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<p>Traditional heat treatment methods require a significant amount of time and energy to affect atomic diffusion and enhance the spheroidization process of carbides in bearing steel, while pulsed current can accelerate atomic diffusion to achieve ultra-fast spheroidization of carbides. However, the understanding of the mechanism by which different pulse current parameters regulate the dissolution behavior of carbides requires a large amount of experimental data to support, which limits the application of pulse current technology in the field of heat treatment. Based on this, quantify the obtained pulse current processing data to create an important dataset that could be applied to machine learning. Through machine learning, the mechanism of mutual influence between carbide regulation and various factors was elucidated, and the optimal spheroidization process parameters were determined. Compared to the 20&#xa0;h required for traditional heat treatment, the application of pulsed electric current technology achieved ultra-fast spheroidization of GCr15 bearing steel within 90&#xa0;min.</p>

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Realizing Ultra-fast Spheroidization of GCr15 Bearing Steel by Analyzing the Correlation of Carbide Dissolution Law and Pulsed Electric Current Parameters Through Machine Learning

  • 期刊论文

  • 发表日期：

    2025年4月10日

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  • Zhongxue Wang,
  • Le Ren,
  • Yating Zhang,
  • Mengcheng Zhou,
  • Xinfang Zhang

摘要

Traditional heat treatment methods require a significant amount of time and energy to affect atomic diffusion and enhance the spheroidization process of carbides in bearing steel, while pulsed current can accelerate atomic diffusion to achieve ultra-fast spheroidization of carbides. However, the understanding of the mechanism by which different pulse current parameters regulate the dissolution behavior of carbides requires a large amount of experimental data to support, which limits the application of pulse current technology in the field of heat treatment. Based on this, quantify the obtained pulse current processing data to create an important dataset that could be applied to machine learning. Through machine learning, the mechanism of mutual influence between carbide regulation and various factors was elucidated, and the optimal spheroidization process parameters were determined. Compared to the 20 h required for traditional heat treatment, the application of pulsed electric current technology achieved ultra-fast spheroidization of GCr15 bearing steel within 90 min.