Mohamed Abdellilah Fidma

Self-Supervised Contrastive Learning for Online Damage Detection in Bridge Acceleration Signals

Structural Health Monitoring (SHM) increasingly relies on data-driven methods applied to dense vibration measurements, however, reliable damage detection from acceleration time series remains challenging due to environmental variability, limited labeled damage data, and severe class imbalance. This work investigates se...