Applying the heat conduction-based 3D normalization and thermal tomography to pulsed infrared thermography for defect characterization in composite materials. (March 2016)

• Record Type: Journal Article
• Authors: Pawar, S.S.; Vavilov, V.P.
• Is Part Of: International journal of heat and mass transfer. Volume 94(2016:Mar.)
• Page Start: 56
• Page End: 65
• Publication Date: 2016-03
• Subjects: Normalization -- Thermal nondestructive testing -- 3D heat conduction -- Composites -- Tomography -- Modeling; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2015.11.018
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: We developed a novel 3D normalization approach by using heat conduction model. It was applied for characterization of different types of defects in composites. The approach improved defect detection by reducing uneven heating phenomenon. 3D normalized tomography increased the number of material resolved layers. Abstract: Active infrared (IR) thermography is a non-contact, fast and wide-area nondestructive testing (NDT) technique that has been increasingly used in aerospace applications to detect both manufacturing and in-service environment-induced defects. The classical pulsed IR thermographic testing suffers from the problem of false indications due to surface clutter conditioned by uneven optical properties across a test sample surface. To some extent, this problem can be relaxed by using a technique called 'normalization'. A simple normalization algorithm, conventionally called 1D, involves the division of all images in a sequence by a chosen single image, often captured immediately after a flash. The novel technique of 3D normalization is implemented in this study to overcome the problems arising due to non-uniform heating and lateral heat diffusion in the case of pulsed IR thermographic NDT. In this case, normalization is carried out by dividing an experimental IR image sequence by the synthetic sequence which is calculated by solving the corresponding 3D problem of heat conduction. As a result of 3D normalization, the artefacts appearing due to uneven heating and absorption can be subdued through data normalization (division). Furthermore, fully automatic defect detection becomes possible as defining a reference point for sound area is not required as opposed to thermal contrast methods. In this work, the effectiveness of proposed 3D normalization approach is demonstrated for different heating conditions applied to glass and carbon fiber reinforced composites.