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Electrical equipment failures can cause significant downtime, safety hazards, and economic losses. Traditional fault detection methods in any power system network often rely on human expertise and rule-based systems, which can be limited in their accuracy and adaptability expand more .This paper explores the potential of machine learning (ML) for fault detection and classification in electrical equipment expand more .It discusses the different types of ML algorithms suitable for this task, analyzes the data requirements and challenges, and reviews the current state-of-the-art research in this field. Finally, the paper highlights the benefits and limitations of using ML for fault detection and classification, paving the way for future research directions.
Mantri et al. (Tue,) studied this question.