Image reconstruction method for electrical capacitance tomography based on the combined series and parallel normalization model

In this paper, a novel image reconstruction method for electrical capacitance tomography (ECT) based on the combined series and parallel model is presented. A regularization technique is used to obtain a stabilized solution of the inverse problem. Also, the adaptive coefficient of the combined model is deduced by numerical optimization. Simulation results indicate that it can produce higher quality images when compared to the algorithm based on the parallel or series models for the cases tested in this paper. It provides a new algorithm for ECT application.

[1]  H. Yan,et al.  Image reconstruction in electrical capacitance tomography using multiple linear regression and regularization , 2001 .

[2]  Y H Liu,et al.  Identification of flow regimes using back-propagation networks trained on simulated data based on a capacitance tomography sensor , 2004 .

[3]  Yewang Su,et al.  Investigation of square fluidized beds using capacitance tomography: preliminary results , 2001 .

[4]  Tomasz Dyakowski,et al.  Applications of electrical tomography for gas-solids and liquid-solids flows : a review , 2000 .

[5]  Tomasz Dyakowski,et al.  Direct flow-pattern identification using electrical capacitance tomography , 2002 .

[6]  Brian S. Hoyle,et al.  Electrical capacitance tomography for flow imaging: system model for development of image reconstruction algorithms and design of primary sensors , 1992 .

[7]  Trevor A. York Status of electrical tomography in industrial applications , 2001, J. Electronic Imaging.

[8]  Manuchehr Soleimani,et al.  Nonlinear image reconstruction for electrical capacitance tomography using experimental data , 2005 .

[9]  Lihui Peng,et al.  Using Regularization Methods for Image Reconstruction of Electrical Capacitance Tomography , 2000 .

[10]  Weifu Fang,et al.  A nonlinear image reconstruction algorithm for electrical capacitance tomography , 2004 .

[11]  Hannes Wegleiter,et al.  Formulation of cost functionals for different measurement principles in nonlinear capacitance tomography , 2006 .

[12]  Wim De Waele,et al.  Optical measurement of target displacement and velocity in bird strike simulation experiments , 2003 .

[13]  F. Teixeira,et al.  A nonlinear image reconstruction technique for ECT using a combined neural network approach , 2006 .

[14]  Wuqiang Yang,et al.  Optimization of an iterative image reconstruction algorithm for electrical capacitance tomography , 1999 .

[15]  Umer Zeeshan Ijaz,et al.  Sensitivity map generation in electrical capacitance tomography using mixed normalization models , 2007 .

[16]  Lihui Peng,et al.  Image reconstruction algorithms for electrical capacitance tomography , 2003 .

[17]  Liang-Shih Fan,et al.  Neural network based multi-criteria optimization image reconstruction technique for imaging two- and three-phase flow systems using electrical capacitance tomography , 2001 .