Single-shot high-voltage circuit for electrical capacitance tomography

Smolik, Waldemar T.; Kryszyn, Jacek; Radzik, B; Stosio, M.; Wróblewski, Przemysław; Wanta, Damian; Dańko, Ł; Olszewski, Tomasz K.; Szabatin, R.

doi:10.1088/1361-6501/aa50e1

Cited by 27 publications

(18 citation statements)

References 20 publications

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“…EVT4 system performance is determined by a method used for the capacitance measurement. In the single-shot high voltage (SSHV) method [24], a single pulse excitation increases the speed of the measurement, whereas a high amplitude of the excitation and oversampling of the output signal preserve high signal to noise ratio. The current is integrated using a charge preamplifier while a voltage pulse is applied to the measured capacitance (Fig.…”

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confidence: 99%

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Evaluation of the Electrical Capacitance Tomography System for Measurement Using 3d Sensor

Kryszyn

Wanta

Smolik

2019

IAPGOS

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Further tests of EVT4 data acquisition system for electrical capacitance tomography are presented. The modular system, which can have up to 32 channels with an individual analogue to digital converter, was designed to ensure small uncertainty of capacitance measurement at high speed of imaging. The system’s performance in the context of 3D imaging was experimentally verified. In particular, we show that the measurement of changes in capacitance due to a small change of an electric permittivity distribution for the most distant electrodes in a suitably designed 3D sensor is possible using our system. Cross-plane measurements together with the measurements for the pairs of most distant electrodes are essential for accurate reconstruction of 3D distributions. Due to sensitivity of capacitance measurements obtained in the hardware, the measurements for all electrode pairs can be used in the inverse problem – the system of equations can be extended. Although the numerical condition number of a matrix of such a system is high, image reconstruction is possible from the data obtained in our system. The results of 3D image reconstruction for simple test objects are shown.

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confidence: 99%

“…New ECT and EIT hardware was developed to increase the throughput of contemporary data acquisition systems [3,9,28,30,38]. The state of the art in measurement methods and data acquisition systems development for ECT together with performance comparison was presented in [13] and [24].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Electrical Capacitance Tomography System for Measurement Using 3d Sensor

Kryszyn

Wanta

Smolik

2019

IAPGOS

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“…The object's conductivity is reconstructed on the basis of known voltages and measured potentials. Reconstruction of electrical impedance requires accurate modelling [6,11,17,18,20]. EIT is a method of imaging in which the conductivity distribution of the tested object is estimated on the basis of measurements of electrical voltages and potentials of electrodes at the boundary.…”

Section: Introductionmentioning

confidence: 99%

Using Statistical Algorithms for Image Reconstruction in EIT

Rymarczyk

Kozłowski

2018

MATEC Web Conf.

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The problem with image reconstruction from impedance tomography is an ill-posed inverse problem. To get quantitative information on the change in conductivity, it would be better to use a non-linear model in the differential imaging solution. Statistical methods such as PCR, PLRS, elastic net, Lars, SVR were used to reconstruct the image. The discussed techniques can be applied to the problem of electrical tomography. The algorithms used to identify unknown material coefficient.

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“…The issue of tomographic imaging is an important element of modern life, not only because of the role of tomography in medicine, but also the potential of this technology, which has not been used so far [1][2][3][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Applying Machine Learning Algorithms to Solve Inverse Problems in Electrical Tomography

Rymarczyk

Kłosowski

2018

MATEC Web Conf.

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The article presents four selected methods of supervised machine learning, which can be successfully used in the tomography of flood embankments, walls, tanks, reactors and pipes. A comparison of the following methods was made: Artificial Neural Networks (ANN), Supported Vector Machine (SVM), K-Nearest Neighbour (KNN) and Multivariate Adaptive Regression Splines (MAR Splines). All analysed methods concerned regression problems. Thanks to performed analysis the differences expressed quantitatively were visualized with the use of indicators such as regression, error of mean square deviation, etc. Moreover, an innovative method of denoising tomographic output images with the use of convolutional auto-encoders was presented. Thanks to the use of a convolutional structure composed of two autoencoders, a significant improvement in the quality of the output image from the ECT tomography was achieved.

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Single-shot high-voltage circuit for electrical capacitance tomography

Cited by 27 publications

References 20 publications

Evaluation of the Electrical Capacitance Tomography System for Measurement Using 3d Sensor

Evaluation of the Electrical Capacitance Tomography System for Measurement Using 3d Sensor

Using Statistical Algorithms for Image Reconstruction in EIT

Applying Machine Learning Algorithms to Solve Inverse Problems in Electrical Tomography

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