Identification of Phase Transformations in Alloy and Non-Alloy Steel During Austempering Using Acoustic Emission and Neural Network

This research was carried out for selected alloy (bearing) and non-alloy (tool) steel. The steels were subjected to austempering. The hardening temperature range was from 100 °C to 180 °C. The use of acoustic emission in connection with the artificial neural network (ANN) enabled the analysis and identification of phase changes occurring in steels during austempering. Classification of acoustic emission events was carried out with the help of their energy values and with the use of an artificial neural network. On this basis, it was observed that in the process of isothermal hardening of steel at the applied temperatures, complex transformations of austenite into martensite and bainite occur. In addition, it was found that the research methods used enabled the identification of signal components originating from the phase transformation causing the formation of thin-plate martensite midrib. The use of acoustic methods in the field of bainitic transformation creates the possibility of their application in the industry.

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Publication Details

Journal
Materials
Published
2025-05-10
DOI
https://doi.org/10.3390/ma18102198
Citations
1
Primary Topic
Metal Alloys Wear and Properties
Type
article
Field-Weighted Citation Impact
0.52
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article

Identification of Phase Transformations in Alloy and Non-Alloy Steel During Austempering Using Acoustic Emission and Neural Network

Qingshan Jiang, Małgorzata Łazarska, Tomasz Tański, Zbigniew Ranachowski et al.
1 citations
Materials
Metal Alloys Wear and Properties
0.52
article

Identification of Phase Transformations in Alloy and Non-Alloy Steel During Austempering Using Acoustic Emission and Neural Network

Qingshan Jiang, Małgorzata Łazarska, Tomasz Tański, Zbigniew Ranachowski, Janusz Musiał
article en
1 citations

Abstract

This research was carried out for selected alloy (bearing) and non-alloy (tool) steel. The steels were subjected to austempering. The hardening temperature range was from 100 °C to 180 °C. The use of acoustic emission in connection with the artificial neural network (ANN) enabled the analysis and identification of phase changes occurring in steels during austempering. Classification of acoustic emission events was carried out with the help of their energy values and with the use of an artificial neural network. On this basis, it was observed that in the process of isothermal hardening of steel at the applied temperatures, complex transformations of austenite into martensite and bainite occur. In addition, it was found that the research methods used enabled the identification of signal components originating from the phase transformation causing the formation of thin-plate martensite midrib. The use of acoustic methods in the field of bainitic transformation creates the possibility of their application in the industry.

MaterialsVol. 18(10)
Silesian University of Technology (PL), Kazimierz Wielki University in Bydgoszcz (PL), Jimei University (CN), Institute of Fundamental Technological Research (PL), Polish Academy of Sciences (PL)
Affordable and clean energy
Openalex Percentile: Top 39%
Metal Alloys Wear and Properties
0.52
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