Pulsed thermography is commonly used as a non-destructive technique for evaluating defects within materials and components. In the last few years, many algorithms have been developed with the aim to detect defects and different methods have been used for detecting their size and depth. However, only few works in the literature reported a comparison among the different algorithms in terms of the number of detected defects, the time spent in testing and analysis, and the quantitative evaluation of size and depth. In this work, starting from a pulsed thermographic test carried out on an aluminum specimen with twenty flat bottom holes of known nominal size and depth, different algorithms have been used with the aim to obtain a comparison among them in terms of signal to background contrast (SBC) and number of detected defects by analyzing different time intervals. Moreover, the correlation between SBC and the aspect ratio of the defects has been investigated. The algorithms used have been: Pulsed Phase Thermography (PPT), Slope, Correlation Coefficient (R2), Thermal Signal Reconstruction (TSR) and Principal Component Thermography (PCT). The results showed the advantages, disadvantages, and sensitivity of the various thermographic algorithms.

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Additive manufacturing (AM) technologies, generally called 3D printing, are widely used because their use provides a high added value in manufacturing complex-shaped components and objects. Defects may occur within the components at different time of manufacturing, and in this regard, non-destructive techniques (NDT) represent a key tool for the quality control of AM components in many industrial fields, such as aerospace, oil and gas, and power industries. In this work, the capability of active thermography and eddy current techniques to detect real imposed defects that are representative of the laser powder bed fusion process has been investigated. A 3D complex shape of defects was revealed by a µCT investigation used as reference results for the other NDT methods. The study was focused on two different types of defects: porosities generated in keyhole mode as well as in lack of fusion mode. Different thermographic and eddy current measurements were carried out on AM samples, providing the capability to detect volumetric irregularly shaped defects using non-destructive methods.

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Pulsed thermography is commonly used as non-destructive technique for evaluating defects within materials and components. However, raw thermal imaging data are usually not suitable for quantitative evaluation of defects. Many data processing algorithms have been developed and each of them provide enhanced detection and sizing of researched defects. In this work, two algorithms have been investigated: Slope, Square of the Correlation Coefficient (R 2 ). The aim of this work is to compare these algorithms with the well-established Pulse Phase thermography technique in terms of defects detectability.