Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy
Arquivos
Data
2015
Autores
Albuquerque, Victor Hugo Costa de
Barbosa, Cleisson Vieira
Silva, Cleiton Carvalho
Moura, Elineudo Pinho de
Rebouças Filho, Pedro Pedrosa
Papa, João Paulo [UNESP]
Tavares, João Manuel Ribeiro da Silva
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Resumo
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 γ'' and δ 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.
Descrição
Palavras-chave
Metric function, Microstructural characterization, Optimum path forest, Signal classification, Ultrasonic sensor
Como citar
Sensors (Basel, Switzerland), v. 15, n. 6, p. 12474-12497, 2015.