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

Un enfoque al diagnóstico de fallos aplicando meta heurísticas: nueva variante del algoritmo Evolución Diferencial

Lídice Camps Echevarría¹, Orestes Llanes Santiago¹, Antônio J. Silva Neto², and Haroldo Fraga de Campos Velho³

¹ Instituto Superior Politécnico José Antonio Echeverría, CUJAE, Havana, Cuba. lidice@cemat.cujae.edu.cu, orestes@electrica.cujae.edu.cu

³ National Institute of Spatial Researchs, INPE, São Jose dos Campos, SP, Brazil. haroldo@lac.inpe.br

Abstract

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.

Keywords: Differential evolution, meta-heuristics, fault diagnosis, particle collision, robustness, sensitivity.

Resumen

Este trabajo presenta un estudio de la aplicación de meta heurísticas al diagnóstico de fallos, con el fin de desarrollar métodos que sean robustos ante perturbaciones, sensibles ante fallos incipientes y con adecuado costo computacional. La aplicación de las mismas es posible a partir de la formulación del diagnóstico de fallos como un problema de optimización. Los resultados indican la factibilidad del uso de meta heurísticas. En este estudio se aplicó la meta heurística, Evolución diferencial al diagnóstico de fallos en el sistema de prueba Motor CD. El estudio permitió desarrollar un nuevo algoritmo que se ha llamado Evolución diferencial con colisión de partículas. Este fue validado con funciones de prueba de optimización continúa mostrando su superioridad sobre Evolución diferencial.

Palabras clave: Colisión de partículas, diagnóstico de fallos, evolución diferencial, meta heurísticas, robustez sensibilidad.

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