Automatic Method for Vickers Hardness Estimation by Image Processing

Hardness is one of the most important mechanical properties of materials, since it is used to estimate their quality and to determine their suitability for a particular application. One method of determining quality is the Vickers hardness test, in which the resistance to plastic deformation at the...

Full description

Autores:
Polanco, Jonatan D.
Jacanamejoy-Jamioy, Carlos
Mambuscay, Claudia L.
Piamba Jiménez, Jeferson Fernando
Forero, Manuel G.
Tipo de recurso:
Article of investigation
Fecha de publicación:
2023
Institución:
Universidad de Ibagué
Repositorio:
Repositorio Universidad de Ibagué
Idioma:
eng
OAI Identifier:
oai:repositorio.unibague.edu.co:20.500.12313/5540
Acceso en línea:
https://hdl.handle.net/20.500.12313/5540
https://www.mdpi.com/2313-433X/9/1/8
Palabra clave:
Procedimiento de imágenes
Mecánica de materiales
Acero - Tratamiento térmico
Hardness estimation
Image processing
Mechanics of materials
Steel heat treating
Vickers hardness
Rights
openAccess
License
© 2022 by the authors.
Description
Summary:Hardness is one of the most important mechanical properties of materials, since it is used to estimate their quality and to determine their suitability for a particular application. One method of determining quality is the Vickers hardness test, in which the resistance to plastic deformation at the surface of the material is measured after applying force with an indenter. The hardness is measured from the sample image, which is a tedious, time-consuming, and prone to human error procedure. Therefore, in this work, a new automatic method based on image processing techniques is proposed, allowing for obtaining results quickly and more accurately even with high irregularities in the indentation mark. For the development and validation of the method, a set of microscopy images of samples indented with applied forces of (Formula presented.) and (Formula presented.) on AISI D2 steel with and without quenching, tempering heat treatment and samples coated with titanium niobium nitride (TiNbN) was used. The proposed method was implemented as a plugin of the ImageJ program, allowing for obtaining reproducible Vickers hardness results in an average time of (Formula presented.) seconds with an accuracy of (Formula presented.) and a maximum error of (Formula presented.) with respect to the values obtained manually, used as a golden standard.