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    <identifier>10.57760/sciencedb.34035</identifier>
    <datestamp>2026-04-17T15:35:34Z</datestamp>
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  <dc:date>2026-04-17</dc:date>
  <dc:title>AE Source Database</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.34035</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>In laser processing of surface micro-textures on PCD tools, online monitoring and quality prediction are difficult. This study uses acoustic emission technology to capture the dynamic response during laser ablation, combined with MTF encoding and deep learning to achieve quality prediction. This dataset contains all the original data and processed results required to reproduce the experiments and analysis in the paper.</dc:description>
  <dc:subject>Laser Processing; Surface Textures; Acoustic Emission</dc:subject>
  <dc:creator>Zhanjiang Yu</dc:creator>
  <dc:creator>Ruiwang Tan</dc:creator>
  <dc:creator>Shen Yang</dc:creator>
  <dc:creator>Cong Li</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
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