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| article pdf uploaded. | 19 December 2025 14:14 CET | Version of Record | https://www.mdpi.com/2075-1702/14/1/9/pdf |
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| article pdf uploaded. | 19 December 2025 14:14 CET | Version of Record | https://www.mdpi.com/2075-1702/14/1/9/pdf |
Bourdalos, D.M.; Sakellariou, J.S. A Machine Learning Vibration-Based Methodology for Robust Detection and Severity Characterization of Gear Incipient Faults Under Variable Working Speed and Load. Machines 2026, 14, 9. https://doi.org/10.3390/machines14010009
Bourdalos DM, Sakellariou JS. A Machine Learning Vibration-Based Methodology for Robust Detection and Severity Characterization of Gear Incipient Faults Under Variable Working Speed and Load. Machines. 2026; 14(1):9. https://doi.org/10.3390/machines14010009
Chicago/Turabian StyleBourdalos, Dimitrios M., and John S. Sakellariou. 2026. "A Machine Learning Vibration-Based Methodology for Robust Detection and Severity Characterization of Gear Incipient Faults Under Variable Working Speed and Load" Machines 14, no. 1: 9. https://doi.org/10.3390/machines14010009
APA StyleBourdalos, D. M., & Sakellariou, J. S. (2026). A Machine Learning Vibration-Based Methodology for Robust Detection and Severity Characterization of Gear Incipient Faults Under Variable Working Speed and Load. Machines, 14(1), 9. https://doi.org/10.3390/machines14010009