This article presents the development of an active thermography algorithm capable of detecting defects in materials, based on the techniques of Thermographic Signal Reconstruction (TSR), Thermal Contrast (TC) and the physical principles of heat transfer. The results obtained from this algorithm are compared to the TSR technique and the raw thermogram obtained by stepped thermography inspection. Experimentally, a short thermal pulse is used and the surface temperature of the sample is monitored over time with an infrared camera. Due to the volume of data, the first step is data compression. Newton’s law of cooling was used to store the normalized temperature data pixel-by-pixel over time and a compression ratio of 99% was obtained. The main contributions of the developed algorithm are: only four parameters for data compression and the concept of change in the direction of the heat flow to delimit the edges of the defects, where the borders are identified with a remarkable accuracy. Some well known image processing technique are also integrated to improve the thermal analysis: edge detection/interface between the sample and the image background; consolidation in a single image by aggregating the indicators referring to the concept of cooling/heating time constant, maximum thermal amplitude and contrast.

The use of anticorrosive coatings has been a powerful method to be applied on the surface of metallic materials to mitigate the corrosive process. In this study, the focus is composite coatings that are commonly used on the internal surface of storage tanks in petrochemical industries. The development of non-destructive methods for inspection of faults in this field is desired due to unhealthy access and mainly because undercoating corrosion is difficult to detect by visual inspection. Pulsed thermography (PT) was employed to detect undercoating corrosion and adhesion loss of anticorrosive composite coatings defects. Additionally, a computational simulation model was developed to complement the PT tests. According to the experimental results, PT was able to detect all types of defects evaluated. The results obtained by computational simulation were compared with experimental ones. Good correlation (similarity) was verified, regarding both the defect detection and thermal behavior, validating the developed model. Additionally, by reconstructing the thermal behavior according to the defect parameters evaluated in the study, it was estimated the limit of the remaining thickness of the defect for which it would be possible to obtain its detection using the pulsed modality.

Thermoplastic composite pipes (TCPs) have potential applications in offshore oil and gas industries because of their strength, lack of corrosion, and flexibility. Designed for fluid transportation in high‐pressure and high‐temperature environments, manufacturing defects and operational loads can compromise their performance. However, their material composition and thickness make conventional non‐destructive testing (NDT) methods ineffective, highlighting a gap in the literature on suitable inspection techniques. This study aims to evaluate the effectiveness of the pulse‐echo ultrasound technique and X‐ray microtomography (micro‐CT) in detecting defects in TCPs. Two samples were analyzed, each consisting of two outer layers of PVDF and an inner layer of carbon fiber‐reinforced PVDF. The layer thicknesses, from outer to inner, measured 5.74, 18.86, and 4.48 mm. Based on the evaluated samples and the results obtained, the pulse‐echo technique proved effective in detecting defects at depths of up to 18 mm, as well as their corresponding locations in the samples. Micro‐CT provided a three‐dimensional representation of the discontinuities, offering detailed insights into the spatial distribution and connectivity of structural delaminations. The combination of the analyses conducted using these two non‐destructive techniques becomes a valuable tool for evaluating their impact on the mechanical performance of TCPs.

In offshore operations, lines that circulate seawater are considered critical, as they are highly susceptible to severe internal corrosion damage. To mitigate the issues caused by corrosion, the application of internal coatings, such as HDPE, in carbon steel pipelines has become a widely adopted practice within the industry. To assess the integrity of pipelines with internal HDPE coating, the objective of this work was to develop a non-destructive inspection system employing ultrasound to identify the coating integrity. Based on the results obtained from the A-scan signal analysis, differences were observed in the signal behavior between regions where the HDPE coating was disbonded and regions where the coating remained intact. The developed system was also applied to monitor corrosion in pipelines where the internal coating was no longer present due to disbondment. Based on the proposed methodology, it was possible to monitor the variation in pipeline wall thickness as a result of the corrosion process induced by the internal fluid.