Quantitative analysis of thermographic data through different algorithms

Abstract 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. It was necessary to process the raw thermal data acquired to obtain a series of satisfactory results for a correct and quantitative material evaluation. In the last years, many data processing algorithms have been developed and each of them provide enhanced detection and sizing of flaws. In this work, starting from the same brief pulsed thermographic test carried out on an aluminium specimen with twenty flat bottom holes of known nominal size, different algorithms have been compared. The algorithms used have been: Pulsed Phase Thermography (PPT), Slope, Correlation Coefficient (R 2 ), Thermal Signal Reconstruction (TSR), Principal Component Analysis (PCT). By analysing the results obtained using different approaches, it was possible to focus on the advantages, disadvantages and sensitivity of the various thermographic algorithms implemented.