Analysis of signal processing techniques commonly used for broken bars detection on induction motors

  • Danilo Granda Universidad de las Fuerzas Armadas ESPE, Carrera de Ingeniería en Electrónica, Automatización y Control, Departamento de Eléctrica y Electrónica; Sangolquí, Ecuador
  • Diego Arcos-Aviles Universidad de las Fuerzas Armadas ESPE, Departamento de Eléctrica y Electrónica; Sangolquí, Ecuador
  • Danny Sotomayor Universidad de las Fuerzas Armadas ESPE, Departamento de Eléctrica y Electrónica; Sangolquí, Ecuador

Resumen

The fault detection of electric motors has been widely studied due to the importance of these devices at industrial level. This work presents the analysis of different signal processing techniques commonly used for broken bar detection of three-phase induction motors. Fast Fourier Transform (FFT), Hilbert Transform (HT), and Wavelet Transform (WT) are analyzed to obtain the motor current signal characteristics of healthy and faulty motors. The main advantages and drawbacks of each processing technique applied for broken bar detection of induction motors are presented in this study. The performance evaluation of each technique is carried out in the three-phase induction motor test bench at Universidad de las Fuerzas Armadas ESPE, Sangolquí-Ecuador.

Publicado
jun 30, 2018
##submission.howToCite##
GRANDA, Danilo; ARCOS-AVILES, Diego; SOTOMAYOR, Danny. Analysis of signal processing techniques commonly used for broken bars detection on induction motors. Revista CienciAmérica, [S.l.], v. 7, n. 1, p. 60-72, jun. 2018. ISSN 1390-9592. Disponible en: <http://cienciamerica.us/openjournal/index.php/uti/article/view/153>. Fecha de acceso: 20 abr. 2018