Multi-index optimization design for electrical resistance tomography sensor

A multiple index optimization method for ERT sensors is put forward which combines an orthogonal design and fuzzy analysis. This method first establishes a scientific and proper fuzzy evaluation method using fuzzy mathematics to define ERT index satisfaction (ERTIS) and overall ERT index satisfaction (OERTIS) and to construct their satisfaction functions. It unifies all of ERT sensor indices into a single comparable satisfaction value. Then, the OERTIS analysis is developed which allows a set of multiple index orthogonal experiments to be transferred into a single index orthogonal experiment. Where, the uniformity index and the correlation coefficient index of the ERT sensor are set as the optimization objectives. The experiments are set up based on multi-index orthogonal design. The experimental results indicate that the method can derive an evenly distributed sensitivity field and a better image with the optimized sensors, and improve the OERTIS of the ERT sensors by 13.75%.

[1]  Philippe A. Tanguy,et al.  ERT algorithms for quantitative concentration measurement of multiphase flows , 2008 .

[2]  Po Box,et al.  Image reconstruction algorithms for electrical capacitance tomography: state of the art , 2004 .

[3]  Mi Wang,et al.  Electrical resistance tomography for process applications , 1996 .

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

[5]  Hao Wang,et al.  Simulation study of the electrode array used in an ERT system , 1997 .

[6]  Z. Szczepanik,et al.  Field analysis and electrical models of multi-electrode impedance sensors , 2007 .

[7]  R. H. Myers,et al.  Response Surface Techniques for Dual Response Systems , 1973 .

[8]  Yanbiao Liao,et al.  Preconditioned Landweber iteration algorithm for electrical capacitance tomography , 2005 .

[9]  Yizeng Liang,et al.  Uniform design and its applications in chemistry and chemical engineering , 2001 .

[10]  Richard A Williams,et al.  Process tomography : principles, techniques and applications , 1995 .

[11]  Wuqiang Yang,et al.  Design of electrical capacitance tomography sensors , 2010 .

[12]  Liu Xu-min,et al.  多スロープ応答及び画像再構成アルゴリズムを用いる高ダイナミックレンジ相補性金属‐酸化物‐半導体(CMOS)カメラ , 2009 .

[13]  Lei Tang,et al.  A Novel ECT System Based on FPGA and DSP , 2007, Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007).

[14]  Wuliang Yin,et al.  A highly adaptive electrical impedance sensing system for flow measurement , 2002 .

[15]  Wang Huaxiang,et al.  Optimum design of the structure of the electrode for a medical EIT system , 2001 .

[16]  Maurice Beck,et al.  Design of capacitance electrodes for concentration measurement of two-phase flow , 1990 .

[17]  Wuqiang Yang,et al.  Virtual electrical capacitance tomography sensor , 2005 .

[18]  Mi Wang,et al.  Impedance mapping of particulate multiphase flows , 2005 .

[19]  Rob Morrison,et al.  Analysis of electrical resistance tomography (ERT) data using least-squares regression modelling in industrial process tomography , 2009 .

[20]  P. Hua,et al.  Finite element modeling of electrode-skin contact impedance in electrical impedance tomography , 1993, IEEE Transactions on Biomedical Engineering.

[21]  Zdzislaw Szczepanik,et al.  Frequency analysis of electrical impedance tomography system , 2000, IEEE Trans. Instrum. Meas..

[22]  Nan Li,et al.  Characterisation of Liquid Properties by Electrical Capacitance Tomography Sensor for Security Applications , 2009, 2009 Second International Symposium on Electronic Commerce and Security.

[23]  A. Khuri,et al.  Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions , 1981 .

[24]  Wang Hua Optimum Design of Array Electrode for ECT System , 2003 .