Enhanced method for flaws depth estimation in CFRP slabs from FDTC thermal contrast sequences

After the detection of internal defects in materials, the characterization of these plays a decisive role in order to establish the severity of these flaws. Finite difference thermal contrast (FDTC) is a new technique proposed recently for contrast enhancement in sequences of thermal images in order...

Full description

Autores:
Restrepo Girón, Andrés David
Tipo de recurso:
Article of journal
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/67648
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/67648
http://bdigital.unal.edu.co/68677/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
Pulsed thermography
composite materials
thermal contrast
FDTC.
Termografía pulsada
materiales compuestos
contraste térmico
CTDF.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:After the detection of internal defects in materials, the characterization of these plays a decisive role in order to establish the severity of these flaws. Finite difference thermal contrast (FDTC) is a new technique proposed recently for contrast enhancement in sequences of thermal images in order to allow the detection of internal flaws in composite slabs with greater probability of success. Besides FDTC, a criterion was also conceived for the estimation of the depth of the detected defects, which brings good results for shallow and strong contrast defects, but poor estimations for deeper and weaker defects. Considering this problem, a revision of the original criterion is carried out in this paper to define a new and robust criterion for estimating the depth of defects, applied after FDTC en-hancement and flaws detection. Results of the execution of the revised algorithm on a synthetized thermal sequence from an artificial CFRP slab (using ThermoCalc6L software) show a better performance of the estimation task, reducing the average relative error by more than half.