Image reconstruction of electrical capacitance tomography using the dynamic mesh and changing physical properties methods

Abbasian, Saman; Maddahian, Reza

doi:10.1088/1361-6501/ab3dc4

Cited by 8 publications

(5 citation statements)

References 35 publications

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“…Generally, the ECT technique can be summarized into forward problem and inverse problem. The forward problem aims to use the known sensor parameters and the permittivity distribution in the sensor pipeline to calculate the capacitance values between each electrode pair by the following mathematical model [30]…”

Section: Principle Of Ectmentioning

confidence: 99%

Iterative weighted fidelity and hybrid regularization-based algorithm for ECT

Cui¹,

Tian²,

Wang³

et al. 2022

Meas. Sci. Technol.

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A new image reconstruction algorithm for electrical capacitance tomography (ECT) based on iterative weighted fidelity and hybrid regularization is proposed. Specifically, an improved cost function model including iterative weighted data fidelity term and hybrid regularization term can reduce the impact of the outlier and enhance the sparsity of solution. In order to solve the proposed model efficiently, the alternating direction method of multipliers (ADMM) is used to divide the complex optimization problem into several simple iterative sub-problems. Moreover, the iterative shrinkage thresholding algorithm (ISTA) and the iterative p-shrinkage algorithm (IPSA) are also adopted to solve the sub-problems. Besides, simulation experiments for six different permittivity distributions are investigated with noise-free and noise-contaminated cases respectively. The research results verify that the reconstruction images with proposed algorithm have less artifacts and deformations, clearer edges, and better noise robustness than that of the classic methods.

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Section: Principle Of Ectmentioning

confidence: 99%

Iterative weighted fidelity and hybrid regularization-based algorithm for ECT

Cui¹,

Tian²,

Wang³

et al. 2022

Meas. Sci. Technol.

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“…Planar array capacitance imaging technology (Nassr et al 2008, Thiele et al 2009, Tholin-Chittenden and Soleimani 2017 is a new NDT technology developed on the basis of electrical capacitance tomography (ECT) (Abbasian andMaddahian 2019, Darma et al 2019). Planar array capacitance imaging technique uses the edge effect of electrodes for detection and reconstructs the distribution information of the measured spatial dielectric constant by the measured capacitance value (Ye et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Split Bregman algorithm based on adaptive parameter for planar array sensor imaging

Sun¹,

Zhang²,

Wen³

2022

Meas. Sci. Technol.

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Planar array capacitance imaging is a visualization imaging technique based on the edge effect of electric fields. However, there are ill-posed problem and soft-field effects in the imaging process, which results in unstable and susceptible imaging. To address this issue, the inverse solution of planar array capacitive imaging system is transformed into an optimization problem with the approximate solution of linear-squares. A new cost function with total variation (TV) sparse reconstruction model is presented, which considers the sparsity of regularisation operator to improve the stability of the inversion process. The adaptive split Bregman iterative algorithm is proposed to solve the inverse optimization problem. The computation is simplified by splitting the complex optimization problem into simple subproblems. The results show that the algorithm can obtain stable model updates, and numerical experiments prove the effectiveness and reliability of the algorithm.

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“…To obtain more accurate and sharper images of the materials distribution, iterative image reconstruction algorithms are crucial [29], [30]. In the iterative techniques, the inverse and forward problems are solved in a continuous loop until an acceptable measurement error rate is reached.…”

Section: Introductionmentioning

confidence: 99%

Efficient Image Reconstruction Algorithm for ECT System Using Local Ensemble Transform Kalman Filter

Deabes

Bouazza

2021

IEEE Access

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One of the vital processes that should be monitored and analyzed continuously in the oilgas and petroleum-related industries is the multi-phase flow inside pipes. Multi-phase flow means flowing two or more phases of gas, liquid, or solid inside a pipe. Electrical Capacitance Tomography (ECT) is a feasible and economical solution for monitoring dynamic applications. The ECT system offers the benefits of no radiation, non-intrusive, and non-invasive. Despite its potential, ECT systems deployment's major limitation is the crucial need to develop rapid image reconstruction algorithms. In this paper, a Local Ensemble Transform Kalman Filter (LETKF) is developed as a non-linear system estimator for reconstructing images in the ECT system. This method manages each node of the model independently by assimilating only the observations at a predefined distance. The localized approach of the LETKF gives it high computational efficiency allowing it to be applied to large dynamic systems. A quantitative analysis using Image Error (IE) and Coefficient Correlation (CC) measures has been applied to prove the effectiveness of the proposed algorithm. Indeed, the IE has been significantly decreased (around 62%), and the CC greatly increased (around 58%). Then, the influence of the noise was discussed. The results are promising and prove the algorithm feasibility.INDEX TERMS ECT, image reconstruction, Kalman filter, multi-phase flow.

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Image reconstruction of electrical capacitance tomography using the dynamic mesh and changing physical properties methods

Cited by 8 publications

References 35 publications

Iterative weighted fidelity and hybrid regularization-based algorithm for ECT

Iterative weighted fidelity and hybrid regularization-based algorithm for ECT

Split Bregman algorithm based on adaptive parameter for planar array sensor imaging

Efficient Image Reconstruction Algorithm for ECT System Using Local Ensemble Transform Kalman Filter

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