Rotor Fault Detection in Induction Motors Based on Time-Frequency Analysis Using the Bispectrum and the Autocovariance of Stray Flux Signals

Miguel E. Iglesias-Martínez, Jose Alfonso Antonino-Daviu, Pedro Fernández de Córdoba and J. Alberto Conejero
Additional contact information
Miguel E. Iglesias-Martínez: Departamento de Telecomunicaciones, Universidad de Pinar del Río, Pinar del Río, Martí #270, CP 20100, Cuba
Jose Alfonso Antonino-Daviu: Instituto Tecnológico de la Energía, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Pedro Fernández de Córdoba: Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
J. Alberto Conejero: Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain

Energies, 2019, vol. 12, issue 4, 1-16

Abstract: 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 the condition of the rotor in an induction motor from the processing of the stray flux signals. For this, the calculation of two indicators is proposed: the first is based on the frequency domain and it relies on the calculation of the sum of the mean value of the bispectrum of the flux signal. The use of high order spectral analysis is justified in that with the one-dimensional analysis resulting from the Fourier Transform, there may not always be solid differences at the spectral level that enable us to distinguish between healthy and faulty conditions. Also, based on the high-order spectral analysis, differences may arise that, with the classical analysis with the Fourier Transform, are not evident, since the high order spectra from the Bispectrum are immune to Gaussian noise, but not the results that can be obtained using the one-dimensional Fourier transform. On the other hand, a second indicator based on the temporal domain that is based on the calculation of the square value of the median of the autocovariance function of the signal is evaluated. The obtained results are satisfactory and let us conclude the affirmative hypothesis of using flux signals for determining the condition of the rotor of an induction motor.

Keywords: indicator; fault diagnosis; induction motors; bispectrum; autocovariance (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/4/597/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/4/597/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:4:p:597-:d:205737

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().