Image reconstruction algorithm for electrical capacitance tomography based on radial basis function neural network

Li-Feng Zhang Li-Feng Zhang,Xiu-Zhang Jin Xiu-Zhang Jin,Hua-Xiang Wang Hua-Xiang Wang,Min Ma Min Ma

doi:10.1109/icmlc.2005.1527664

Image reconstruction algorithm for electrical capacitance tomography based on radial basis function neural network

Li-Feng Zhang Li-Feng Zhang, Xiu-Zhang Jin Xiu-Zhang Jin + Show 2 more

https://doi.org/10.1109/icmlc.2005.1527664

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Publication Date: Jan 1, 2005

Citations: 7

Affiliation: North China Electric Power University

#Electrical Capacitance Tomography #Radial Basis Function Neural Network + Show 8 more

Abstract
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Abstract

Electrical capacitance tomography (ECT) technique is a new technique for two-phase flow measurement. This paper describes the basic principles of ECT. Forward and inverse problem of ECT are analyzed in detail. The conventional image reconstruction algorithm, i.e., linear back projection algorithm has been given. Then, the new image reconstruction algorithm for ECT based on radial basis function (RBF) neural network has been presented. Using the measurement data obtained from the ECT simulation software developed by the author, the reconstructed images were obtained. Results indicate that RBF neural network is suitable for solving the nonlinear problem of ECT image reconstruction. Comparing with linear back projection algorithm, this algorithm has advantages of higher accuracy.

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