Evaluación de técnicas de inteligencia artificial utilizadas en el diagnóstico de fallas en plantas de potencia

Evaluation of artificial intelligence techniques used in the diagnosis of failures in power plants

Contenido principal del artículo

Jesús Filander-Caratar
Andrés Mauricio-Valencia
Gladys Caicedo-Delgado
Cristian Chamorro

Resumen

Este artículo presenta una evaluación de herramientas computacionales basadas en técnicas de inteligencia artificial, las cuales se enfocan en la detección y diagnóstico de fallas en los diferentes procesos asociados a una central de generación de energía tal como: hidroeléctricas, termoeléctricas y centrales nucleares. Inicialmente, se describen de manera general las principales técnicas de inteligencia artificial que permiten la construcción de sistemas inteligentes para el diagnóstico de fallas en centrales eléctricas, se presentan técnicas como: lógica difusa, redes neuronales, sistemas basados en el conocimiento y técnicas hibridas.  Posteriormente se presentan en tablas los diferentes artículos encontrados para cada una de las técnicas, ilustrando el año de publicación y una descripción de cada publicación. El resultado de este trabajo es la comparación y evaluación de cada técnica enfocada al diagnóstico de fallas en centrales eléctricas.  Lo novedoso de este trabajo, es que presenta una extensa bibliografía de las aplicaciones de las diferentes técnicas inteligentes en la solución del problema de detección y diagnóstico de falla en centrales de generación eléctrica

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Detalles del artículo

Biografía del autor/a (VER)

Jesús Filander-Caratar, Universidad del Valle

M.Sc. Mechanical engineering

Andrés Mauricio-Valencia, Universidad del Valle

Mechanical engineer

Gladys Caicedo-Delgado, Universidad del Valle

PhD in Electrical engineering

Cristian Chamorro, Universidad del Valle

PhD in Electrical engineering

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