A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence

A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence

Power transformers are critical components in ensuring the continuous and stable operation of power systems. Failures in these units can lead to significant power outages and costly downtime. Existing maintenance strategies often fail to accurately predict such failures, highlighting the need for no...

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Bibliographic Details
Main Authors: Emrah Aslan, Yildirim Ozupak, Feyyaz Alpsalaz, Zakaria M. S. Elbarbary
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Fault detection
power transformers
machine learning
SHAP
LIME
Online Access:https://ieeexplore.ieee.org/document/11053795/
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