Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy

• Autor(a) principal: Victor Hugo C. de Albuquerque
• Data de Publicação: 2015
• Outros Autores: Cleisson V. Barbosa, Cleiton C. Silva, Elineudo P. Moura, Pedro P. Rebouças Filho, João P. Papa, João Manuel R. S. Tavares
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://repositorio-aberto.up.pt/handle/10216/78879
• topic: Ciências Tecnológicas, Ciências da engenharia e tecnologias; Technological sciences, Engineering and technology

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.