The framework learns damage-sensitive but variability-invariant representations from vibration signals via self-supervised autoencoding with VICReg regularization and frequency constraints.
Multi-mode fault diagnosis datasets of gearbox under variable working conditions.Data in brief 2024; 54: 110453
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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.