TY  - JOUR 
AU  - Rodríguez Martín, Manuel
AU  - Fueyo, José G.
AU  - González Aguilera, Diego
AU  - Madruga, Francisco J.
AU  - García Martín, Roberto José
AU  - Muñoz Nieto, Ángel Luis
AU  - Pisonero Carabias, Javier
PY  - 2020
UR  - http://hdl.handle.net/10366/154937
AB  - [EN] The present article addresses a generation of predictive models that assesses the thickness
and length of internal defects in additive manufacturing materials. These modes use data from
the application of active transient thermography numerical...
LA  - spa
KW  - Active thermography
KW  - Finite element method
KW  - Termografía activa
KW  - Método de elementos finitos
TI  - Predictive Models for the Characterization of Internal Defects in Additive Materials from Active Thermography Sequences Supported by Machine Learning Methods
DO  - 10.3390/s20143982
T2  - Sensors
VL  - 20
M2  - 3982
ER  -