ニューラルネットワークと計算力学を用いた超音波欠陥同定法 : レーザ超音波実験による精度検証

概要

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This paper describes an application of the neural networks to defect identification with laser ultrasonics. The present method consists of three subprocesses. First, sample data of identification parameters vs. dynamic responses of displacements at several monitoring points on surface are calculated using the dynamic finite element method. Second, the back-propagation neural network is trained using the sample data. Finally, the well trained network is utilized for defect identification. This method is applied to the identification of a surface defect hidden in solid with laser ultrasonics. Its performance in accuracy and robustness is quantitatively verified in detail through both numerical simulations and experiments.
一般社団法人日本機械学会の論文
1998-03-25