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20192025
most citedFault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data

3 citations · 6 across the 11 of their papers we have counts for

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cs.AI2022★ 3 cited

Fault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data

Lucas Costa Brito, Gian Antonio Susto, Jorge Nei Brito +1

Artificial Intelligence (AI) is one of the approaches that has been proposed to analyze the collected data (e.g., vibration signals) providing a diagnosis of the asset's operating…

cs.AI2021★ 1 cited

An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery

Lucas Costa Brito, Gian Antonio Susto, Jorge Nei Brito +1

The monitoring of rotating machinery is an essential task in today's production processes. Currently, several machine learning and deep learning-based modules have achieved excelle…