Influence of CT image processing on the predicted impact of pores on fatigue of additively manufactured Ti6Al4V and AlSi10Mg

Pores are inherent to additively manufactured components and critical especially in technical components. Since they reduce the component's fatigue life, a reliable identification description of pores is vital ensure performance. X-ray computed tomography (CT) an established non-destructive testing method investigate internal defects. The CT scan process can induce noise artefacts resulting images which afterwards have be reduced through image processing. To reconstruct defects component, need segmented defect region bulk material by applying threshold. application threshold as well previous processing alter geometry size identified This contribution aims quantify influence selected commercial segmentation methods on several made AlSi10Mg Ti6Al4V artificial scan. that aim, gray value histograms characteristic parameters thereof compared for different tools. After processed images, particle characteristics compared. predicted life evaluated change largest pore each set data Murakami's empirical area $$ \sqrt{\mathrm{area}} -parameter model.