An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery. - Lucas Costa Brito; Gian Antonio Susto; Jorge Nei Brito; Marcus Antonio Viana Duarte (CoRR, 2021)

Fault Detection of Bearing: An Unsupervised Machine Learning Approach Exploiting Feature Extraction and Dimensionality Reduction. - Lucas Costa Brito; Gian Antonio Susto; Jorge Nei Brito; Marcus Antonio Viana Duarte (Informatics, 2021)

Identification of cutting tool wear condition in turning using self-organizing map trained with imbalanced data. - Lucas Costa Brito; Márcio Bacci da Silva; Marcus Antonio Viana Duarte (J. Intell. Manuf., 2021)

Band Relevance Factor (BRF): a novel automatic frequency band selection method based on vibration analysis for rotating machinery. - Lucas Costa Brito; Gian Antonio Susto; Jorge Nei Brito; Marcus Antonio Viana Duarte (CoRR, 2022)

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; Marcus Antonio Viana Duarte (Expert Syst. Appl., 2023)