Second-order sensitivity coefficient based electrical tomography imaging

Ding, Mingliang; Yue, Shihong; Li, Jia; Wang, Yaru; Wang, Huaxiang

doi:10.1016/j.ces.2019.01.020

Cited by 17 publications

(18 citation statements)

References 23 publications

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“…The actual measurement in Ω is required to use a reference field Ω0 in which all pixels have the same conductivity value [18]. After individually exciting Ω0 and Ω, the increments of both σ and u in the two fields are △σ and △u, and (1) is further expressed as…”

Section: A Ert Measuring Principlementioning

confidence: 99%

ERT Based Computation of Solid Phase Fraction in Solid-Liquid Flow With Various Object Sizes

et al. 2022

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Solid phase fraction (SPF) is one of the most important parameters in solid-liquid two-phase flow, and has been increasingly addressed on most of the measuring techniques. As an effective measuring technique, Electrical Resistance Tomography (ERT) has been applied to measure SPF owing to low-cost, fast-response, non-invasive and non-radiation characteristics. The ERT-based SPF estimation is greatly affected by different solid object sizes from the existing methods, but currently there is none efficient method to solve this problem. In this paper, a mathematical model firstly is proposed to generally approximate various object sizes and thereby reconstruct all measurements. Therefore, when all solid objects have unevenly distributed and different sizes, SPF can still be effectively computed. Experiments are implemented in three groups of actual experiments by a building platform, where the solid objects in each group have individual object size. Results show that the new method can compute the value of SPF more accurate than the existing method, and thus provide a more accurate way to SPF computation.

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Section: A Ert Measuring Principlementioning

confidence: 99%

ERT Based Computation of Solid Phase Fraction in Solid-Liquid Flow With Various Object Sizes

et al. 2022

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“…The algorithms for solving (7) are classified into iterative and non-iterative algorithms. Among the non-iterative algorithms, the Tikhonov regularization (TR) algorithm [13] is the most typical one.…”

Section: A the Principle Of Ertmentioning

confidence: 99%

“…Among the non-iterative algorithms, the Tikhonov regularization (TR) algorithm [13] is the most typical one. It transforms (7) into (8) by adding the regularity term G(σ ),…”

Section: A the Principle Of Ertmentioning

confidence: 99%

“…It uses the finite element analysis method to calculate the sensitivity coefficient. Then, the solution principle is to select the finite elements in the field and use the finite difference equation to replace the partial differential equation to obtain the value of the field function at discrete points [7]. Therefore, the method cannot clearly express the relationship between the sensitivity coefficient and the sensing field.…”

Section: Introductionmentioning

confidence: 99%

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A New Calculation Method of the Sensitivity Coefficient for the ERT System

Hao

et al. 2022

IEEE Access

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Electrical Resistance Tomography (ERT) is a promising technique owing to its low cost, high speed, and visualization features. The sensitivity coefficient plays a significant role in ERT image reconstruction as a priori information. However, the existing methods for calculating sensitivity matrix suffer from poor interpretability and operability. The result leads to an obstacle to improving the quality of the reconstructed images. Therefore, we propose a new sensitivity calculation method that has the advantages of clear physical significance, high robustness, and strong interpretability. We compared the existing and new sensitivity matrices with some metrics, such as correlation coefficient and relative error, and tested the new method's performance by numerical simulations and experiments. The results show that the new sensitivity matrix is feasible and has better performance in ERT imaging reconstruction, especially in the presence of noise.INDEX TERMS Electrical resistance tomography, sensitivity matrix, electromagnetic field theory.

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“…To overcome the problem, the sensitivity matrix S and pixel conductivity/grey distributions G have been used for the CF computation. As a typical example, Ding et al [ 31 ] reformates the MG method by the following equation:

where

is the mean of the grey levels of all pixels after obtaining grey distributions G . Thereby, the applicable range of Equation (4) can be widened.…”

Section: Related Workmentioning

confidence: 99%

Clustering-Based Component Fraction Estimation in Solid–Liquid Two-Phase Flow in Dredging Engineering

Sun

Yue

et al. 2020

Sensors

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Component fraction (CF) is one of the most important parameters in multiple-phase flow. Due to the complexity of the solid–liquid two-phase flow, the CF estimation remains unsolved both in scientific research and industrial application for a long time. Electrical resistance tomography (ERT) is an advanced type of conductivity detection technique due to its low-cost, fast-response, non-invasive, and non-radiation characteristics. However, when the existing ERT method is used to measure the CF value in solid–liquid two-phase flow in dredging engineering, there are at least three problems: (1) the dependence of reference distribution whose CF value is zero; (2) the size of the detected objects may be too small to be found by ERT; and (3) there is no efficient way to estimate the effect of artifacts in ERT. In this paper, we proposed a method based on the clustering technique, where a fast-fuzzy clustering algorithm is used to partition the ERT image to three clusters that respond to liquid, solid phases, and their mixtures and artifacts, respectively. The clustering algorithm does not need any reference distribution in the CF estimation. In the case of small solid objects or artifacts, the CF value remains effectively computed by prior information. To validate the new method, a group of typical CF estimations in dredging engineering were implemented. Results show that the new method can effectively overcome the limitations of the existing method, and can provide a practical and more accurate way for CF estimation.

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Second-order sensitivity coefficient based electrical tomography imaging

Cited by 17 publications

References 23 publications

ERT Based Computation of Solid Phase Fraction in Solid-Liquid Flow With Various Object Sizes

ERT Based Computation of Solid Phase Fraction in Solid-Liquid Flow With Various Object Sizes

A New Calculation Method of the Sensitivity Coefficient for the ERT System

Clustering-Based Component Fraction Estimation in Solid–Liquid Two-Phase Flow in Dredging Engineering

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