A physics-informed GNN-transformer model performs unsupervised modal decomposition and identification for populations of structures from sparse dynamic measurements.
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VFM-SDM enables accurate multi-directional structural displacement measurement from video using pre-trained vision models for camera estimation and point tracking, combined with geometry constraints, without task-specific training or preparation.
An operator-based Energy Concentration Index yields the IMRED detector that identifies defect-induced changes in impulse responses with AUC 0.908, outperforming standard Fourier and wavelet energy measures.
citing papers explorer
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Modal Decomposition and Identification for a Population of Structures Using Physics-Informed Graph Neural Networks and Transformers
A physics-informed GNN-transformer model performs unsupervised modal decomposition and identification for populations of structures from sparse dynamic measurements.
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VFM-SDM: A vision foundation model-based framework for training-free, marker-free, and calibration-free structural displacement measurement
VFM-SDM enables accurate multi-directional structural displacement measurement from video using pre-trained vision models for camera estimation and point tracking, combined with geometry constraints, without task-specific training or preparation.
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Operator-Theoretic Energy Functionals for Impulse-Excited Nonstationary Signal Analysis
An operator-based Energy Concentration Index yields the IMRED detector that identifies defect-induced changes in impulse responses with AUC 0.908, outperforming standard Fourier and wavelet energy measures.