Optimization of Hessian Matrix in Modified Newton-Raphson Algorithm for Electrical Resistance Tomography

Xiao, Liao

doi:10.18280/ejee.210506

Cited by 3 publications

(3 citation statements)

References 27 publications

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“…en, the noise reduction of the data and the extraction of feature signals are made by Shannon wavelet analysis to reach the information of the internal conductivity distribution of the metal. Finally, the image reconstruction unit reconstructs the media distribution image based on this to visualize the internal structure of the metal [25]. e signal source generates a sine wave signal as the control signal of the voltage-controlled constant-current source module, which will output the sinusoidal AC power required after conversion by the voltage-controlled constant-current source module [26].…”

Section: Basic Principles Of Metal Conductivity Chromatographymentioning

confidence: 99%

High-Precision Electrical Impedance Tomography for Electrical Conductivity of Metallic Materials

Zhao

Miao

Chai

et al. 2022

Advances in Materials Science and Engineering

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Metal materials are subject to deformation, internal stress distribution, and cracking during processing, all of which affect the distribution of electrical conductivity of the metal. Suppose we can detect the conductivity distribution of metal materials in real time. In that case, we can complete the inverse imaging of metal material properties, structures, cracks, etc. and realize nondestructive flaw detection. However, metal materials' small resistance, high electrical conductivity, and susceptibility of voltage signals to noise signal interference make an accurate measurement of metal conductivity challenging. Therefore, this paper addresses the problem of detecting the conductivity distribution of metals by investigating a high-precision four-electrode AC measurement method. This technical approach combines laminar imaging techniques with high-precision weak signal extraction methods. On this basis, a method and equipment for high-precision electrical impedance tomography of metallic materials’ electrical conductivity were established. The way specifies a new number of electrodes and adopts a model of spaced excitation reference measurements. Single-frequency sinusoidal AC signal is used for excitation, and Shannon wavelet analysis is used for signal extraction and noise reduction. Super-resolution reconstruction algorithms are used for resistivity distribution image reconstruction to improve image quality. Based on the results of various comparative experiments, it is clear that this new functional technique method has good imaging stability and operability and can perform tasks such as analyzing the internal conductivity distribution of metals. This research provides an effective way of new ideas for the safe detection of metal structures, the changes in crystal tissue structure, and the study of metal properties. In particular, it expands the scope of research in the development and application of resistance tomography, which has tremendous commercial potential research significance.

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Section: Basic Principles Of Metal Conductivity Chromatographymentioning

confidence: 99%

High-Precision Electrical Impedance Tomography for Electrical Conductivity of Metallic Materials

Zhao

Miao

Chai

et al. 2022

Advances in Materials Science and Engineering

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“…Based on the different electrical features of the object in the sensitivity field, the ET techniques could be divided into electromagnetic tomography (EMT), electrical capacitance tomography (ECT), electrical impedance tomography (EIT), and electrical resistance tomography (ERT). Based on the principle of electromagnetic induction, the EMT can reconstruct the distribution state of the magnetic permeability for the medium in the sensitivity field [1][2][3][4][5][6]; Based on the principle of capacitance sensitivity, the ECT can reconstruct the distribution state of the dielectric constant for the medium in the sensitivity field [7][8][9][10][11][12][13][14][15][16][17]; Based on the principle of impedance sensitivity, the EIT can reconstruct the distribution state of the complex admittance for the medium in the sensitivity field [18][19][20][21][22][23][24]; Based on the principle of resistance sensing, the ERT can reconstruct the distribution state of the dielectric resistivity/conductivity for the medium in the sensitivity field [25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of a Finite Element Model for Electrical Resistance Tomography of Human Lungs

Xiao¹

2021

Self Cite

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To improve the reconstruction quality of electrical resistance tomography (ERT) images, this paper designs and optimizes the finite element model for human lungs. According to the computer tomography (CT) scan image on human chest, the entire simulation domain was divided into a region of lungs, heart, and spine, and a region of adipose tissue, and the boundary curve equations of each region were derived by the improved particle swarm optimization (PSO). Based on the prior knowledge, a structural model was established for human lungs; the ERT forward problem was solved by the finite element model based on grid reconstruction, and the calculated boundary voltage of sensitivity field was taken as the theoretical value. Next, two optimization goals were set up: improving the calculation accuracy of forward problem, and easing the ill-conditionedness of the sensitivity matrix; two variables were configured: the number of layers of the finite element model in each region, and the polar diameter ratio of the finite element nodes on each layer to the finite element nodes on the boundary of each region corresponding to the same polar angle. On this basis, the finite element model was optimized by the improved PSO to adapt to human lung ERT. Simulation results show that, under the same experimental conditions, the proposed finite element model could solve the forward problem more accurately, improve the ill-conditionedness of the sensitivity matrix and the Hessian matrix, and make the sensitivity distribution more uniformly, thereby enhancing the accuracy of image reconstruction.

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“…Electrical tomography (ET) technology consists of 4 different branches, namely, electrical impedance tomography (EIT) [8][9][10][11][12][13][14], ERT [15][16][17][18][19][20], electrical capacitance tomography (ECT) [21][22][23][24][25][26][27], and electromagnetic tomography (EMT) [28][29][30][31][32][33], among which the ERT technology is a new generation of medical imaging technology and a simplified form of the EIT technology when only the change of conductivity/resistivity of the sensitive field is considered, having three outstanding advantages of functional imaging, no damage, and medical image monitoring. Compared with other monitoring methods, ERT technology has incomparable advantages in real-time monitoring and quantitative evaluation of critical respiratory diseases.…”

Section: Introductionmentioning

confidence: 99%

Width Optimization of Array Electrode for Human Lung Electrical Resistance Tomography System Based on prior Knowledge

Xiao

2021

Complexity

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In electrical resistance tomography (ERT) technology for human lung, under the same experimental conditions, the width of the sensitive field boundary electrode has a significant impact on the calculation accuracy of the inverse problem besides the finite element model (FEM) topology. Aiming to improve the quality of reconstructed images, the FEM for human lung was set up based on prior knowledge. On this basis, the electrode width of the FEM was optimised by comparing the morbidity degrees of the sensitivity matrix and Hessian matrix, the uniformity of sensitivity distribution, and the quality of reconstructed images, which can improve the accuracy of solving the inverse problem significantly.

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Optimization of Hessian Matrix in Modified Newton-Raphson Algorithm for Electrical Resistance Tomography

Cited by 3 publications

References 27 publications

High-Precision Electrical Impedance Tomography for Electrical Conductivity of Metallic Materials

High-Precision Electrical Impedance Tomography for Electrical Conductivity of Metallic Materials

Design and Optimization of a Finite Element Model for Electrical Resistance Tomography of Human Lungs

Width Optimization of Array Electrode for Human Lung Electrical Resistance Tomography System Based on prior Knowledge

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