An Approach of Fault Diagnosis Using Meta-Heuristics: a New Variant of the Differential Evolution Algorithm

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Auteur principal: Lídice Camps Echevarría
Format: Artículo científico
Langue:en
Publié: Instituto Politécnico Nacional 2014
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author Lídice Camps Echevarría
author_facet Lídice Camps Echevarría
contents An Approach of Fault Diagnosis Using Meta-Heuristics: a New Variant of the Differential Evolution Algorithm Lídice Camps Echevarría Orestes Llanes Santiago Antônio José da Silva Neto Haroldo Fraga de Campos Velho Computación meta heuristics robustness sensitivity fault diagnosis This paper presents an application of meta-heuristics to fault diagnosis. The idea behind this application is to develop methods for fault diagnosis that should be robust, sensitive and with an adequate computational cost. Applications of meta-heuristics are possible based on the formulation of fault diagnosis as an optimization problem. The results indicate the suitability of the use of meta-heuristics for fault diagnosis. In particular, this study shows an application of meta-heuristic termed Differential Evolution to diagnosing a DC Motor benchmark. This allowed developing a new variant of Differential Evolution, namely, Differential Evolution with Particle Collision. This new algorithm was validated with some benchmark functions for continuous optimization, showing that it over-performed the behavior of Differential Evolution. 2014 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61530484002 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.18
format Artículo científico
id redalyc_61530484002
institution Redalyc
language en
publishDate 2014
publisher Instituto Politécnico Nacional
spellingShingle An Approach of Fault Diagnosis Using Meta-Heuristics: a New Variant of the Differential Evolution Algorithm
Lídice Camps Echevarría
Computación
meta
heuristics
robustness
sensitivity
fault diagnosis
An Approach of Fault Diagnosis Using Meta-Heuristics: a New Variant of the Differential Evolution Algorithm Lídice Camps Echevarría Orestes Llanes Santiago Antônio José da Silva Neto Haroldo Fraga de Campos Velho Computación meta heuristics robustness sensitivity fault diagnosis This paper presents an application of meta-heuristics to fault diagnosis. The idea behind this application is to develop methods for fault diagnosis that should be robust, sensitive and with an adequate computational cost. Applications of meta-heuristics are possible based on the formulation of fault diagnosis as an optimization problem. The results indicate the suitability of the use of meta-heuristics for fault diagnosis. In particular, this study shows an application of meta-heuristic termed Differential Evolution to diagnosing a DC Motor benchmark. This allowed developing a new variant of Differential Evolution, namely, Differential Evolution with Particle Collision. This new algorithm was validated with some benchmark functions for continuous optimization, showing that it over-performed the behavior of Differential Evolution. 2014 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61530484002 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.18
title An Approach of Fault Diagnosis Using Meta-Heuristics: a New Variant of the Differential Evolution Algorithm
topic Computación
meta
heuristics
robustness
sensitivity
fault diagnosis
url https://www.redalyc.org/articulo.oa?id=61530484002