Bearing Spall Detection and Remaining Useful Life Prediction Using an Operational Binning Approach for eVTOLs

This paper presents a novel approach for bearing spall detection and Remaining Useful Life (RUL) prediction in electric vertical takeoff and landing (eVTOL) aircraft. By leveraging vibration-based signals and an operational binning methodology, a robust Health Index (HI) is developed using angular resampling-based order analysis. This HI accounts for varying operational conditions, providing a reliable indicator of bearing degradation. A piecewise Bayesian degradation model is then applied to predict RUL, facilitating effective predictive maintenance and enhancing eVTOL operations.