A Novel Preconditioned Conjugate Gradient Image Reconstruction Algorithm for Electrical Capacitance Tomography System

Abstract:

To solve the‘soft-field’nature and the ill-posed problem in electrical capacitance tomography (ECT)technology, a novel preconditioned conjugate gradient algorithm for electrical capacitance tomography is presented. The analysis of the basic principles of electrical capacitance tomography, based on the given preconditioned conjugate gradient method and calculation formula of the iteration steps of the ECT and to explore the feasibility of application of the algorithm, the algorithm to meet the convergence conditions and the reconstruction image error. Experimental results and simulation data indicate that the algorithm can provide high quality images and favorable stabilization compared with LBP，conjugate gradient algorithms in simple flow pattern and this new algorithm presents a feasible and effective way to research on image reconstruction algorithm for Electrical Capacitance Tomography System.

• Periodical: Advanced Materials Research (Volumes 181-182)
• Pages: 629-635
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.181-182.629
• Online since: January 2011
• Authors: Yu Chen, Jun Cao, De Yun Chen
• Keywords: Conjugate-Gradient, Electrical Capacitance Tomography (ECT), Image Reconstruction, Iterative Algorithm

References

[1] Xie C G, Plaskowski, Beck M S. 8-electode capacitance system for two-component flow identification. Part 1: Tomographic flow imaging [J], IEE Proc A, 1989; 136(4): 173-190.

DOI: 10.1049/ip-a-2.1989.0031

[2] Warsito W., Fan L. S, Measurement of real-time flow structures in gas-liquid and gas-liquid-solid flow systems using electrical capacitance tomography(ECT)[J]. Chemical Engineering Science 2001, 56(6): 6455-6462.

DOI: 10.1016/s0009-2509(01)00234-2

[3] W. q. Yang, Modeling of capacitance tomography sensors[J]. IEE Proc. Sci. Meas. Technol. 1997, 144: 203-220.

[4] K.L. Ostrowski, S.P. Luke, R.A. Williams. Simulation of the performance of electrical capacitance tomography for muasurement of dense phase pneumatic conveying[J]. Chemical Engineering Journal, 1997, 6, 8197-8205.

DOI: 10.1016/s1385-8947(97)00095-8

[5] B.T. Hjertaker. Static characterization of a dual sensor flow imaging system[J]. Flow Measurement and Instrumentation, 1998, 9183-191.

DOI: 10.1016/s0955-5986(98)00018-1

[6] Liu S, Yang W Q, Wang H, Jiang F, Su Y. Investigation of square fluidized beds using capacitance tomography preliminary results[J]. Measurement Science and Technology, 2002, 12(8): 1120-1125.

DOI: 10.1088/0957-0233/12/8/318

[7] Xi Shaolin, Zhao Fengzhi. Computation Methods for Optimization[D]. Shanghai: Shanghai Scientific & Technical Publishers. 1983: 74-95.

[8] Yang W Q, Peng L H. Image reconstruction algorithms for electrical capacitance tomography[J]. Meas Sci Technol, 2003, 14: R1-R3.

DOI: 10.1088/0957-0233/14/1/201

[9] Liu S, Fu L, Yang W Q et al. Prior-online iteration for image reconstruction with electrical capacitance tomography [J]. IEE Proc-sci. Meas. Technol., 2004, 151(3): 195-200.

DOI: 10.1049/ip-smt:20040246

[10] Wang Huaxiang, Zhu Xueming, Zhang Lifeng. Conjugate gradient algorithm for electrical capacitance tomography[J]. Journal of Tianjin University, 2005, 38(1): 1-4.