Shrinkage porosity is one of the defects that occurs in the manufacturing of components during solidification and insufficient feeding. This can significantly reduce the life duration of components by causing fatique stress. As a result, it is necessary to detect and evaluate the casting porosity. Typically, porosity evaluation has to be performed manually by experts. However, manual assessment is not reproducible method and time inefficient. Moreover, the task of determining whether different pores in a 2D cross section should be treated as a single connected pore in terms of an initial failure size for fracture mechanical assessment is difficult. Therefore, the used criteria such as the threshold distance between pores to be unified as a pore group or pore size metrics are needed to be examined, whether they are plausible and valid. Since only little work in automation of measuring defect sizes has been achieved so far, there is the demand to develop an automated tool for microstructural analysis of casting porosity.
In this paper, an automated defect size assessment method based on image processing techniques is presented. This method allows for a quicker, more cost-effective, and most
significantly, more consistent evaluation of porosity. Furthermore, the used criteria is validated through 3D renderings of sample materials. The results of this thesis provide the groundwork for follow-up projects to evaluate porosity effects on the fatigue life of components.
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Shrinkage porosity is one of the defects that occurs in the manufacturing of components during solidification and insufficient feeding. This can significantly reduce the life duration of components by causing fatique stress. As a result, it is necessary to detect and evaluate the casting porosity. Typically, porosity evaluation has to be performed manually by experts. However, manual assessment is not reproducible method and time inefficient. Moreover, the task of determining whether different p...
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