Filter banks as proposal in electrical motors fault discrimination

Jhonattan Bulla; Alvaro David Orjuela-Cañón; Oscar D. Flórez

doi:10.1007/978-3-030-03023-0_5

Filter banks as proposal in electrical motors fault discrimination

Jhonattan Bulla
, Alvaro David Orjuela-Cañón
, Oscar D. Flórez

Producción científica: Capítulo en Libro/Informe › Capítulo › Investigación

Resumen

Studies related with the induction motor bearings fault detection have been used digital signal processing and pattern recognition techniques. However, performance of these approaches depends on the use of correct features. This paper deals an analysis of the use of filter banks with uniform and nonuniform frequency subbands to features extraction from vibration signals. Discrimination was developed by an artificial neural network with feedforward connections. Results identifies that the employment of filter banks improve the accuracy in 23% for six considered classes related with faults in bearings.

Idioma original	Inglés estadounidense
Título de la publicación alojada	Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers
Editores	Alvaro David Orjuela-Cañón, Juan Carlos Figueroa-García, Julián David Arias-Londoño
Editorial	Springer
Páginas	50-62
Número de páginas	13
ISBN (versión impresa)	9783030030223
DOI	https://doi.org/10.1007/978-3-030-03023-0_5
Estado	Publicada - 2018
Publicado de forma externa	Sí
Evento	1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018 - Medellin, Colombia Duración: may. 16 2018 → may. 18 2018

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	833
ISSN (versión impresa)	1865-0929

Conferencia

Conferencia	1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018
País/Territorio	Colombia
Ciudad	Medellin
Período	5/16/18 → 5/18/18

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

Áreas temáticas de ASJC Scopus

Ciencia de la Computación General
Matemáticas General

Acceder al documento

10.1007/978-3-030-03023-0_5

Otros archivos y enlaces

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Bulla, J., Orjuela-Cañón, A. D., & Flórez, O. D. (2018). Filter banks as proposal in electrical motors fault discrimination. En A. D. Orjuela-Cañón, J. C. Figueroa-García, & J. D. Arias-Londoño (Eds.), Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers (pp. 50-62). (Communications in Computer and Information Science; Vol. 833). Springer. https://doi.org/10.1007/978-3-030-03023-0_5

Bulla, Jhonattan ; Orjuela-Cañón, Alvaro David ; Flórez, Oscar D. / Filter banks as proposal in electrical motors fault discrimination. Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. editor / Alvaro David Orjuela-Cañón ; Juan Carlos Figueroa-García ; Julián David Arias-Londoño. Springer, 2018. pp. 50-62 (Communications in Computer and Information Science).

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title = "Filter banks as proposal in electrical motors fault discrimination",

abstract = "Studies related with the induction motor bearings fault detection have been used digital signal processing and pattern recognition techniques. However, performance of these approaches depends on the use of correct features. This paper deals an analysis of the use of filter banks with uniform and nonuniform frequency subbands to features extraction from vibration signals. Discrimination was developed by an artificial neural network with feedforward connections. Results identifies that the employment of filter banks improve the accuracy in 23\% for six considered classes related with faults in bearings.",

author = "Jhonattan Bulla and Orjuela-Ca{\~n}{\'o}n, \{Alvaro David\} and Fl{\'o}rez, \{Oscar D.\}",

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Bulla, J, Orjuela-Cañón, AD & Flórez, OD 2018, Filter banks as proposal in electrical motors fault discrimination. En AD Orjuela-Cañón, JC Figueroa-García & JD Arias-Londoño (eds.), Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. Communications in Computer and Information Science, vol. 833, Springer, pp. 50-62, 1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018, Medellin, Colombia, 5/16/18. https://doi.org/10.1007/978-3-030-03023-0_5

Filter banks as proposal in electrical motors fault discrimination. / Bulla, Jhonattan; Orjuela-Cañón, Alvaro David; Flórez, Oscar D.
Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. ed. / Alvaro David Orjuela-Cañón; Juan Carlos Figueroa-García; Julián David Arias-Londoño. Springer, 2018. p. 50-62 (Communications in Computer and Information Science; Vol. 833).

Producción científica: Capítulo en Libro/Informe › Capítulo › Investigación

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T1 - Filter banks as proposal in electrical motors fault discrimination

AU - Bulla, Jhonattan

AU - Orjuela-Cañón, Alvaro David

AU - Flórez, Oscar D.

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

Y1 - 2018

N2 - Studies related with the induction motor bearings fault detection have been used digital signal processing and pattern recognition techniques. However, performance of these approaches depends on the use of correct features. This paper deals an analysis of the use of filter banks with uniform and nonuniform frequency subbands to features extraction from vibration signals. Discrimination was developed by an artificial neural network with feedforward connections. Results identifies that the employment of filter banks improve the accuracy in 23% for six considered classes related with faults in bearings.

AB - Studies related with the induction motor bearings fault detection have been used digital signal processing and pattern recognition techniques. However, performance of these approaches depends on the use of correct features. This paper deals an analysis of the use of filter banks with uniform and nonuniform frequency subbands to features extraction from vibration signals. Discrimination was developed by an artificial neural network with feedforward connections. Results identifies that the employment of filter banks improve the accuracy in 23% for six considered classes related with faults in bearings.

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Bulla J, Orjuela-Cañón AD, Flórez OD. Filter banks as proposal in electrical motors fault discrimination. En Orjuela-Cañón AD, Figueroa-García JC, Arias-Londoño JD, editores, Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. Springer. 2018. p. 50-62. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-03023-0_5

Filter banks as proposal in electrical motors fault discrimination

Resumen

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Conferencia

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