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Second-order sensitivity coefficient based electrical tomography imaging
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DOI：10.1016/j.ces.2019.01.020.png)
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Abstract
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In this paper, efforts are made to improve the spatial resolution of electrical tomography imaging (ETI), which has succeeded in many fields in the past decades as an advanced process tomography technique. However, its spatial resolution is usually too low to be efficiently used in applications due to the inaccurate sensitivity coefficient. Most of the existing ETI algorithms use the linear components of sensitivity coefficient owing to easy implementation and comprehensive operation. However, the neglected nonlinear parts may contain more useful information. In this paper, we characterized the nonlinear second-order sensitivity coefficient, analyzed its major characteristics, and finally proposed a novel ETI model, which was helpful for improving the spatial resolution of the ETI process. Experimental results showed that this model had higher spatial resolutions than the traditional models that only used linear sensitivity coefficients. The research in this paper can provide reference for the ETI-related applications. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords:
Electrical tomography
Second-order sensitivity
Image reconstruction
Quadratic programming
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