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Analysis of Machine Learning based Condition Monitoring Schemes Applied to Complex Electromechanical Systems., , , , and . ETFA, page 1419-1422. IEEE, (2020)Deep Learning based Condition Monitoring approach applied to Power Quality., , , , and . ETFA, page 1427-1430. IEEE, (2020)Thermography-Based Method for the Fault Diagnosis of Magnetite-Contaminated Rolling Bearings., , , , , and . IECON, page 1-7. IEEE, (2023)Incremental Learning Framework-based Condition Monitoring for Novelty Fault Identification Applied to Electromechanical Systems., , , , , and . ETFA, page 1359-1364. IEEE, (2018)Industrial Data-Driven Monitoring Based on Incremental Learning Applied to the Detection of Novel Faults., , , and . IEEE Trans. Ind. Informatics, 16 (9): 5985-5995 (2020)Diagnosis Methodology Based on Deep Feature Learning for Fault Identification in Metallic, Hybrid and Ceramic Bearings., , , and . Sensors, 21 (17): 5832 (2021)Reliable methodology for gearbox wear monitoring based on vibration analysis., , , , , and . IECON, page 3381-3385. IEEE, (2014)Deep-Learning-Based Methodology for Fault Diagnosis in Electromechanical Systems., , , , and . Sensors, 20 (14): 3949 (2020)Condition monitoring approach based on dimensionality reduction techniques for detecting power quality disturbances in cogeneration systems., , , , , and . ETFA, page 898-903. IEEE, (2019)Design and control of a mechatronic system for the homogenization of compost in anaerobic digesters., , , and . CONIELECOMP, page 198-202. IEEE, (2013)