A derivation of the electrical capacitance tomography sensitivity matrix

Youngquist, Robert C.; Storey, Jedediah M.; Nurge, Mark A.; Biagi, C. J.

doi:10.1088/1361-6501/aca0b1

Cited by 8 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Electrical capacitance volume tomography (ECVT) has recently received significant interest as a microgravity mass gauging technique [7][8][9]]. An ECVT system is comprised of lightweight metal plates wrapped around the region of interest (RoI) and a high-speed acquisition device featuring real-time operations, ideally suited for in-space mass gauging.…”

Section: Introductionmentioning

confidence: 99%

Propellant Mass Gauging in a Spherical Tank under Micro-Gravity Conditions Using Capacitance Plate Arrays and Machine Learning

Chowdhury,

Charleston,

Marashdeh

et al. 2023

Sensors

View full text Add to dashboard Cite

Propellant mass gauging under micro-gravity conditions is a challenging task due to the unpredictable position and shape of the fuel body inside the tank. Micro-gravity conditions are common for orbiting satellites and rockets that operate on limited fuel supplies. Capacitance sensors have been investigated for this task in recent years; however, the effect of various positions and shapes of the fuel body is not analyzed in detail. In this paper, we investigate this with various fill types, such as annular, core-annular, and stratified fills at different positions. We compare the performance among several curve-fitting-based approaches and a machine-learning-based approach, the latter of which offers superior performance in estimating the fuel content.

show abstract

Section: Introductionmentioning

confidence: 99%

Propellant Mass Gauging in a Spherical Tank under Micro-Gravity Conditions Using Capacitance Plate Arrays and Machine Learning

Chowdhury,

Charleston,

Marashdeh

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Higher-order approximation methods are also essential methods in reconstruction algorithms. Youngquist et al [25] proposed an asymmetric sensitivity matrix in which high-order terms are retained in the derivation process. This sensitivity matrix contains the electric field at the actual permittivity distribution, resulting in iterations of the image reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Image reconstruction for ECT based on high-order approximate sensitivity matrix

Yang

Liu

2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

Electrical capacitance tomography (ECT), widely used for industrial measurements, reflects the permittivity distribution of the imaging region by measuring capacitance. The image reconstruction method is a crucial factor in determining image quality. Normally, the ECT image is reconstructed by sensitivity matrix. To alleviate the effects of the soft field property of the traditional sensitivity matrix, we propose an ECT reconstruction method based on the high-order approximate sensitivity matrix. The high-order approximate sensitivity matrices with four different nonlinearities, including a traditional sensitivity matrix, are derived through electromagnetic field analysis. Both numerical simulation and experiment are implemented for four sensitivity matrices using the Tikhonov regularisation algorithm and Landweber algorithm. Sensitivity evaluation indicators, image evaluation metricises, and capacitance matching correlation coefficients are used to compare the performance of sensitivity matrices. The results show that the high-order approximate sensitivity matrix with suitable nonlinearities improves image reconstruction quality. In different flow regimes, the sensitivity matrix with proper linearity has obvious advantages for regimes with high nonlinearity. The high-order approximate sensitivity matrix leads to shorter calculation time and can be used by various algorithms to enhance image reconstruction quality.

show abstract

“…The process relies on a pre-calculated sensitivity matrix and a projection vector derived from the impedance measurements. The sensitivity matrix allows for the transformation of the acquired measurements into the representation of the internal phase distribution [27][28][29]. So, in addition to the image reconstruction algorithm, the sensitivity matrix is also a crucial factor to ensure the accuracy of the image reconstruction results.…”

Section: Introductionmentioning

confidence: 99%

A new image reconstruction strategy for capacitively coupled electrical impedance tomography

Wu,

Jiang,

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

Capacitively coupled electrical impedance tomography (CCEIT) is an attractive improvement of electrical resistance tomography (ERT) that offers contactless measurement and utilizes both the real and imaginary parts of the impedance for monitoring conductive gas-liquid two-phase flows in the industry. The conventional CCEIT adopts the finite element method under the benchmark of conductive liquid background to obtain the sensitivity matrices, which has been validated effective in ERT for the usage of the real part information. However, few researches on the usage of the imaginary part information of the conductive fluid have been reported. More research work should be undertaken to seek the most effective sensitivity calculation benchmark for the imaginary part utilization in CCEIT. In this work, the usage of the imaginary part information under different sensitivity calculation benchmarks is studied and a new image reconstruction strategy is proposed for CCEIT. By comparing the imaginary part sensitivity matrices and the corresponding imaging performance under different backgrounds, the benchmark that can make better use of the imaginary part information is determined. With the determined benchmark, a new image reconstruction strategy of CCEIT, which utilizes the respective effective benchmarks for the image reconstruction of the two parts of the fluid impedance, and employs a novel hybrid image fusion method to obtain the final image, is presented. Research results show that the benchmark of non-conductive gas background is more effective for the usage of the imaginary part information of the conductive gas-liquid two-phase flow. And the experimental results demonstrate the effectiveness of the proposed strategy in obtaining high-quality images. Compared with the conventional image reconstruction strategy of CCEIT, the proposed strategy has better imaging performance. This research provides valuable experience in utilizing the imaginary part information of the fluid impedance and lays a good foundation for the further development of CCEIT.

show abstract

A derivation of the electrical capacitance tomography sensitivity matrix

Cited by 8 publications

References 17 publications

Propellant Mass Gauging in a Spherical Tank under Micro-Gravity Conditions Using Capacitance Plate Arrays and Machine Learning

Propellant Mass Gauging in a Spherical Tank under Micro-Gravity Conditions Using Capacitance Plate Arrays and Machine Learning

Image reconstruction for ECT based on high-order approximate sensitivity matrix

A new image reconstruction strategy for capacitively coupled electrical impedance tomography

Contact Info

Product

Resources

About