Experimental Characterization and Non-Linear Dynamic Modelling of PCD Bearings: A Digital-Twin Approach for the Condition Monitoring of Rotating Machinery.

This study proposes a comprehensive methodology for the experimental characterization and non-linear dynamic modelling of Polycrystalline Diamond (PCD) bearings, establishing a high-fidelity digital twin approach for the condition monitoring of rotating machinery. The research addresses complex rotor-stator interactions through the development of a multibody numerical framework. A structural 1D Finite Element (FE) model of the stator assembly was first calibrated via experimental modal analysis, achieving a high correlation with the first four bending modes and a maximum frequency discrepancy of only 1.4%. This validated structure was integrated into a non-linear multibody environment to simulate transient rub-impact events at rotational speeds up to 5500 rpm across varying clearance configurations. The model successfully captures the transition from stable periodic orbital motion to the stochastic and chaotic regimes observed in high-clearance setups. Frequency-domain validation further confirms the model's accuracy in identifying supersynchronous harmonics and energy distribution patterns. Quantitative analysis shows that high-clearance configurations generate impact forces exceeding 6000 N, providing critical data for structural health assessment. These results demonstrate that the proposed digital twin serves as a robust physical foundation for diagnostic systems, enabling the identification of contact-induced vibrational signatures that are essential for training prognostic algorithms. This approach facilitates the autonomous monitoring of critical rotating machinery in demanding industrial and subsea applications, supporting the transition toward active balancing and model-based vibration control strategies.