Please use this identifier to cite or link to this item: http://www.repositorio.ufc.br/handle/riufc/44675
Title in Portuguese: Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy
Author: Albuquerque, Victor Hugo Costa de
Barbosa, Cleisson Vieira
Silva, Cleiton Carvalho
Moura, Elineudo Pinho de
Rebouças Filho, Pedro Pedrosa
Papa, João Paulo
Tavares, João Manuel Ribeiro da Silva
Keywords: Ligas - Tecnologia
Metric function
Optimum path forest
Signal classification
Ultrasonic sensor
Issue Date: 2015
Publisher: Sensors
Citation: ALBUQUERQUE, V. H. C. et. al. Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy. Sensors, v. 15, n. 6, p. 12474-12497
Abstract: Secondary phases, such as laves and carbides, are formed during the final solidification stages of nickel-based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the 00 and phases. This work presents an evaluation of the powerful optimum path forest (OPF) classifier configured with six distance functions to classify background echo and backscattered ultrasonic signals from samples of the inconel 625 superalloy thermally aged at 650 and 950 C for 10, 100 and 200 h. The background echo and backscattered ultrasonic signals were acquired using transducers with frequencies of 4 and 5 MHz. The potentiality of ultrasonic sensor signals combined with the OPF to characterize 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 OPF classifier is sufficiently fast (classification total time of 0.316 ms) and accurate (accuracy of 88.75% and harmonic mean of 89.52) for the application proposed.
URI: http://www.repositorio.ufc.br/handle/riufc/44675
metadata.dc.type: Artigo de Periódico
ISSN: 1424-8220
Appears in Collections:DEME - Artigos publicados em revista científica

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