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Rotor fault detection in induction motors based on time-frequency analysis using the bispectrum and the autocovariance of stray flux signals

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Rotor fault detection in induction motors based on time-frequency analysis using the bispectrum and the autocovariance of stray flux signals

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Iglesias-Martínez, ME.; Antonino Daviu, JA.; Fernández De Córdoba, P.; Conejero, JA. (2019). Rotor fault detection in induction motors based on time-frequency analysis using the bispectrum and the autocovariance of stray flux signals. Energies. 12(4):1-16. https://doi.org/10.3390/en12040597

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/157507

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Título: Rotor fault detection in induction motors based on time-frequency analysis using the bispectrum and the autocovariance of stray flux signals
Autor: Iglesias-Martínez, Miguel E. Antonino Daviu, José Alfonso Fernández de Córdoba, Pedro Conejero, J. Alberto
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica
Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Fecha difusión:
Resumen:
[EN] The aim of this work is to find out, through the analysis of the time and frequency domains, significant differences that lead us to obtain one or several variables that may result in an indicator that allows diagnosing ...[+]
Palabras clave: Indicator , Fault diagnosis , Induction motors , Bispectrum , Autocovariance
Derechos de uso: Reconocimiento (by)
Fuente:
Energies. (eissn: 1996-1073 )
DOI: 10.3390/en12040597
Editorial:
MDPI AG
Versión del editor: https://doi.org/10.3390/en12040597
Código del Proyecto:
info:eu-repo/grantAgreement/MINECO//MTM2016-75963-P/ES/DINAMICA DE OPERADORES/
Agradecimientos:
This research was funded by MEC, grant number MTM 2016-7963-P.
Tipo: Artículo

References

Henao, H., Capolino, G.-A., Fernandez-Cabanas, M., Filippetti, F., Bruzzese, C., Strangas, E., … Hedayati-Kia, S. (2014). Trends in Fault Diagnosis for Electrical Machines: A Review of Diagnostic Techniques. IEEE Industrial Electronics Magazine, 8(2), 31-42. doi:10.1109/mie.2013.2287651

Riera-Guasp, M., Antonino-Daviu, J. A., & Capolino, G.-A. (2015). Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art. IEEE Transactions on Industrial Electronics, 62(3), 1746-1759. doi:10.1109/tie.2014.2375853

Jiang, C., Li, S., & Habetler, T. G. (2017). A review of condition monitoring of induction motors based on stray flux. 2017 IEEE Energy Conversion Congress and Exposition (ECCE). doi:10.1109/ecce.2017.8096907 [+]
Henao, H., Capolino, G.-A., Fernandez-Cabanas, M., Filippetti, F., Bruzzese, C., Strangas, E., … Hedayati-Kia, S. (2014). Trends in Fault Diagnosis for Electrical Machines: A Review of Diagnostic Techniques. IEEE Industrial Electronics Magazine, 8(2), 31-42. doi:10.1109/mie.2013.2287651

Riera-Guasp, M., Antonino-Daviu, J. A., & Capolino, G.-A. (2015). Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art. IEEE Transactions on Industrial Electronics, 62(3), 1746-1759. doi:10.1109/tie.2014.2375853

Jiang, C., Li, S., & Habetler, T. G. (2017). A review of condition monitoring of induction motors based on stray flux. 2017 IEEE Energy Conversion Congress and Exposition (ECCE). doi:10.1109/ecce.2017.8096907

Ramirez-Nunez, J. A., Antonino-Daviu, J. A., Climente-Alarcon, V., Quijano-Lopez, A., Razik, H., Osornio-Rios, R. A., & Romero-Troncoso, R. de J. (2018). Evaluation of the Detectability of Electromechanical Faults in Induction Motors Via Transient Analysis of the Stray Flux. IEEE Transactions on Industry Applications, 54(5), 4324-4332. doi:10.1109/tia.2018.2843371

Park, Y., Yang, C., Kim, J., Kim, H., Lee, S. B., Gyftakis, K. N., … Capolino, G.-A. (2019). Stray Flux Monitoring for Reliable Detection of Rotor Faults Under the Influence of Rotor Axial Air Ducts. IEEE Transactions on Industrial Electronics, 66(10), 7561-7570. doi:10.1109/tie.2018.2880670

Iglesias-Martinez, M. E., de Cordoba, P. F., Antonino-Daviu, J. A., & Conejero, J. A. (2018). Detection of Bar Breakages in Induction Motor via Spectral Subtraction of Stray Flux Signals. 2018 XIII International Conference on Electrical Machines (ICEM). doi:10.1109/icelmach.2018.8507078

Mendel, J. M. (1991). Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications. Proceedings of the IEEE, 79(3), 278-305. doi:10.1109/5.75086

Nikias, C. L., & Mendel, J. M. (1993). Signal processing with higher-order spectra. IEEE Signal Processing Magazine, 10(3), 10-37. doi:10.1109/79.221324

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