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<p>This paper presents an integrated non-destructive evaluation method for monitoring thermal aging in P91 steel by analyzing magneto-acoustic emission (MAE) signals through wavelet packet transform (WPT). Samples were thermally aged for 0–600&#xa0;h at 780&#xa0;°C and tested under controlled excitation conditions of 30&#xa0;V and 30&#xa0;Hz. The resulting MAE signals were processed using level-3 WPT decomposition to obtain energy distribution ratio (EDR%) features across multiple frequency bands. These frequency-domain features were compared with changes in hardness, tensile properties, and impact energy, as well as metallographic observations showing a transition from fine-lath martensitic to coarsened ferritic structures. Lower-frequency energy (Node 0, 0–125&#xa0;kHz) increased during early aging and then declined due to precipitate coarsening and boundary pinning, while mid-frequency energy (Node 1) showed complementary trends associated with evolving domain-wall interactions. Although the dataset is limited (n = 4), Pearson correlation and linear regression further confirmed that Node-specific EDR% tracks progression of mechanical degradation. Overall, the findings demonstrate that WPT-based MAE analysis offers a sensitive and practical approach for non-destructive condition monitoring of thermally aged P91 steel components.</p>

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Linking Frequency Band Energy Features of Magneto Acoustic Emission to Mechanical Degradation in Thermally Aged P91 Steel

  • 期刊论文

  • 发表日期：

    2026年1月11日

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  • Wasil Riaz,
  • Zenghua Liu,
  • Xiaoran Wang,
  • Yongna Shen,
  • Omer Farooq,
  • Cunfu He,
  • Gongtian Shen

摘要

This paper presents an integrated non-destructive evaluation method for monitoring thermal aging in P91 steel by analyzing magneto-acoustic emission (MAE) signals through wavelet packet transform (WPT). Samples were thermally aged for 0–600 h at 780 °C and tested under controlled excitation conditions of 30 V and 30 Hz. The resulting MAE signals were processed using level-3 WPT decomposition to obtain energy distribution ratio (EDR%) features across multiple frequency bands. These frequency-domain features were compared with changes in hardness, tensile properties, and impact energy, as well as metallographic observations showing a transition from fine-lath martensitic to coarsened ferritic structures. Lower-frequency energy (Node 0, 0–125 kHz) increased during early aging and then declined due to precipitate coarsening and boundary pinning, while mid-frequency energy (Node 1) showed complementary trends associated with evolving domain-wall interactions. Although the dataset is limited (n = 4), Pearson correlation and linear regression further confirmed that Node-specific EDR% tracks progression of mechanical degradation. Overall, the findings demonstrate that WPT-based MAE analysis offers a sensitive and practical approach for non-destructive condition monitoring of thermally aged P91 steel components.