Hostname: page-component-84b7d79bbc-5lx2p Total loading time: 0 Render date: 2024-07-27T03:03:31.848Z Has data issue: false hasContentIssue false

Conditioning of a statistical indicator for the detection of an asynchronous machine rotor faults

Published online by Cambridge University Press:  16 November 2012

Get access

Abstract

In this paper, the cyclostationary characteristics of electrical signals will be exploited in order to detect the rotor faults of an asynchronous machine. These defects are the most complex in terms of detection since they interact with the 50 Hz carrier with a weak band occupied in frequency. The testing ground used includes an industrial three-phase wound rotor asynchronous motor of 400 V, 6.2 A, 50 Hz, 3 kW, 1385 rpm characteristics. The rotor fault has been carried out by adding an extra 40 mΩ resistance on one of the rotor phases (i.e. 10% of the rotor resistance value per phase, Rr = 0.4Ω). From the stator voltage and current acquisition, and by application of the Time Synchronous Averaging (TSA) method to the stator current, the electrical signal will be conditioned in order to obtain a sensitive indicator allowing to easily distinguish the healthy cases from defective ones.

Type
Research Article
Copyright
© AFM, EDP Sciences 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Références

H. Razik, Notes de cours sur le diagnostic de la machine asynchrone, IUFM de Lorraine, 2003
O. Ondel, Diagnostic par reconnaissance des formes : Application à un ensemble Convertisseur – Machine asynchrone, Thèse, École Centrale de Lyon, 2006
G. Didier, Modélisation et diagnostic de la machine asynchrone en présence de défaillances, Thèse, Université Henri Poincaré Nancy-I, 2004
A. Ibrahim, Contribution au diagnostic de machines électromécaniques : Exploitation des signaux électriques et de la vitesse instantanée, Thèse, Université Jean Monnet, St-Étienne, 2009
R. Fiser, S. Ferkolj, Modelling of dynamic performance of induction machine with rotor faults, In Procedings ICEM 1996, Vigo, Spain 1 17–22
Didier, G., Razik, H., Sur la détection d’un défaut au rotor des moteurs asynchrones, Revue 3EI. 27 (2001) 5362 Google Scholar
T. Boumégoura, H. Yahoui, G. Clerc, G. Grellet, Observation des paramètres du moteur asynchrone à cage d’écureuil avec un observateur non linéaire, Colloque EF’99, pp. 375–379, Lille 30&31, mars 1999
McFadden, P.D., Smith, J.D., A signal processing technique for detecting local defects in a gear from the signal average of the vibration, Proceedings of the Institution of Mechanical Engineers 199 (1985) 287292 Google Scholar
McFadden, P.D., A revised model for the extraction of periodic waveforms by time domain averaging, Mechanical Systems and Signal Processing 1 (1987) 8395 CrossRefGoogle Scholar
Bennett, W.R., Statistics of regenerative digital transmission, Bell System Techn. J. 37 (1958) 15011542 CrossRefGoogle Scholar
F. Bonnardot, Comparaison entre les analyses angulaire et temporelle des signaux vibratoires de machines tournantes. Étude du concept de cyclostationnarité floue, Thèse, Institut National Polytechnique de Grenoble, 2004
Benbouzid, M.E.H., Vieira, M., Theys, C., Induction motors faults detection and localisation using stator current advanced signal processing techniques, IEEE Trans. Power Electronics 14 (1999) 1422 CrossRefGoogle Scholar
Benbouzid, M.E.H., G.B. Kliman, What stator current processing-based technique to use for induction motor rotor faults diagnosis? IEEE Trans. Energy Convers. 18 (2003) 238244 Google Scholar
G. Salles, Surveillance et diagnostic des défauts de la charge d’un entraînement par machine asynchrone, Thèse, Université Lyon 1, 1997