Electrical Capacitance Tomography (ECT) is a non-invasive and non-destructive imaging technique that uses electrical capacitance measurements at the periphery of an object to generate map of dielectric permittivity of the object. This visualization method is a relatively mature industrial process tomography technique, especially in 2D imaging mode. Volumetric ECT is a new method that poses major computational challenges in image reconstruction and new challenges in sensor design. This paper shows a nonlinear image reconstruction method for 3D ECT based on a validated forward model. The method is based on the finite element approximation for the complete sensor model and the solution of the inverse problem with nonlinear iterative reconstruction. The nonlinear algorithm has been tested against some complicated experimental test cases, and it has been demonstrated that by using an improved forward model and nonlinear inversion method, very complex shaped samples can be reconstructed. The reconstruction of very complex geometry with objects in the shape of letters H, A, L and T is extremely promising for the applications of 3D ECT.
2. Calderon, A. P., "On an inverse boundary value problem," Seminar on Numerical Analysis and Its Applications to Continuum Physics (Rio de Janeiro), 65-73, Sociedade Brasileira de Matematica, 1980.
3. Cheney, M., D. Isaacson, and J. C. Newell, "Electrical impedance tomography," SIAM Review, Vol. 41, No. 1, 85-101, 1999.
4. Dyakowski, T., L. F. C. Jeanmeure, W. B. Zimmerman, and W. Clark, "Direct flow-pattern identification using electrical capacitance tomography," Experimental Thermal and Fluid Science, Vol. 26, No. 6-7, 763-773, 2002.
5. Nurge, M. A., "Electrical capacitance volume tomography with high contrast dielectrics using a cuboid sensor geometry," Measurement Science and Technology, Vol. 18, No. 5, 1511-1520, 2007.
6. Olszewski, T., P. Brzeski, J. Mirkowski, A. Plaskowski, W. Smolik, and R. Szabatin, "Modular capacitance tomograph," Proc. of 4th International Symposium on Process Tomography, Warsaw, 2006.
7. Romanowski, A., K. Grudzien, R. Banasiak, R. A. Williams, and D. Sankowski, "Hopper flow measurement data visualization: Developments towards 3D," Proc. of 5th World Congress on Industrial Process Tomography, Bergen, Norway, 2006.
8. Soleimani, M., C. N. Mitchell, R. Banasiak, R. Wajman, and A. Adler, "Four-dimensional electrical capacitance tomography imaging using experimental data," Progress In Electromagnetics Research, Vol. 90, 171-186, 2009.
9. Soleimani, M., "Three-dimensional electrical capacitance tomography imaging," Insight --- Non-destructive Testing and Condition Monitoring, Vol. 48, No. 10, 613-617, 2006.
10. Wajman, R., R. Banasiak, L. Mazurkiewicz, T. Dyakowski, and D. Sankowski, "Spatial imaging with 3D capacitance measurements," Measurement Science and Technology, Vol. 17, No. 8, 2113-2118, August 2006.
11. Warsito, W. and L. S. Fan, "Development of 3-dimensional electrical capacitance tomography based on neural network multi-criterion optimization image reconstruction," Proc. of 3rd World Congress on Industrial Process Tomography, 942-947, 2003.
12. Warsito, W., Q. Marashdeh, and L. S. Fan, "Electrical capacitance volume tomography," IEEE Sensors Journal, Vol. 7, No. 3-4, 525-535, 2007.
13. Warsito, W. and L. S. Fan, "Neural network based multi-criterion optimization image reconstruction technique for imaging two- and three-phase flow systems using electrical capacitance tomography," Measurement Science and Technology, Vol. 12, 2198-2210, 2001.
14. Williams, R. A. and M. S. Beck, Process Tomography, Principles, Techniques and Applications, Butterworth-Heinemann, Oxford, UK, 1995.
15. Yang, W. Q., D. M. Spink, T. A. York, and H. McCann, "An image-reconstruction algorithm based on Landweber's iteration method for electrical-capacitance tomography," Measurement Science and Technology, Vol. 10, 1065-1069, 1999.
16. Yang, W. Q. and L. Peng, "Image reconstruction algorithms for electrical capacitance tomography," Measurement Science and Technology, Vol. 14, R1-R13, 2003.
17. Goharian, M., M. Soleimani, and G. Moran, "A trust region subproblem for 3D electrical impedance tomography inverse problem using experimental data," Progress In Electromagnetics Research, Vol. 94, 19-32, 2009.
18. Chen, G. P., W. B. Yu, Z. Q. Zhao, Z. P. Nie, and Q. H. Liu, "The prototype of microwave-induced thermo-acoustic tomography imaging by time reversal mirror," Journal of Electromagnetic Waves and Applications, Vol. 22, No. 11-12, 1565-1574, 2008.
19. Cheng, X., B. I.Wu, H. Chen, and J. A. Kong, "Imaging of objects through lossy layer with defects," Progress In Electromagnetics Research, Vol. 84, 11-26, 2008.
20. Huang, C. H., Y. F. Chen, and C. C. Chiu, "Permittivity distribution reconstruction of dielectric objects by a cascaded method," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 2, 145-159, 2007.
21. Franceschini, G., M. Donelli, D. Franceschini, M. Benedetti, P. Rocca, and A. Massa, "Microwave imaging from amplitude-only data-advantages and open problems of a two-step multi-resolution strategy," Progress In Electromagnetics Research, Vol. 83, 397-412, 2008.
22. Chen, X. D., "Subspace-based optimization method in electric impedance tomography," Journal of Electromagnetic Waves and Applications, Vol. 23, No. 11-12, 1397-1406, 2009.
23. Polydorides, N., "Linearization error in electrical impedance tomography," Progress In Electromagnetics Research, Vol. 93, 323-337, 2009.