Search Results (3)

This study comprehensively compares the performance of two non-destructive testing (NDT) techniques—active thermography (AT) and digital shearography (DS)—for identifying various damage types in composite structures. Three distinct composite specimens were inspected: a carbon-fiber-reinforced polymer (CFRP) plate with flat-bottom holes, an aluminum honeycomb core sandwich plate with a circular skin-core disbond, and a CFRP plate with two low-energy impacts damage. The research highlights the significant role of post-processing methods in enhancing damage detectability. For AT, algorithms such as fast Fourier transform (FFT) for temperature phase extraction and principal component thermography (PCT) for identifying significant temperature components were employed, generally making anomalies brighter and easier to locate and size. For DS, a novel band-pass filtering approach applied to phase maps, followed by summing the filtered maps, remarkably improved the visualization and precision of damage-induced anomalies by suppressing background noise. Qualitative image-based comparisons revealed that DS consistently demonstrated superior performance. The sum of DS filtered phase maps provided more detailed and precise information regarding damage location and size compared to both pulsed thermography (PT) and lock-in thermography (LT) temperature phase and amplitude. Notably, DS effectively identified shallow flat-bottom holes and subtle imperfections that AT struggled to clearly resolve, and it provided a more comprehensive representation of the impacts damage location and extent. This enhanced capability of DS is attributed to the novel phase map filtering approach, which significantly improves damage identification compared to the thermogram post-processing methods used for AT. Full article

In this article, optical excitation thermographic techniques, including pulsed thermography and lock-in thermography, were used to detect foreign object defect (FOD) and delamination in CFRP. Then, vibrothermography as an ultrasonic excitation technique was used to detect these defects for the comparative purposes. Different image processing methods, including cold image subtraction (CIS), principal component thermography (PCT), thermographic signal reconstruction (TSR) and Fourier transform (FT), were performed. Finally, a comparison of optical excitation thermography and vibrothermography was conducted, and a thermographic probability of detection was given. Full article

In this work a new gap-fill technique entitled projection transformation has been developed and used for filling missed parts of remotely sensed imagery. In general techniques for filling missed area of an image are broken down into three main categories: multi-source techniques that take the advantages of other data sources (e.g. using cloud free images to reconstruct the cloudy areas of other images); the second ones fabricate the gap areas using non-gapped parts of an image itself, this group of techniques are referred to as single-source gap-fill procedures; and third group contains methods that make up a combination of both mentioned techniques, therefore they are called hybrid gap-fill procedures. Here a new developed multi-source methodology called projection transformation for filling a simulated gapped area in the Landsat7/ETM+ imagery is introduced. The auxiliary imagery to filling the gaps is an earlier obtained L7/ETM+ imagery. Ability of the technique was evaluated from three points of view: statistical accuracy measuring, visual comparison, and post classification accuracy assessment. These evaluation indicators are compared to the results obtained from a commonly used technique by the USGS as Local Linear Histogram Matching (LLHM) [1]. Results show the superiority of our technique over LLHM in almost all aspects of accuracy. Full article