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The effects of manual XCT focusing on extracted surface texture data

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X-Ray computed tomography, (XCT) has begun to prove itself as a valid method to quantify internal and external surface metrology of parts. However, the understanding of how a small change… Click to show full abstract

X-Ray computed tomography, (XCT) has begun to prove itself as a valid method to quantify internal and external surface metrology of parts. However, the understanding of how a small change in the capture settings of the XCT can affect the surface data extracted from parts needs to be developed so that like all metrology instruments the operating window in which the technology provides repeatable results with minimum uncertainty is understood. For XCT there exists a clear point of uncertainty in the measurement process, this being at the generation point of the x-rays, at this point the electron beam impacts a target material causing the generation of x-rays. As the intensity and size of the electron beam focal spot have direct control of the produced x-rays, it is important to align the filament in such a way that the best quality radiographs are generated. The more optimally focused each individually radiograph is in an XCT scan the better quality the 3D model acquired will be, thus leading to more representative surface data extraction. The present paper details an investigation into the effects of this focusing procedure on the extracted surface data. Further to this, the results of the study were compared to work showing the variation in extracted surface data resulting from a full filament change. The present study found that variance in extracted surface texture parameters resulting from beam refocussing exceeded that when comparing filaments, leading to the conclusion that the installation process is likely to be the main contributing factor to the variance noted in both studies.

Keywords: extracted surface; surface data; surface texture; xct; surface; metrology

Journal Title: Surface Topography: Metrology and Properties
Year Published: 2022

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