畳み込みニューラルネットワーク用いたＥＣＴ信号からのキズ深さ同定

DOI Web Site

書誌事項

タイトル別名
  • Flaw Depth Identification from ECT Signal using Convolutional Neural Network

説明

<p>Eddy current testing (ECT) is a nondestructive inspection method for detecting cracks and defects in conductive materials such as thin heat transfer tubes of steam generator. ECT applies inverse problem analysis for crack shape estimation, but in many cases requires large CPU time and memory. In this study, an application of convolutional neural network (CNN), which is one of deep learning models, was proposed and showed the possibility of high-speed estimation of crack depth.</p>

収録刊行物

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ