Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/78879
Author(s): Victor Hugo C. de Albuquerque
Cleisson V. Barbosa
Cleiton C. Silva
Elineudo P. Moura
Pedro P. Rebouças Filho
João P. Papa
João Manuel R. S. Tavares
Title: Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy
Issue Date: 2015
Abstract: Secondary phases, such as laves and carbides, are formed during the finalsolidification stages of nickel-based superalloy coatings deposited during the gas tungstenarc welding cold wire process. However, when aged at high temperatures, other phases canprecipitate in the microstructure, like the 00 and phases. This work presents an evaluationof the powerful optimum path forest (OPF) classifier configured with six distance functionsto classify background echo and backscattered ultrasonic signals from samples of the inconel625 superalloy thermally aged at 650 and 950 C for 10, 100 and 200 h. The backgroundecho and backscattered ultrasonic signals were acquired using transducers with frequenciesof 4 and 5 MHz. The potentiality of ultrasonic sensor signals combined with the OPF tocharacterize the microstructures of an inconel 625 thermally aged and in the as-welded condition were confirmed by the results. The experimental results revealed that the OPFclassifier is sufficiently fast (classification total time of 0.316 ms) and accurate (accuracy of88.75% and harmonic mean of 89.52) for the application proposed.
Subject: Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
Scientific areas: Ciências da engenharia e tecnologias
Engineering and technology
URI: https://repositorio-aberto.up.pt/handle/10216/78879
Document Type: Artigo em Revista Científica Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

Files in This Item:
File Description SizeFormat 
101818.pdfPaper621.79 kBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons