Physically-Constrained Mamba-SDE for Remaining Useful Life Prediction under Irregular Observations
Researchers introduce PC-MambaSDE, a machine learning framework designed to predict remaining useful life in industrial equipment by combining continuous-time neural networks with physics-based constraints. The model handles irregular sensor data and prevents physically impossible degradation patterns, outperforming existing methods especially when observation data is sparse.