Authors:
Florian Kerber | TU Bergakademie Freiberg | Germany
Dr. Marc Neumann | TU Bergakademie Freiberg | Germany
Dr. Jana Hubálková | TU Bergakademie Freiberg | Germany
Dr. Gert Schmidt | TU Bergakademie Freiberg | Germany
Dr.-Ing. Thomas Schemmel | Refratechnik Steel GmbH | Germany
Dr. Volker Stein | Refratechnik Steel GmbH | Germany
Prof. Dr.-Ing. habil. Helge Jansen | Refratechnik Steel GmbH | Germany
Prof. Dr.-Ing. habil. Christos G. Aneziris | TU Bergakademie Freiberg | Germany
Since decades the presence of non-metallic inclusions within steel products is of high interest and because of their detrimental impact on the processing technologies and the properties of fabricated metallic components, their population has to be under complete control. Therefore, suitable characterization methods for non-metallic inclusions are indispensable. One of them, presented in this work, is automated feature analysis, which automatically determines non-metallic inclusions based on grayscale differences by an automated scanning electron microscope. However, to achieve the greatest possible benefit from this method, proper data evaluation and interpretation of the obtained raw data is required. Therefore, within this study automated feature analysis is exemplified for determining the inclusion population within steel samples after contact with different MgO-C refractory materials. Thereby, opportunities and limitations of the method are highlighted. Moreover, the study presents approaches for investigating an unknown inclusion population in terms of present inclusion species and inclusion size distributions and thus, is a guideline for the application of automated feature analysis in inclusion analysis.