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

de Albuquerque VH, Barbosa CV, Silva CC, Moura EP, Filho PP, Papa JP, Tavares JM - Sensors (Basel) (2015)

Bottom Line: However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ'' and δ phases.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.

View Article: PubMed Central - PubMed

Affiliation: Programa de Pós-Graduação em Informática Aplicada, Universidade de Fortaleza, Fortaleza, Ceará 60811-905, Brazil. victor.albuquerque@unifor.br.

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 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.

No MeSH data available.


Spatial distribution of the samples of the (a) 4-MHz backscattered signals at 650 °C, (b) 950 °C and (c) of both temperatures together and of the (d) pulse echo signals at 650 °C, (e) 950 °C and (f) of both temperatures together.
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f1-sensors-15-12474: Spatial distribution of the samples of the (a) 4-MHz backscattered signals at 650 °C, (b) 950 °C and (c) of both temperatures together and of the (d) pulse echo signals at 650 °C, (e) 950 °C and (f) of both temperatures together.

Mentions: Figure 1 shows the PCA (principal component analysis) corresponding to the spatial distribution of the samples of the 4-MHz backscattered signals at 650 °C (Figure 1a), 950 °C (Figure 1b) and both temperatures together (Figure 1c), as well as for the background pulse echo signals for 650 °C (Figure 1d), 950 °C (Figure 1e) and both temperatures together (Figure 1f). Accordingly, it is possible to analyze the complexity during the difficult assignment of classifying the samples.


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

de Albuquerque VH, Barbosa CV, Silva CC, Moura EP, Filho PP, Papa JP, Tavares JM - Sensors (Basel) (2015)

Spatial distribution of the samples of the (a) 4-MHz backscattered signals at 650 °C, (b) 950 °C and (c) of both temperatures together and of the (d) pulse echo signals at 650 °C, (e) 950 °C and (f) of both temperatures together.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507598&req=5

f1-sensors-15-12474: Spatial distribution of the samples of the (a) 4-MHz backscattered signals at 650 °C, (b) 950 °C and (c) of both temperatures together and of the (d) pulse echo signals at 650 °C, (e) 950 °C and (f) of both temperatures together.
Mentions: Figure 1 shows the PCA (principal component analysis) corresponding to the spatial distribution of the samples of the 4-MHz backscattered signals at 650 °C (Figure 1a), 950 °C (Figure 1b) and both temperatures together (Figure 1c), as well as for the background pulse echo signals for 650 °C (Figure 1d), 950 °C (Figure 1e) and both temperatures together (Figure 1f). Accordingly, it is possible to analyze the complexity during the difficult assignment of classifying the samples.

Bottom Line: However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ'' and δ phases.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.

View Article: PubMed Central - PubMed

Affiliation: Programa de Pós-Graduação em Informática Aplicada, Universidade de Fortaleza, Fortaleza, Ceará 60811-905, Brazil. victor.albuquerque@unifor.br.

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 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.

No MeSH data available.