Abstract

This work is a review of current trends in the stray flux signal processing techniques applied to the diagnosis of electrical machines. Initially, a review of the most commonly used standard methods is performed in the diagnosis of failures in induction machines and using stray flux; and then specifically it is treated and performed the algorithms based on statistical analysis using cumulants and polyspectra. In addition, the theoretical foundations of the analyzed algorithms and examples applications are shown from the practical point of view where the benefits that processing can have using HOSA and its relationship with stray flux signal analysis, are illustrated.

Details

Title
Higher-Order Spectral Analysis of Stray Flux Signals for Faults Detection in Induction Motors
Author
Iglesias Martínez, Miguel E 1 ; Antonino-Daviu, Jose A 2 ; Fernández de Córdoba, Pedro 3 ; Conejero, J Alberto 3 

 Departamento de Telecomunicaciones, Universidad de Pinar del Río, Pinar del Río, Martí 270, CP20100, Cuba; Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, E46022València, Spain 
 Instituto de Tecnología Eléctrica, Universitat Politècnica de València, E46022ValènciaSpain 
 Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, E46022València, Spain 
Pages
1-14
Publication year
2020
Publication date
2020
Publisher
De Gruyter Poland
e-ISSN
24448656
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3191239266
Copyright
© 2020. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.