in Signal Processing, Amsderdam, The Netherlands, Elsevier.
Picinbono B. (1997). On instantaneous amplitude and phase of signals. IEEE Trans. Signal Processing, vol. 45, n° 3, March, p. 552-560.
Rilling G., Flandrin P., Goncalves P. (2003). On empirical mode decomposition and its algorithms. in Proceedings of the IEEE/EURASIP Workshop on Nonlinear Signal and Image Processing, Grado (Italy), July.
Rioul O., Flandrin P. (1992). Time-scale energy distributions: a general class extending wavelet transforms. IEEE Trans. On Signal Processing, vol. 40, n° 7, July.
Rusek J. (1996). Reflection of eccentricities in spectral composition of currents of induction machines. in Proc. ICEM, Vigo, Spain, September, p. 470-475.
Theodoridis S., Koutroumbas K. (2003). Pattern Recognition. Elsevier Academic Press, Second Edition.
Thirion-Moreau N., Arquès P.Y. (2002). Analyse Temps Fréquence Linéaires et Quadratiques. Techniques de l’Ingénieur, Traité Télécoms, novembre.
Thomson W.T., Fenger M. (2003). Case histories of current signature analysis to detect faults in induction motor drives. Proceedings of the IEEE IEMDC’03, Madison (USA), vol. 3, June, p. 1459-1465.