Microstructural Characterization of Eutectics using Digital Image Analysis

Metallic 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...

Full description

Saved in:
Bibliographic Details
Published in:Metallography, microstructure, and analysis microstructure, and analysis, 2024-10, Vol.13 (5), p.942-953
Main Authors: Bortnyik, Kornél, Gyöngyösi, Szilvia, Barkóczy, Péter
Format: Article
Language:English
Subjects:
Algorithms
Cast iron
Casting machines
Cellular automata
Characterization and Evaluation of Materials
Chemistry and Materials Science
Cluster analysis
Clustering
Digital imaging
Eutectics
Image analysis
Machine learning
Materials Science
Metallic Materials
Microstructure
Nanotechnology
Original Research Article
Phases
Photomicrographs
Structural Materials
Surfaces and Interfaces
Technology assessment
Thin Films
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Metallic 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.
ISSN:2192-9262
2192-9270
DOI:10.1007/s13632-024-01112-y