レーザー超音波場における欠陥パラメータ化物理情報ニューラルネットワークを用いたフォワードおよびインバースモデリング
Liu Yang1, Peipei Liu2, Kiyoon Yi1
1Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, The Republic of Korea.
Ultrasonics
|January 7, 2026
まとめ
新しい欠陥パラメータ化物理情報ニューラルネットワーク（DP-PINN）は、レーザー超音波を用いて金属部品のサブミリメートル表面欠陥を正確に特性評価します。この非破壊検査方法は、限られたデータから完全な波形を再構築し、構造的完全性を保証します。
背景:
- 非破壊検査（NDE）は、金属部品の完全性にとって重要です。
- 表面欠陥は、疲労寿命と性能に大きく影響します。
- レーザー超音波は非接触検査を提供しますが、限られたデータからの波形再構築と欠陥特定には課題があります。
結論:
- DP-PINNは、レーザー超音波を介して金属部品のサブミリメートル表面欠陥を効果的に特性評価します。
- この方法は、限られたデータで正確な波形再構築と欠陥局在化を可能にします。
- このアプローチは、構造的完全性を保証するための非破壊検査能力を向上させます。
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