The framework learns damage-sensitive but variability-invariant representations from vibration signals via self-supervised autoencoding with VICReg regularization and frequency constraints.
A comparison of linear approaches to filter out environmental effects in structural health monitoring.Mechanical systems and signal processing 2018; 105: 1–15
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Disentangling Damage from Operational Variability: A Label-Free Self-Supervised Representation Learning Framework for Output-Only Structural Damage Identification
The framework learns damage-sensitive but variability-invariant representations from vibration signals via self-supervised autoencoding with VICReg regularization and frequency constraints.