A review on detection and fault diagnosis in induction machines
Keywords:
Induction machines, type of failures, characteristics signal generated, failure detection methods, diagnosis methodsAbstract
In this work a careful review describing diferent types of failures in electricalmachines, their characteristic signals generated and diagnosis methodsis performed. Additionally a comparison of the advantages between theknown failure detection methods based on the information required for diagnosis, the occurrence and importance of failures detection, the effectiveness for anticipating a mal function or failure and the final diagnosis accuracy is also made. Particularly, this review will help to provide a straight forward update about the most recent work and research in this field. The work is mainly oriented to engineering students interested in starting the researchand study of electrical machines.
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Aguado, J. (2012). Análisis de fallas en motores de inducción utilizando la corriente estatorica, diseño y construcción de prototipo basado en un microcontrolador. Available at http://www.elistas.net.
ANSI/NEMA. (2012). Mg 1-2011. motors and generators (includes errata 2012). standard published 02/14/2012 by American National Standards Institute/National Electrical Manufacturers Association.
ASA. (2009). S12.60-2010/part 1. acoustical performance criteria, design requirements, and guidelines for schools, part 2:. Relocatable Classroom Factors standard published 09/02/2009 by American National Standards of the Acoustical Society of America.
ASA. (2010). S12.60-2010/part 1. acoustical performance criteria, design requirements, and guidelines for schools, part 1:. Permanent Schools standard published 04/28/2010 by American National Standards of the Acoustical Society of America.
Bakhri, S., Ertugrul, N., Soong, W. L., & Arkan, M. (2010). Investigation of negative sequence components for stator shorted turn detection in induction motors.
Baldizzone, S., Novak, C. J., & Kar, N. C. (2012). Experimental investigations of noise and vibration in electric machines.
Bayindir, R., Sefa, I., Colak, I., & Bektas, A. (2008). Fault detection and protection of induction motors using sensors. IEEE Transactions on Energy Conversion, 23 (3), pp 734-741.
Boesing, M., & Doncker, R. W. (2012, January/Frbruary). Exploring a vibration synthesis process for the acoustic characterization of electric drives. IEEE Transactions on Industry applications., 48 (1), pp 70-78.
Boukra, T., & Lebaroud, A. (2010). Classification of induction machine faults. Systems Signals and Devices. 7th International Multi-Conference., pp 1-6.
Brown, A., David, E., & Essalihi, M. (2011). Insulation resistance measurements for machine insulation. Electrical Insulation Conference. pp 261-264. Calero Pérez, R., & Carta González, J. A. (1998). Fundamentos de mecanismos y m´aquinas para ingenieros. Ed. McGrawHill/Interamericana de España. S.A., 1. ed. ISBN: 844812099X ISBN-13: 9788448120993.
Castelli, M., & Andrade, M. (2008). Metodología de monitoreo, deteccin y diagn´ostico de fallos en motores asíncronos de inducción. Memorias URUMAN.(6), pp 1-20.
Concari, C., Franceschini, G., & Tassoni, C. (2010). A mcsa procedure to diagnose low frequency mechanical unbalances in induction machines.
Filippetti, F., Bellini, A., & Capolino, G. (2013). Condition monitoring and diagnosis of rotor faults in induction machines: State of art and future perspectives. Electrical Machines Design Control and Diagnosis. IEEE Workshop., pp 196-209.
Frosini, L., Borin, A., Girometta, L., & Venchi, G. (2011). Development of a leakage flux measurement system for condition monitoring of electrical drives.
Gnal, S., & Nehiz, . N. (2009). Induction machine condition monitoring using notch-xfiltered motor current. Mechanical Systems and Signal Processing., 23 (8), pp 2658-2670.
Grubic, S., Aller, J. M., Lu, B., & Habetler, T. G. (2008). A survey on 28 Publicaciones en Ciencias y Tecnolog´ia. Vol 8,N01, Ene-Jul 2014, pp.11-30. Medrano, Z.; Pérez, T.; G´omez, S. testing and monitoring methods for stator insulation systems of low-voltage induction machines focusing on turn insulation problems. IEEE Electrical Insulation Magazine. ISBN: 978-1- 4244-1621-9 , pp 4127-4136.
Gubric, S., Aller, J. M., Lu, B., & Habetler, T. G. (2012). A survey of testing and monitoring methods for stator insulation system in induction machines. Available at http://prof.usb.ve, pp 1-8.
Guedidi, S., Zouzou, S. E., Laala, W., Sahraoui, M., & Yahia, K. (2011). Broken bar fault diagnosis of induction motors using mcsa and neural network. diagnostics for electric machines. power electronics and drives.
Hidalgo, J. C. (2013). An´alisis de las zonas de falla de motores eléctricos. Available at http://www.termogram.com. pp 1-12.
Kathir, I., Balakrishnan, S., & Bevila, R. J. (2011). Fault analysis of induction motor. Emerging Trends in Electrical and Computer Technology. International Conference., pp 476-479.
Kia, S. H., Henao, H., & Capolino, G. (2010). Torsional vibration assessment using induction machine electromagnetic torque estimation. IEEE Transactions on Industrial Electronics., 57 (1), pp 209-219.
Kreitzer, S., Obermeyer, J., & Mistry, R. (2008). The effects of structural and localized resonances on induction motor performance. IEEE Transactions on Industry Applications., 44 (5), pp 1367-1375.
Mariun, N., Mehrjou, M. R., Marhaban, M. H., & Misron, N. (2011). An experimental study of induction motor current signature analysis techniques for incipient broken rotor bar detection.
Nandi, S., Toliyat, H. A., & Li, X. (2005). Condition monitoring and fault diagnosis of electrical motors-a review. IEEE Transactions on Energy Conversion., 20 (4), pp 719-729.
Puche, R. (2008). Nuevos métodos de diagnosis de excentricidad y otras asimetrías rotóricas en máquinas eléctricas de inducción a través del análisis de la corriente estatórica. Tesis Doctoral. Universidad Politécnica de Valencia.
Puche, R., Pons, J., Climente, V., & Pineda, M. (2004). Review diagnosis methods of induction electrical machines based Publicaciones en Ciencias y Tecnología. Vol 8,N01, Ene-Jul 2014, pp.11-30. 29 DETECTION AND FAULT DIAGNOSIS IN INDUCTION MACHINES on steady state current. Phys. Rev. D, pp1-5. Available at . Rangel, J. J., Romero, R. J., Osornio, R. A., Cabal, E., & Contreras, L. M. (2009). Novel methodology for online half-broken-bar detection on induction motors. IEEE Transactions on Instrumentation and Measurement., 58 (5), pp 1690-1698.
Sánchez, M. A., Aguilar, J. D., & Jutinico, A. L. (2012). Revisión bibliogr´afica: Implementaci´on del vector de park para la detecci´on de fallas en máquinas rotativas.
Siddique, A., Yadava, G. S., & Singh, B. (2005). A review of stator fault monitoring techniques of induction motors. IEEE Transaction on Energy Conversion., 20 (1), pp 106-114.
Sin, M. L., Soong, W. L., & Ertugrul, N. (2012). Induction machine on-line condition monitoring and fault diagnosis-a survey. Available at http://adelaide.academia.edu.
Spyropoulos, D. V., Gyftakis, K. N., Kappatou, J., & Mitronikas, E. D. (2012). The influence of the broken bar fault on the magnetic field and electromagnetic torque in 3-phase induction motors.
Tozzi, M., Cavallini, A., & Montanari, G. C. (2011). Monitoring off-line and on-line pd under impulsive voltage on induction motors-part 2: Testing*. IEEE Electrical Insulation Magazine., 27, pp 14-21.
Verucchi, C., Acosta, G. G., & Benger, F. A. (2009). A review on fault diagnosis of induction machines. Latin American App. Research., pp 113-121.
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