A typical infrared (IR) thermographic system intended for active thermal/IR nondestructive testing includes a heat source, an IR imager and a computer. The software ensures acquisition and processing of IR image sequences to result in a binary map of defects or other image which is to be interpreted by a thermographer in order to meet inspection requirements. Typically, hardware developers supply a certain set of technical parameters of their units, such as heater power, imager temperature resolution, acquisition rate and a set of available data processing algorithms. The suggested approach allows optimization of inspection parameters if thermal and optical parameters of test materials are known.
In this paper, we investigate the fusion of imaging data from pulsed phase thermography (PPT) with local temperature data obtained from embedded fiber Bragg grating (FBG) sensors for non-destructive evaluation of composite structures. We use the square pulse heating applied for the PPT imaging as the input thermal wave for both the imaging and sensing processes. In addition, the role of the local microstructure surrounding the FBG on the measured wavelength shift as a function of temperature is derived analytically. Fusing the FBG wavelength response with the PPT data at the corresponding pixel and depth is shown to provide a unique characterization of the local material condition.
In this paper we investigate the performance of defect detection using long duration transient thermography for woven
composite laminates subjected to low-velocity impacts. Two types of defects are studied: inclusions represented by foam
tabs inserted into the laminate during fabrication and barely visible impact damage due to low-velocity impacts. These
defects represent the expected damage states that are necessary for inspection during the service life of a woven
composite aircraft component. The long duration transient thermography is demonstrated to successfully detect the
embedded inclusions, with a dimension to depth ratio detection capability of approximately 3. It is also demonstrated
that the detection of low velocity impact damage with the transient thermography is less successful due to uneven emissivity of the surface. Therefore, processing of the image using a self referencing algorithm is performed which improves the damage detection clarity.
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