Deep neural network for simulation of magnetic flux leakage testing-Reference-Cited by-同舟云学术

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Deep neural network for simulation of magnetic flux leakage testing

Published:2021-01 Issue: Volume:170 Page:108726
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Le Minhhuy,Pham Cong-Thuong,Lee Jinyi

Funder

National Foundation for Science and Technology Development

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference17 articles.

1. Y. Li Y, G. Y. Tian, S. Ward, Numerical simulations on electromagnetic NDT at high speed, Insight, 48(2), 103–108 (2006).

2. An effective 3-D element scheme for computing electromagnetic field distortions due to defects in eddy-current nondestructive evaluation;Badics;IEEE Trans Mag,1997

3. On the Use of the Magnetic Vector Potential in the Finite Element Analysis of Three-Dimensional Eddy Currents;Biro;IEEE Trans on Mag,1984

4. J. P. A. Bastos and N. Sadowski, Electromagnetic modeling by finite element methods, CRC Press ISBN 9780824742690, 1st Edition, April, 2003.

5. Magnetic leakage testing using linearly integrated Hall and GMR sensor arrays to inspect inclusions in cold-rolled strips;Angani;IEEE Trans. Magn.,2014

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4. The homogeneity effects of magnetic flux density distribution on the detection of railhead surface defects via the magnetic flux leakage method;Insight - Non-Destructive Testing and Condition Monitoring;2023-12-01

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