首页> 外文期刊>Inverse Problems in Science & Engineering >DYNAMIC ELECTRICAL IMPEDANCE IMAGING OF BINARY-MIXTURE FIELDS WITH EXTERNAL AND INTERNAL ELECTRODES
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DYNAMIC ELECTRICAL IMPEDANCE IMAGING OF BINARY-MIXTURE FIELDS WITH EXTERNAL AND INTERNAL ELECTRODES

机译:具有内部和外部电极的二元混合场的动态电阻抗成像

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摘要

In the conventional electrical impedance tomography (EIT), the internal impedivity distribution, that is mixture distribution, is reconstructed based on the physical relationship between the known sets of injected currents through the electrodes and induced voltages on the surface of the domain of interest under the assumpution that the domain is stationary during the measurements. This study considers a dynamic electrical impedance imaging to binary-mixture systems with known internal structures to which additional electrodes can be attached, We attempt the utilization of the additional electrodes to enhance the recontruction. Also, we assume the domain is undergoing rapid transient, so the resistivity distribution in the domain of interest changes rapidly within the time taken to acquire a full set of independent measurement data. The dynamic EIT problem is treated as the nonlinear state estimation problem and the unknown state (resistivity) is estimated with the aid of extended Kalman filter in a minimum mean square error sense. Computer simulations for the two-dimensional object with abrupt changing resistivity distribution are provided to illustrate the reconstruction performance of the proposed algorithm.
机译:在常规的电阻抗层析成像(EIT)中,内部阻抗分布(即混合物分布)是基于已知的通过电极的注入电流组与目标区域下感兴趣区域表面上的感应电压之间的物理关系来重建的。假设在测量期间域是固定的。这项研究考虑了具有已知内部结构的二元混合系统的动态电阻抗成像,可以在其中附加电极。我们尝试利用附加电极来增强重构。同样,我们假设该域正在经历快速瞬变,因此感兴趣域中的电阻率分布会在获取全套独立测量数据所花费的时间内迅速变化。动态EIT问题被视为非线性状态估计问题,未知状态(电阻率)借助于扩展卡尔曼滤波器在最小均方误差意义上进行估计。为电阻率分布突然变化的二维物体提供了计算机仿真,以说明该算法的重建性能。

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