Pulsed Thermography (PT) data are usually affected by noise and as such most of the research effort in the last few years has been directed towards the development of advanced signal processing methods to improve defect detection. Among the numerous techniques that have been proposed, principal component thermography (PCT)—based on principal component analysis (PCA)—is one of the most effective in terms of defect contrast enhancement and data compression. However, it is well-known that PCA can be significantly affected in the presence of corrupted data (e.g., noise and outliers). Robust PCA (RPCA) has been recently proposed as an alternative statistical method that handles noisy data more properly by decomposing the input data into a low-rank matrix and a sparse matrix. We propose to process PT data by RPCA instead of PCA in order to improve defect detectability. The performance of the resulting approach, Robust Principal Component Thermography (RPCT)—based on RPCA, was evaluated with respect to PCT—based on PCA, using a CFRP sample containing artificially produced defects. We compared results quantitatively based on two metrics, Contrast-to-Noise Ratio (CNR), for defect detection capabilities, and the Jaccard similarity coefficient, for defect segmentation potential. CNR results were on average 40% higher for RPCT than for PCT, and the Jaccard index was slightly higher for RPCT (0.7395) than for PCT (0.7010). In terms of computational time, however, PCT was 11.5 times faster than RPCT. Further investigations are needed to assess RPCT performance on a wider range of materials and to optimize computational time.

International audienceThis paper investigates thermography and shearography couplings, using feasibility trials and numerical simulations, for non-destructive control evaluations of bonding of carbon fiber-reinforced polymer plates glued over concrete structures. Those are well-known methods in non-destructive testing (NDT) applied to civil engineering, but in this context, they are seen as paired because they use the same excitation source: square-pulsed optical heating. Furthermore, because both methods are based on different properties, the detection of defects is optimised regardless of its nature or type. The combination of the methods allows the measurement of a thermal as well as a thermomechanical response from the structure at the same time. A quick review of those methods and their respective advantage and inconvenient is mentioned. An in-depth study of the interpretation of the thermal and mechanical responses is carried out in relation to the thermal excitation. Then, the thought process behind the conception of the finite element model and its limitation is discussed. The experimental setup, used for feasibility testing, is described as well as a thorough analysis of the experimental and simulated results. Finally, the pairing of both methods is discussed regarding the evaluation of the bond quality, as well as the similitude of the sample and its numerical model

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This study concern the use of a common thermal excitation for infrared thermography and shearographic measurements. The two NDT methods are used simultaneously to detect defects in the bonding between a concrete slab and a tissue of carbon fiber reinforced polymer (CFRP). Experimentation was conducted to evaluate defects depending on their size and simulated bonding quality. A numerical model was designed according to the experimental conditions. Obtained simulated results were compared with experimental data that allowed the validation of the numerical model. Analysis of the results shed some light on the relation between the thermal and mechanical response on defective samples.