Depth Retrieval Procedures in Pulsed Thermography: Remarks in Time and Frequency Domain Analyses

Abstract

Featured Application: The present study intends to show the potentiality of pulsed thermographic imaging to quantitatively characterise hidden defects in Carbon Fibre Reinforced Polymers. By comparing the performance of different depth retrieval procedures, it was possible to evaluate the produced depth estimation accuracy and to define the impact of different experimental and analysis parameters in quantitative analysis. Abstract:In the present study, a Carbon Fibre Reinforced Polymer (CFRP) sample of trapezoid shape, consisting of internal artificial delaminations of various sizes and depth locations, is investigated by means of optical pulsed thermography for the retrieval of quantitative depth information. The main objectives of this work are to evaluate the produced depth estimation accuracy from two contrast-based depth inversion procedures as well as to correlate the acquired results with characteristics such as the location and size of the detected features and with analysis parameters such as the selection of the sound area. Quantitative analysis is performed in both the temporal and frequency domains, utilising, respectively, the informative parameters of thermal contrast peak slope time and blind frequency. The two depth retrieval procedures are applied for the depth estimation of features ranging in size from 3 mm to 15 mm and in depth from 0.2 mm to 1 mm. The results of the present study showed that the two different analyses provided efficient depth estimations, with frequency domain analysis presenting a greater accuracy. Nevertheless, predicting errors were observed in both cases and the factors responsible for these errors are defined and discussed.

Adaptive spectral band integration in flash thermography: Enhanced defect detectability and quantification in composites

“…However, the selection of such a reference pixel is often non-trivial since it requires a priori information about the sample and its defects. As a practical alternative, the average phase value of the entire sample can also be used as reference value [28]. In this paper, the phase contrast is calculated according to the latter manner.…”

“…On the other hand, in the field of ultrasonic NDT, the drop technique is a standard technique for defect size estimation, in which a defect is sized by applying a cut-off at a specific percentage of the defect's maximum amplitude [25][26][27]. For FT, several procedures for defect depth estimation have been introduced [21,[28][29][30][31][32][33][34], most of which rely on the idealized 1D solution for the heat diffusion equation or on artificial neural networks. With respect to PPT, it is known that there does not exist an unambiguous relationship between the phase angle and the defect depth [30], which means that individual phase (contrast) images cannot be used for proper depth inversion.…”

An Experimental Study on the Defect Detectability of Time- and Frequency-Domain Analyses for Flash Thermography

“…In contrast, the present approach focuses on a systematic search of the maximum phase contrast and its corresponding frequency, analogous to DTT. The phase contrast was calculated by either subtracting the phase profile of a single known sound pixel, the mean phase value of a known sound area, or the mean phase value of the entire inspected sample, from the phase profile of every pixel [36]. In this study, the phase contrast was calculated by the latter approach.…”

Special Issue on ‘Novel Ideas for Infrared Thermography and Its Application to Integrated Approaches’

“…The results showed that the two different analyses provided efficient depth estimations, with frequency domain analysis demonstrating greater accuracy. Finally, predicting errors were observed in both cases and the factors responsible for these errors were defined and discussed [23].…”