K. Gryllias

Physics-Informed Domain Generalization for Bearing Prognostics Under Unseen Operating Conditions

Modern condition-based maintenance of rotating machinery increasingly relies on data-driven prognostic models to estimate bearing health and remaining useful life (RUL). While machine-learning approaches have demonstrated strong performance under known operating conditions, their reliability often degrades under unseen...