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Neural network for classification of MnS microinclusions in steels

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Author(s):
de Oliveira Filho, Marcos Fernando ; Caradec, Pierre D'Amelio Briquet ; Calsaverini, Rafael ; Spinelli, Jose Eduardo ; Ishikawa, Tomaz Toshimi
Total Authors: 5
Document type: Journal article
Source: JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T; v. 24, p. 11-pg., 2023-05-24.
Abstract

The influence of MnS inclusions on steel properties is highly noticeable. For instance, higher severity levels of inclusions are associated with lower mechanical properties and a higher risk of failure in service. Manual inclusions classification methods are the most used in laboratories and metallurgical sector industries because of their low cost, while auto-matic methods have high operating costs, which makes their use more restrict. Neural network models, on the other hand, are extremely advantageous for several applications. The present study is motivated by the use of a neural network model for classifying in-clusions in steels. The aim is to achieve the highest possible accuracy in classifying the MnS inclusions severities (0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and 4.5) using optical images captured from steel specimens. The results have showed that the classification of MnS severities was very sensitive to the database number of images. A 98% training accuracy was obtained by increasing the number of images from 3,156 to 4,136, mostly adding im-ages for some severity levels. However, validation and test results were not satisfactory. As such, a severity re-categorization of the database was able to enhance the true positive values, with an error of 8%. In general, the neural network represented speed in decision making, proving to be a potential tool for classifying steel inclusions.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). (AU)

FAPESP's process: 21/08436-9 - Electromigration and 4D microtomography in Sn-Bi-In thermal joints
Grantee:José Eduardo Spinelli
Support Opportunities: Scholarships abroad - Research
FAPESP's process: 19/23673-7 - Evaluation of alloys for thermal interface contact and for additive manufacturing
Grantee:José Eduardo Spinelli
Support Opportunities: Regular Research Grants