Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/95114
Author(s): Victor Hugo C. de Albuquerque
Cleiton Carvalho Silva
Thiago Ivo de S. Menezes
Jesualdo Pereira Farias
João Manuel R. S. Tavares
Title: Automatic Evaluation of Nickel Alloy Secondary Phases from SEM Images
Issue Date: 2011
Abstract: Quantitative metallography is a technique to determine and correlate the microstructures of materials with their properties and behavior. Generic commercial image processing and analysis software packages have been used to quantify material phases from metallographic images. However, these all-purpose solutions also have some drawbacks, particularly when applied to segmentation of material phases. To overcome such limitations, this work presents a new solution to automatically segment and quantify material phases from SEM metallographic images. The solution is based on a neuronal network and in this work was used to identify the secondary phase precipitated in the gamma matrix of a Nickel base alloy. The results obtained by the new solution were validated by visual inspection and compared with the ones obtained by a commonly used commercial software. The conclusion is that the new solution is precise, reliable and more accurate and faster than the commercial software. Microsc. Res. Tech. 74:36-46, 2011. (C) 2010 Wiley-Liss, Inc.
Subject: Redes neuronais, Engenharia mecânica
Neural networks, Mechanical engineering
Scientific areas: Ciências da engenharia e tecnologias::Engenharia mecânica
Engineering and technology::Mechanical engineering
URI: https://repositorio-aberto.up.pt/handle/10216/95114
Document Type: Artigo em Revista Científica Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

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