Fuzzy Model for Power Transformer Condition Monitoring and Fault Detection

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The fuzzy logic model achieved a balanced accuracy of 96% in predicting transformer fault conditions.
Results indicate effective detection of various fault types through a multi-classification approach.
Data sourced from experts was used to create a comprehensive power transformer fault database.
This method aids engineers by reducing time needed for identifying and repairing potential faults.

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This model demonstrates high predictive capacity for fault detection in power transformers, implying effective classification methodologies.

Pérez et al. (2025) studied this question.

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This model demonstrates high predictive capacity for fault detection in power transformers, implying effective classification methodologies.