Four-dimensional electrical capacitance tomography imaging using experimental data

Electrical capacitance tomography (ECT) is a relatively mature non-invasive imaging technique that attempts to map dielectric permittivity of materials. ECT has become a promising monitoring technique in industrial process tomography especially in fast flow visualization. One of the most challenging tasks in further development of ECT for real applications are the computational aspects of the ECT imaging. Recently, 3D ECT has gained interest because of its potential to generate volumetric images. Computation time of image reconstruction in 3D ECT makes it more difficult for real time applications. In this paper we present a robust and computationally efficient 4D image reconstruction algorithm applied to real ECT data. The method takes advantage of the temporal correlation between 3D ECT frames to reconstruct movies of dielectric maps. Image reconstruction results are presented for the proposed algorithms for experimental ECT data of a rapidly moving object.

[1]  C. Liao,et al.  Image Reconstruction of Arbitrary Cross Section Conducting Cylinder Using UWB Pulse , 2007 .

[2]  C. Chiu,et al.  Permittivity Distribution Reconstruction of Dielectric Objects by a Cascaded Method , 2007 .

[3]  Qing Huo Liu,et al.  The Prototype of Microwave-Induced Thermo-Acoustic Tomography Imaging by Time Reversal Mirror , 2008 .

[4]  Jin Au Kong,et al.  Imaging of Objects through Lossy Layer with Defects , 2008 .

[5]  Wuqiang Yang,et al.  A comparative study of three dimensional electrical capacitance tomography , 2007 .

[6]  Manuchehr Soleimani.  Three-dimensional electrical capacitance tomography imaging , 2006 .

[7]  Carsten H. Wolters,et al.  Efficient algorithms for the regularization of dynamic inverse problems: II. Applications , 2002 .

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

[9]  Wuqiang Yang,et al.  Dynamic imaging in electrical capacitance tomography and electromagnetic induction tomography using a Kalman filter , 2007 .

[10]  Robert Banasiak,et al.  Spatial imaging with 3D capacitance measurements , 2007 .

[11]  Wuqiang Yang,et al.  Key issues in designing capacitance tomography sensors , 2006, 2006 5th IEEE Conference on Sensors.

[12]  Simon R. Arridge,et al.  3D Shape Reconstruction in Optical Tomography Using Spherical Harmonics and BEM , 2006 .

[13]  Liang-Shih Fan,et al.  Electrical Capacitance Volume Tomography , 2007, IEEE Sensors Journal.

[14]  Robert Banasiak,et al.  Hopper flow measurement data visualization: Developments towards 3D , 2007 .

[15]  A. Adler,et al.  Temporal image reconstruction in electrical impedance tomography , 2007, Physiological measurement.

[16]  Liang-Shih Fan,et al.  Dynamics of spiral bubble plume motion in the entrance region of bubble columns and three-phase fluidized beds using 3D ECT , 2005 .

[17]  Jari P. Kaipio,et al.  Fluid dynamical models and state estimation in process tomography: Effect due to inaccuracies in flow fields , 2001, J. Electronic Imaging.

[18]  A K Louis,et al.  Efficient algorithms for the regularization of dynamic inverse problems: I. Theory , 2002 .

[19]  Manuel Benedetti,et al.  Reconstruction of Dielectric Objects from Amplitude - Only Data – Advantages and Open Problems of a Two-Step Multi-Resolution Strategy , 2008 .

[20]  V. Serdyuk.  Dielectric Study of Bound Water in Grain at Radio and Microwave Frequencies , 2008 .

[21]  Mark A. Nurge,et al.  Electrical capacitance volume tomography with high contrast dielectrics using a cuboid sensor geometry , 2007 .

[22]  Wuqiang Yang,et al.  Image reconstruction by nonlinear Landweber iteration for complicated distributions , 2008 .