Gear Diagnostics Based On Transfer Learning Methodologies and Digital Twinning
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https://orcid.org/0009-0000-5935-2201
Konstantinos Gryllias
Abstract
This paper outlines the motivation for the research, reviewed the relevant SOTA in TL and CM, and identified some current research gaps. Moreover a dedicated test rig that will be used for methodological development and experimental validation has been described in detail. Finally, a structured research plan has been proposed, with the ultimate objective of developing a robust and scalable methodology combining ML and DTs for fault diagnostics of WT gearboxes, thereby contributing meaningfully to the field of PHM.
How to Cite
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Transfer Learning, Digital Twin, Condition Monitoring, Gear Diagnosis
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