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Fault Classification Methods in Electric Power Systems: A review
DOI:
https://doi.org/10.15446/sicel.v12.121232Palabras clave:
fault classification, Machine learning, Deep learning, power systems (es)Aprendizaje de Máquina, Clasificación de fallas, Aprendizaje profundo, sistemas de potencia (en)
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Las fallas en los sistemas eléctricos impactan significativamente la calidad del servicio. A lo largo de los años, diversos investigadores han propuesto métodos para la clasificación, predicción y detección de fallas, con el objetivo de optimizar el desempeño y la continuidad del servicio eléctrico. Este artículo presenta una revisión de la literatura en la clasificación de fallas, abarcando tanto el empleo de algoritmos clásicos basados en procesamiento de señales, métodos de aprendizaje automático y la implementación de métodos basados en aprendizaje profundo.
Faults in electrical systems significantly impact service quality. Over the years, various researchers have proposed methods for fault classification, prediction, and detection, aiming to optimize the performance and continuity of electrical service. This article presents a literature review on fault classification, covering the use of classical signal-processing algorithms, machine learning methods, and deep learning-based techniques.
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Derechos de autor 2026 Sergio Abraham Botina Josa, Camilo Younes Velosa
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
