Microstructural Characterization of Eutectics using Digital Image Analysis

Abstract

AbstractMetallic eutectics play an important role in casting technology and properties. For this reason, the study of eutectics microstructure is indispensable in the casting qualification. Eutectics have many similar characteristics, including the morphology, size and spatial arrangement of eutectic phases. This makes it possible to develop a method of general use based on analyzing eutectic microscopy images. The method presented in this article performs a posteriori background correction for OM images. The shape and size of phases are determined using cellular automata and machine learning. Another cellular automaton and cluster analysis characterizes the spatial arrangement of eutectic phases. It can also be used to determine the distance between objects both locally and within a given object group. The algorithm is suitable for exploring and examining the spatial clustering of objects. The methods can be included in an algorithm, so a detailed examination of the eutectic microstructure can be carried out. The method was tested on micrographs of Al-Cu, Al-Ni, Al-Si and cast irons.