Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Recently, remarkable progress has been made in the application of machine learning techniques (e.g., neural networks) to transformer fault diagnosis. However, the diagnostic processes employed by these techniques often suffer from a lack of interpretability. To address this limitation, this letter p...

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