Title :
Neural network approach to the flaw identification in a conductive plate with finite element modeling
Author :
Zhao, Yuan Xi ; Chai, Lingyun ; Kagawa, Yukio
Author_Institution :
Electron. & Inf. Syst. Dept, Akita Prefectural Univ., Honjo
Abstract :
In this paper, we examine the capability of the neural network approach to the defect identification and the electrical impedance imaging. It is shown the approach is suitable for detecting the defects and their positions in a conductive field system.
Keywords :
electric impedance imaging; finite element analysis; flaw detection; neural nets; conductive field system; conductive plate; defect identification; electrical impedance imaging; finite element modeling; flaw identification; neural network approach; Biological neural networks; Biomedical measurements; Cities and towns; Education; Finite element methods; Industrial electronics; Neural networks; Nuclear electronics; Power engineering and energy; Surface impedance; Finite Element Modeling; Flow Identification; Neural Network Approach;
Conference_Titel :
System Simulation and Scientific Computing, 2008. ICSC 2008. Asia Simulation Conference - 7th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1786-5
Electronic_ISBN :
978-1-4244-1787-2
DOI :
10.1109/ASC-ICSC.2008.4675318
