Exploring the Impact of Pre-Mechanical Activation of Nickel Powder on the Structure of Deposited Metal: A Deep Neural Network Perspective

Malashin Ivan; Kobernik Nikolay; Pankratov Alexandr; Andriyanov Yuri; Aleksandrova Vitalina; Tynchenko Vadim; Nelyub Vladimir; Borodulin Aleksei; Gantimurov Andrei; Martysyuk Dmitry; Galinovsky Andrey

Дополнительные ссылки: eLibrary

База данных: Каталог библиотеки СФУ

Библиографическое описание: Exploring the Impact of Pre-Mechanical Activation of Nickel Powder on the Structure of Deposited Metal: A Deep Neural Network Perspective : научное издание / I. I. Malashin [et al.]. - Текст : непосредственный // Metals. - 2024. - Т. 14, № 8. - P. 929. - ISSN 2075-4701, DOI 10.3390/met14080929.

Аннотация: This study explores the potential application of the mechanical activation (MA) of nickel powder for incorporation into the composition of powder wire blends for the deposition of wear-resistant coatings. Nickel powder of PNE-1 grade was processed in a vibrational mill for various durations (4 to 16 min) with different combinations of grinding media. The influence of MA parameters on the bulk density and apparent particle size of nickel powder was investigated. The greatest effect was observed at the maximum processing time of 16 min, where electron microscopy revealed significant deformation and an increase in discoid particles, leading to enhanced energy accumulation. Nickel powder processed with a combination of 6 balls that are 20 mm in diameter and 8 balls that are 10 mm in diameter showed significant changes, though no major alteration in chemical composition was noted. XRMA indicated that the powder’s surface was partially covered with oxides, with a composition of 96.8–98.4% Ni and 0.8–1.7% O2. Additionally, the effect of nickel powders after the treatment on the structure of deposited metal was determined, demonstrating alterations in the morphology and a slight increase in hardness. Furthermore, a convolutional neural network (CNN)-based approach was proposed to discern fragments within images depicting surface microstructures, both with and without MA.

Год издания: 2024

Авторы: Malashin Ivan , Kobernik Nikolay , Pankratov Alexandr , Andriyanov Yuri , Aleksandrova Vitalina , Tynchenko Vadim , Nelyub Vladimir , Borodulin Aleksei , Gantimurov Andrei , Martysyuk Dmitry , Galinovsky Andrey

Издательство: MDPI AG

Источник: Metals

Выпуск: Т. 14, № 8

Номера страниц: 929

Держатель оригинала документа: Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia, Center NTI “Digital Materials Science: New Materials and Substances”, Bauman Moscow State Technical University, 105005 Moscow, Russia, Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia, Welding and Control Scientific and Educational Center at Bauman Moscow State Technical University, 105005 Moscow, Russia

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Exploring the Impact of Pre-Mechanical Activation of Nickel Powder on the Structure of Deposited Metal: A Deep Neural Network Perspective
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