Determination of Vickers Hardness in D2 Steel and TiNbN Coating Using Convolutional Neural Networks

The study of material hardness is crucial for determining its quality, potential failures, and appropriate applications, as well as minimizing losses incurred during the production process. To achieve this, certain criteria must be met to ensure high quality. This process is typically performed manu...

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Autores:
Buitrago Diaz, Juan C.
Ortega-Portilla, Carolina
Mambuscay, Claudia L.
Piamba, 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:20.500.12313/5557
Acceso en línea:
https://hdl.handle.net/20.500.12313/5557
https://www.mdpi.com/2075-4701/13/8/1391
Palabra clave:
Redes Neuronales Convolucionales
Dureza Vickers en Acero D2
Recubrimiento TiNbN
Corner detection
D2 steel
Diagonal measurement
Indentation image analysis
Material hardness
Thermal treatment
Titanium niobium nitride (TiNbN) coating
Vickers hardness
Rights
openAccess
License
© 2023 by the authors.