Design and optimization of electromagnetic tomography and electrical resistance tomography dual-modality sensor

Wang, Chao; Wang, Ruichang; Liang, Xiao; Ye, Jiamin; Chen, Xueyong

doi:10.1088/1361-6501/ac8146

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…The sensor mainly consists of an insulated pipe, ERT excitation/measurement electrodes arranged on the inner wall of the pipe, EMT excitation coils arranged around the outside of the pipe, TMR sensors, and the magnetic shield. The structural parameters of the dual-modality sensor have been optimized in the literature, 29 as shown in Table 1.…”

Section: Ert/tmr-emt Dual-modality Systemmentioning

confidence: 99%

“…On this basis, Wang et al designed and constituted an ERT/TMR-EMT dual-modality system. Through the qualitative and quantitative analyses of dual-modality image reconstruction results, the parameters such as the electrode duty ratio of ERT and the relative position between coils of EMT and electrodes were optimized …”

Section: Introductionmentioning

confidence: 99%

“…Through the qualitative and quantitative analyses of dual-modality image reconstruction results, the parameters such as the electrode duty ratio of ERT and the relative position between coils of EMT and electrodes were optimized. 29 In this paper, a new measurement method to obtain the three-phase holdup distribution simultaneously based on the ERT/TMR-EMT dual-modality system is proposed. First, the equivalent conductivity and permeability in each imaging unit of the fluidized bed cross section are calculated by the D-bar algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Measurement of Three-Phase Holdup Distribution in Gas–Liquid–Solid Fluidized Bed Based on ERT/TMR-EMT

Wang,

Zhang,

Guo

et al. 2023

Ind. Eng. Chem. Res.

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The measurement of three-phase holdup distributions in the gas−liquid−solid fluidized bed has guiding significance for the fluidized bed's characterization, design, and optimization. Aimed at the measurement of three-phase holdup distribution simultaneously, an image reconstruction method for electrical resistance tomography and electromagnetic tomography based on tunnel magnetoresistance (ERT/TMR-EMT) dual-modality system is proposed. The distributions of equivalent conductivity and equivalent permeability are reconstructed by the D-bar algorithm based on ERT and TMR-EMT, respectively. Then, the three-phase holdup distribution is reconstructed through equivalent media theory. From the results of the reconstructed image and threephase average holdup in simulation, the holdup variations of the gas, liquid, and solid are principally consistent with the phantom sets. From the measurement results of the dynamic experiments, clusters with high solid holdup and bubbles with high gas holdup can be accurately reflected and the variation of three-phase holdup distribution and average holdup can correctly reflect changes in experimental states in the fluidized bed.

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Section: Ert/tmr-emt Dual-modality Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measurement of Three-Phase Holdup Distribution in Gas–Liquid–Solid Fluidized Bed Based on ERT/TMR-EMT

Wang,

Zhang,

Guo

et al. 2023

Ind. Eng. Chem. Res.

Self Cite

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“…Electromagnetic tomography (EMT) or magnetic induction tomography (MIT) can be used to image distributions of conductivity and/or permeability based on the voltage measurements obtained from electromagnetic coils evenly distributed around the periphery of imaging region [1][2][3][4]. Excitation current is injected into the excitation coil generating alternating primary magnetic field in the imaging region, which induces eddy current on the surface of the measured object.…”

Section: Introductionmentioning

confidence: 99%

A Sparsity Reconstruction Algorithm of Electromagnetic Tomography Technique for High Conductivity Medium Imaging

Liu

Wang

et al. 2023

Sens Imaging

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Electromagnetic tomography (EMT) is a versatile tomographic imaging technique for reconstruction of conductivity and/or permeability distribution due to the advantages of non-contact, non-intrusive, lowcost, simple structure and fast imaging. However, the ill-posed and ill-conditioned features of EMT make it difficult to obtain high quality reconstructed images. To improve the spatial resolution of the high conductivity medium imaging, the L1-L1 framework objective function is presented, which uses L1 norm as both data fidelity term and regularization term to weaken the influence of the data outliers and impose the sparsity feature of the measured objects. An improved Split Bregman method is proposed to solve the complicated optimization problem efficiently, which splits it into several simple sub-tasks.Each subtask can be solved by adopting the proper method. Besides, an acceleration strategy is introduced to improve the convergence rate. Numerical simulations are used to verify the effectiveness and competitive performance of the proposed improved method. The experiments are carried out by the designed modularized EMT system to further verify the effectiveness of the proposed method. The reconstructed images can precisely show the number and positions of the measured objects.

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Section: Introductionmentioning

confidence: 99%

A Sparsity Reconstruction Algorithm of Electromagnetic Tomography Technique for High Conductivity Medium Imaging

Liu

Wang

et al. 2022

Preprint

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Electromagnetic tomography (EMT) is a versatile tomographic imaging technique for reconstruction of conductivity and/or permeability distribution due to the advantages of non-contact, non-intrusive, low-cost, simple structure and fast imaging. However, the ill-posed and ill-conditioned features of EMT make it difficult to obtain high quality reconstructed images. To improve the spatial resolution of the high conductivity medium imaging, the L1-L1 framework objective function is presented, which uses L1 norm as both data fidelity term and regularization term to weaken the influence of the data outliers and impose the sparsity feature of the measured objects. An improved Split Bregman method is proposed to solve the complicated optimization problem efficiently, which splits it into several simple sub-tasks. Each subtask can be solved by adopting the proper method. Besides, an acceleration strategy is introduced to improve the convergence rate. Numerical simulations are used to verify the effectiveness and competitive performance of the proposed improved method. The experiments are carried out by the designed modularized EMT system to further verify the effectiveness of the proposed method. The reconstructed images can precisely show the number and positions of the measured objects.

show abstract

Design and optimization of electromagnetic tomography and electrical resistance tomography dual-modality sensor

Cited by 6 publications

References 24 publications

Measurement of Three-Phase Holdup Distribution in Gas–Liquid–Solid Fluidized Bed Based on ERT/TMR-EMT

Measurement of Three-Phase Holdup Distribution in Gas–Liquid–Solid Fluidized Bed Based on ERT/TMR-EMT

A Sparsity Reconstruction Algorithm of Electromagnetic Tomography Technique for High Conductivity Medium Imaging

A Sparsity Reconstruction Algorithm of Electromagnetic Tomography Technique for High Conductivity Medium Imaging

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