Matthias Hemmleb (Halle (Saale) / DE), Dirk Bettge (Berlin / DE), Lennart Schmies (Berlin / DE), Ulrich Sonntag (Berlin / DE), Benny Botsch (Berlin / DE)
Abstract text (incl. figure legends and references)
The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience.
In the IGF project "iFrakto", software is being developed that quantitatively determines fracture characteristics and fracture mechanisms utilizing digitized expert knowledge, machine learning, and standard 2D and topographical data from SEM imaging. Topographical data are obtained from 4QBSE detector using shape-from-shading technology (Fig. 1). The developed software tool provides knowledge-based suggestions for the evaluation of fracture surfaces (Fig. 2). As a basis for this, round robins were carried out among fractographers to create a knowledge base, to query the practice-relevant requirements for such tools and to carry out first practical tests.
The approach described can be used with all scanning electron microscopes. The results presented here were generated with a Tescan Vega3 and the BSE detector based topography measurement system DISS6 from point electronic GmbH. The investigations were mainly carried out on various metallic fracture surfaces.
The results show that the use of machine learning software together with SEM image and topography data makes an important contribution to the quantification of fracture surfaces and effectively supports the operator in the interpretation of fracture surfaces.