Generalized neural network approach to eddy current inversion for real cracks-Reference-Cited by-同舟云学术

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Generalized neural network approach to eddy current inversion for real cracks

Published:2002-12 Issue:8 Volume:35 Page:609-614
ISSN:0963-8695
Container-title:NDT & E International
language:en
Short-container-title:NDT & E International

Author:

Yusa Noritaka,Cheng Weiying,Chen Zhenmao,Miya Kenzo

Publisher

Elsevier BV

Subject

Mechanical Engineering,Condensed Matter Physics,General Materials Science

Reference14 articles.

1. Review of advances in quantitative eddy current nondestructive evaluation;Auld;J Nondestruct Eval,1999

2. Computational aspects of eddy current testing;Takagi;J Jpn Soc Appl Electromagn Mech,2001

3. Inverse analysis arising in electromagnetic nondestructive evaluation;Kojima;J Jpn Soc Appl Electromagn Mech,2001

4. Caution about simulated cracks in steel for eddy current testing;Randle;Mater Eval,1989

5. Finite element models of stress corrosion cracks (SCC) in 3D eddy current NDE problems;Badics,1995

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1. Bayesian data fusion of eddy current testing for flaw characterization with uncertainty evaluation;NDT & E International;2024-01

2. Estimation of Electromagnetic Properties for 2D Inhomogeneous Media Using Neural Networks;Journal of Electromagnetic Engineering and Science;2022-03-31

3. Crack depth estimation of non-magnetic material by convolutional neural network analysis of eddy current testing signal;Journal of Nuclear Science and Technology;2019-11-18

4. Quantification of Embedded Defect from Magnetic Field Image Using BP Artificial Neural Networks;STUD APPL ELECTROMAG;2019

5. Electrical conductivity identification of a carbon fiber composite material plate using a rotating magnetic field and multi-coil eddy current sensor;The European Physical Journal Applied Physics;2018-08

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