Determination of prior austenite grain-and martensitic substructure size from metallographic etchings using a multi-step image processing algorithm

Thomas Hönigmann, Dominik Christian Brandl, Martin Stockinger, Christian Gruber, Franziska Frois, Gerald Ressel

Research output: Contribution to journalArticleResearchpeer-review

Abstract

State-of-the-art modelling algorithms allowing for prediction of macroscopic properties of martensitic steels are primarily based on microstructural parameters such as prior austenite grain size as well as martensite packet-and block size distribution. The latter are usually obtainable via electron backscatter diffraction (EBSD) measurements. However, determination via light microscopy would present a more cost-effective determination method. This work presents a python-based multi-step image processing algorithm capable of separating the grain boundaries and the martensitic substructure from etched micrographs. Additionally, the viability of a characteristic mean free path parameter λ of the martensitic substructure for comparison of different martensitic microstructures is tested. To this end, a microstructure variation of PH15-5 was performed using different heat treatments and the specimens were analyzed using EBSD and electrolytically etched micrographs.
Translated title of the contributionGrößenbestimmung von ehemaligen Austenitkörnern und martensitischen Substrukturen mit Hilfe eines mehrstufigen Bildverarbeitungsalgorithmus anhand metallographischer Ätzungen
Original languageEnglish
Pages (from-to)386-404
Number of pages19
JournalPraktische Metallographie/Practical Metallography
Volume59.2022
Issue number7
DOIs
Publication statusPublished - 20 Jul 2022

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