Electrical impedance tomography

Wang, M.

doi:10.1016/b978-1-78242-118-4.00002-2

Cited by 22 publications

(19 citation statements)

References 83 publications

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“…In the experimental research, a sensing strategy called the ‘opposite electrode pair strategy’ was applied [31]. This strategy means that the voltage source was connected to an opposite pair of electrodes, e.g.…”

Section: Resultsmentioning

confidence: 99%

“…Due to the very high impedance of the chokeberry (at a low moisture content), it is virtually impossible to build a current source that would allow the generation of stimulus signal in the required frequency range [29,30]. These circumstances caused the need to apply, in this research, voltage stimulation and accurate current measurement systems [2,31]. As the voltage source (SRC), the programmable signal generator Agilent 33500B was used.…”

Section: Methodsmentioning

confidence: 99%

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Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography

Porzuczek

2019

Sensors

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This paper presents a method for the online determination of the spatial distribution of the moisture content in granular material. It might be essential for the monitoring and optimal control of, for example, drying processes. The proposed method utilizes Electrical Impedance Tomography (EIT). As an exemplary material for experimental research, the black chokeberry (Aronia melanocarpa) was used. The relationship between the electrical impedance of the chokeberry and its moisture content was determined for a wide range of frequencies (20 Hz–200 kHz). The EIT research consisted of both simulation and experimental investigation. Experimental studies of the spatial distribution of the moisture content were performed in a cylindrical vessel equipped with 8 electrodes circumferentially arranged. The voltage signal from the electrodes was acquired simultaneously using the data acquisition module. Due to the high impedance of the chokeberries, exceeding 109 Ω for the dried matter, extraordinary instrumentation was necessary to be applied. On the other hand, raw chokeberry was characterized by a several orders of magnitude lower impedance (103–104 Ω), especially for high frequencies. The wide range of the observed impedance was able to be measured owing to its use of the voltage stimulation instead of the current stimulation (which is most common for EIT). The image reconstruction problem was solved using an iterative Gauss–Newton algorithm and the EIDORS (Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software) package. The obtained results showed a satisfactory ability to localize an insufficiently dried part of the material. Prospective ways to improve the imaging quality are also discussed.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography

Porzuczek

2019

Sensors

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“…The X-Ray tomography suffers from hazard radiations, big size, fixed, and high cost compared to electrical tomography techniques. Therefore, many current methods have been implemented to image the industrial process [49]. The ECT is a novel feasible technology for imaging dielectric and conductive materials { [50], [51].…”

Section: Ect System For Conductive Materialsmentioning

confidence: 99%

ECT-LSTM-RNN: An Electrical Capacitance Tomography Model-Based Long Short-Term Memory Recurrent Neural Networks for Conductive Materials

2021

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Image reconstruction for industrial applications based on Electrical Capacitance Tomography (ECT) has been broadly applied. The goal of image reconstruction based ECT is to locate the distribution of permittivity for the dielectric substances along the cross-section based on the collected capacitance data. In the ECT-based image reconstruction process: (1) the relationship between capacitance measurements and permittivity distribution is nonlinear, (2) the capacitance measurements collected during image reconstruction are inadequate due to the limited number of electrodes, and (3) the reconstruction process is subject to noise leading to an ill-posed problem. Thence, constructing an accurate algorithm for real images is critical to overcoming such restrictions. This paper presents novel image reconstruction methods using Deep Learning for solving the forward and inverse problems of the ECT system for generating high-quality images of conductive materials in the Lost Foam Casting (LFC) process. Here, Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) models were implemented to predict the distribution of metal filling for the LFC process-based ECT. The recurrent connection and the gating mechanism of the LSTM is capable of extracting the contextual information that is repeatedly passing through the neural network while filtering out the noise caused by adverse factors. Experimental results showed that the presented ECT-LSTM-RNN model is highly reliable for industrial applications and can be utilized for other manufacturing processes.

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“…A number of excitation and measurement methods or sensing strategies have been reported since the late 1980s [ 1 , 27 ]. Figure 4 shows three different sensing strategies under the review, which are adjacent electrode pair strategy [ 2 ] ( figure 4 a ), an alternative sensing strategy ( figure 4 b ), which is named as PI/2 protocol owing to a π /2 radian between its nearest measurement electrode pairs [ 28 ], and the diametrically opposite sensing strategy [ 3 ] ( figure 4 c ). Applying the reciprocity theorem or leads theorem as given by equations ( 2.2 ) and ( 2.3 ) and also in the use of four-electrode method, the number of independent measurements from these strategies (ignoring the measurements from current drive electrodes) is 104, 72 and 96, respectively.…”

Section: Sensing Strategymentioning

confidence: 99%

Arts of electrical impedance tomographic sensing

Wang

Karki

2016

Phil. Trans. R. Soc. A.

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This paper reviews governing theorems in electrical impedance sensing for analysing the relationships of boundary voltages obtained from different sensing strategies. It reports that both the boundary voltage values and the associated sensitivity matrix of an alternative sensing strategy can be derived from a set of full independent measurements and sensitivity matrix obtained from other sensing strategy. A new sensing method for regional imaging with limited measurements is reported. It also proves that the sensitivity coefficient back-projection algorithm does not always work for all sensing strategies, unless the diagonal elements of the transformed matrix, ATA, have significant values and can be approximate to a diagonal matrix. Imaging capabilities of few sensing strategies were verified with static set-ups, which suggest the adjacent electrode pair sensing strategy displays better performance compared with the diametrically opposite protocol, with both the back-projection and multi-step image reconstruction methods. An application of electrical impedance tomography for sensing gas in water two-phase flows is demonstrated.This article is part of the themed issue ‘Supersensing through industrial process tomography’.

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Electrical impedance tomography

Cited by 22 publications

References 83 publications

Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography

Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography

ECT-LSTM-RNN: An Electrical Capacitance Tomography Model-Based Long Short-Term Memory Recurrent Neural Networks for Conductive Materials

Arts of electrical impedance tomographic sensing

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