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Polynomial Collocation for Handling an Inaccurately Known Measurement Configuration in Electrical Impedance Tomography

机译:用于处理电阻抗断层成像中不准确已知测量配置的多项式配置

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摘要

The objective of electrical impedance tomography is to reconstruct the internal conductivity of a physical body based on measurements of current and potential at a finite number of electrodes attached to its boundary. Although the conductivity is the quantity of main interest in impedance tomography, a real-world measurement configuration includes other unknown parameters as well: The information on the contact resistances, electrode positions, and body shape is almost always incomplete. In this work, the dependence of the electrode measurements on all aforementioned model properties is parametrized via polynomial collocation. The availability of such a parametrization enables efficient simultaneous reconstruction of the conductivity and other unknowns by a Newton-type output least squares algorithm, which is demonstrated by two-dimensional numerical experiments based on both noisy simulated data and experimental data from two water tanks.
机译:电阻抗层析成像的目的是基于在连接到其边界的有限数量的电极上的电流和电势的测量结果来重建物理体的内部电导率。尽管电导率是阻抗层析成像中的主要关注内容,但实际的测量配置还包括其他未知参数:接触电阻,电极位置和身体形状的信息几乎总是不完整。在这项工作中,通过多项式搭配参数化了电极测量值对所有上述模型特性的依赖性。这种参数化的可用性使得能够通过牛顿型输出最小二乘算法同时有效地重建电导率和其他未知数,该算法通过基于两个模拟噪声和来自两个水箱的实验数据的二维数值实验来证明。

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