A Remaining Useful Life Prediction Method for Aero-Engines Based on Degradation-Aware Masked Augmentation and a CNN–Transformer Hybrid Network
This study proposes a degradation-aware dynamic masking augmentation method combined with a multiscale CNN–Transformer network to address non-stationary monitoring data, limited informative degradation samples, and the difficulty of jointly modeling local degradation patterns and temporal dependencies.