ORALS

Microcomputed Tomography has become a powerful and widely used tool for non-destructive testing and can be used for mapping the complex 3D structures of cracks and their interactions. The materials of most oil and gas transport pipes, buried or submerged, such as high strength low alloy steels, for example, are likely to suffer corrosion, degradation and fracture due to the corrosive environment. Similarly, cracks are one of the most severe types of discontinuities in a welded joint because they are strong stress concentrators. High tensile stresses develop in the weld region as a result of the localized thermal expansion and contraction associated with the welding thermal cycle. To better characterize the cracking behavior, it is important to gain information about the evolution of the 3D crack network. The search for improving image quality in the inspection of steel samples using X-ray beams, however, is still challenging because of spreading effects that can cause noise in the 3D image. For this purpose, we performed microCT tests to verify cracks due to corrosion, loss of weld adhesion, and cracks applying to mathematical filters to improve the final image quality. To enhance details of the greyscale micro-CT image, the image was filtered using anisotropic diffusion (AD) and unsharp mask (UM) filters [1], which have been found to be highly effective for enhancement of digital fractured media [2,3]. AD is an edge-preserving noise reduction filter that has been shown to enhance the signal-to-noise ratio of tomographic images in a variety of contexts while preserving edges [4]. UM is highly effective at sharpening edges without excessively strengthening the noise [1]. It was possible to verify cracks around 0.66 mm for corrosion cracks and 2.67 mm for cracks due to loss of weld adhesion. Also, observation of the continuities of the cracks in the 3D visualization of the inspected materials was possible.

References:
[1] A.P. Sheppard, R.M. Sok, H. Averdunk Techniques for image enhancement and segmentation of tomographic images of porous materials Phys. A: Stat. Mech. Appl., 339 (2004), pp. 145-151
[2] H.L. Ramandi, P. Mostaghimi, R.T. Armstrong Digital rock analysis for accurate prediction of fractured media permeability J. Hydrol., 554 (2017), pp. 817-826
[3] H.L. Ramandi, M. Liu, S. Tadbiri, P. Mostaghimi Impact of dissolution of syngenetic and epigenetic minerals on coal permeability Chem. Geol. (2018)
[4] R.C. Gonzales, R.E. Woods Digital Image Processing
(3rd edition ed.), Addison & Wesley Publishing Company, MA(1987)