A Fourier-transformed, Helmholtz-style physics-informed neural network reconstructs 3D internal temperature fields with hidden defects from surface thermography data, beating the authors' time-domain PINN baseline.
Thermographic data analysis for defect detection by imposing spatial connectivity and sparsity constraints in principal component thermography,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.app-ph 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Making neural networks understand internal heat transfer using Fourier-transformed thermal diffusion wave fields
A Fourier-transformed, Helmholtz-style physics-informed neural network reconstructs 3D internal temperature fields with hidden defects from surface thermography data, beating the authors' time-domain PINN baseline.