Title :
Phase boundary estimation in electrical resistance tomography with weighted multilayer neural networks
Author :
Kim, Jae Hyoung ; Kang, Byoung Chae ; Choi, Bong Yeol ; Kim, Min Chan ; Kim, Sin ; Kim, Kyung Youn
Author_Institution :
Dept. of Electron. Eng., Kyungpook Nat. Univ., Daegu
fDate :
4/1/2006 12:00:00 AM
Abstract :
This work presents a boundary estimation approach in electrical resistance imaging for binary mixture fields based on weighted multilayer neural network. The interfacial boundaries are expressed with the truncated Fourier series and the unknown Fourier coefficients are estimated with the weighted multilayer neural network. In doing so, normalized boundary voltages are used for training the neural network and the results from real experiments show that the proposed approach has strong possibility for real-time monitoring of binary mixtures
Keywords :
Fourier series; electric impedance imaging; estimation theory; magnetic multilayers; neural nets; tomography; binary mixture fields; electrical resistance imaging; electrical resistance tomography; interfacial boundaries; normalized boundary voltages; phase boundary estimation; truncated Fourier series; unknown Fourier coefficients; weighted multilayer neural networks; Electric resistance; Fourier series; Intelligent networks; Multi-layer neural network; Neural networks; Phase estimation; Pollution measurement; Power engineering and energy; Tomography; Voltage; Binary mixtures; boundary estimation; electrical resistance tomography; multilayer neural network;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2006.871671
