Electrical Resistance Tomography Sensor Research Articles

Determination of optimal positive end-expiratory pressure using electrical impedance tomography in infants under general anesthesia: Comparison between supine and prone positions.

This study determined the optimal positive end-expiratory pressure levels in infants in supine and prone positions under general anesthesia using electrical impedance tomography (EIT). This prospective observational single-centre study included infants scheduled for surgery in the prone position. An electrical impedance tomography sensor was applied after inducing general anesthesia. The optimal positive end-expiratory pressure in the supine position was determined in a decremental trial based on EIT and compliance. Subsequently, the patient's position was changed to prone. Electrical impedance tomography parameters, including global inhomogeneity index, regional ventilation delay, opening pressure, the centre of ventilation, and pendelluft volume, were continuously obtained up to 1 h after prone positioning. The optimal positive end-expiratory pressure in the prone position was similarly determined. Data from 30 infants were analyzed. The mean value of electrical impedance tomography-based optimal positive end-expiratory pressure in the prone position was significantly higher than that in the supine position [10.9 (1.6) cmH2O and 6.1 (0.9) cmH2O, respectively (p < .001)]. Significant differences were observed between electrical impedance tomography- and compliance-based optimal positive end-expiratory pressure. Peak and mean airway, plateau, and driving pressures increased 1 h after prone positioning compared with those in the supine position. In addition, the centre of ventilation for balance in ventilation between the ventral and dorsal regions improved. The prone position required higher positive end-expiratory pressure than the supine position in mechanically ventilated infants under general anesthesia. EIT is a promising tool to find the optimal positive end-expiratory pressure, which needs to be individualized.

Measurement of the water-to-liquid ratio of oil–water two-phase flow for low flow rates and high water content

Oil–water two-phase flow is widely present in the petroleum industry, and the vast majority of oilfields have entered the period of exploitation under high water content. Accurate measurement of water-to-liquid ratio (WLR) is crucial to oil production. Currently, there are fewer works related to the WLR measurement at high water content and low flow rates. In order to get a complete picture of WLR measurement in this context by electrical resistance tomography (ERT) sensors, dynamic experiments with a total flow rate not exceeding 4m3h−1 were conducted. These dynamic experiments considered the influence of the direction of the test pipelines, the inner diameter of the ERT sensor and the conductivity of the water. According to the relative positions of the measurement and excitation electrode pairs of the ERT sensor, different strategies for WLR calculation were established. This paper presents all results of the experiments of the WLR measurement. Especially, image reconstruction at different flow rates was conducted, as a way to qualitatively reflect the mixing of oil and water, thus helping to understand the WLR measurements. The whole work reveals the regularities of the WLR measurement by ERT, and provides a reference for subsequent work to realize the WLR accurate measurement in oil-water two-phase flow at high water content and low flow rates.

Flow velocity computation using a single ERT sensor

Flow velocity is an important parameter in the multi-phase flow detection field. Electrical resistance tomography (ERT) is an advanced and non-invasive measuring technique for velocity estimation that has received considerable interest in the past decade. The process involves using two adjacent ERT sensors to collect measurements in a cross-sectional pipe, and the application of the cross-correlation (CC) principle for computing flow velocity. Currently, however, inaccurate assumptions, uncertain parameters, and noisy data greatly limit ERT efficiency and accuracy in practice. A new flow velocity computation method is presented that uses a single ERT sensor to replace two adjacent ERT sensors. According to the measurements of the single sensor and the corresponding ERT images, two key variables are computed that tightly align with the flow velocity. The proposed method overcomes the limitations of existing flow computation methods to some extents. Moreover, it can compute flow velocities in not only solid-liquid but also gas-liquid two-phase flows. Finally, experiments are conducted to validate the proposed method, and demonstrate its accuracy and reliability over existing methods.

Electrical resistance tomography-based multi-modality sensor and drift flux model for measurement of oil–gas–water flow

This paper proposes a novel method to measure each constituent of an oil–gas–water mixture in a water continuous flow, typically encountered in many processes. It deploys a dual-plane electrical resistance tomography sensor for measuring dispersed phase volume fraction and velocity; a gradiomanometer flow density meter and a drift flux model to estimate slip velocities; with absolute pressure and temperature measurements. These data are fused to estimate constituent volume flow rates. Other commonly used operational parameters can be further derived: water cut or water liquid ratio (WLR) and gas volume fraction (GVF). Trials are described for flow rates of water 5–10 m3 h−1; oil 2–10 m3 h−1 and gas 1–15 m3 h−1. The comparative results are included with published data from the Schlumberger Gould Research flow facility. The paper proposes the use of the described configuration for measurement of volume flow rates in oil–gas–water flows with an absolute error of ±10% within GVF 9%–85% and WLR > 45%.

Hydromechanics-based flow velocity estimation using single ERT sensor

Multi-phase flow detection is an important task in flow velocity estimation. Owing to its fast response, no radiation, and low cost, the electrical resistance tomography (ERT) technique with a pair of sensors is typically used to estimate the flow velocity based on the cross-correlation (CC) measurement principle. However, due to the unreasonable a priori assumption, uncertain parameter, and limitation of ERT, this remains inaccurate and unsteady under complex and multi-flow conditions. We propose a novel flow velocity computation method that uses a single ERT sensor instead of a pair. Different from existing methods that are based on the CC principle, both the Churchill and Bernoulli equations in hydromechanics are used to compute flow velocity, based on which an inherent relation among the flow velocity, pressure difference, and density value in a detected pipeline is derived. Since the pressure difference and density value can be accurately computed from measurements from a single ERT sensor, the estimated flow velocity can greatly overcome the limitations when a pair of ERT sensors is employed. The proposed method is validated via a set of experiments, showing that it is more accurate and steadier than existing methods.

A novel methodology for measuring batch settling velocities of particles using Electrical Resistance Tomography

This study demonstrates how to measure batch settling velocities of particles in columns at an unconventionally high vertical spatial resolution of 1 mm using Electrical Resistance Tomography (ERT). A novel methodology, which utilized a titled vessel fitted with an ERT sensor array and novel analytical equations, was tested on dilute Newtonian suspensions of fairly monodisperse spherical glass beads (4.8% v/v) with a d50 diameter of 123 µm in aqueous glycerol solutions at 80, 85 and 90 wt% concentrations. The model yielded settling velocities of 0.13, 0.076 and 0.043 mm/s for the three suspensions respectively, each approximating their predicted values with errors of 16.3, 14.4 and 2.29%, respectively. Data fluctuations were discerned in the dataset but their effect on the dataset quality was minimized by increasing the time step sizes by factors of 3, 4 and 9 for the 80, 85 and 90 wt% glycerol solutions, respectively.

Measuring 3D Cell Culture Viability in Multiple 3D Printed Scaffolds Within a Single Miniature Electrical Impedance Tomography Sensor

The use of 3D cell culture for tissue engineering and regenerative medicine applications often challenges conventional biochemical and optical assays. Impedance‐based cellular assays have shown their potential to retrieve dielectric parameters pertaining to cell behavior such as viability, proliferation, and differentiation for 2D adherent cell culture. Herein, simultaneous 3D impedance imaging and viability measurements of multiple large (&gt;2 mm) 3D cell cultures embedded in collagen gels are demonstrated. The method is facilitated by low‐resistance 3D printed scaffolds that can hold a 3D cell–gel system throughout cell culture while being transparent to impedance imaging. It is shown in silico and in vitro that frequency‐difference electrical impedance tomography (fd‐EIT) can nondestructively and in a label‐free way differentiate a variety of cell concentrations with a single miniature sensor in real time. This study paves the way toward the development of EIT imaging for the quantitative and noninvasive evaluation of tissue engineering products.

Quantitative Evaluations with 2d Electrical Resistance Tomography in the Low-Conductivity Solutions Using 3d-Printed Phantoms and Sucrose Crystal Agglomerate Assessments.

Crystallization is a significant procedure in the manufacturing of many pharmaceutical and solid food products. In-situ electrical resistance tomography (ERT) is a novel process analytical tool (PAT) to provide a cheap and quick way to test, visualize, and evaluate the progress of crystallization processes. In this work, the spatial accuracy of the nonconductive phantoms in low-conductivity solutions was evaluated. Gauss–Newton, linear back projection, and iterative total variation reconstruction algorithms were used to compare the phantom reconstructions for tap water, industrial-grade saturated sucrose solution, and demineralized water. A cylindrical phantom measuring 10 mm in diameter and a cross-section area of 1.5% of the total beaker area was detected at the center of the beaker. Two phantoms with a 10-mm diameter were visualized separately in noncentral locations. The quantitative evaluations were done for the phantoms with radii ranging from 10 mm to 50 mm in demineralized water. Multiple factors, such as ERT device and sensor development, Finite Element Model (FEM) mesh density and simulations, image reconstruction algorithms, number of iterations, segmentation methods, and morphological image processing methods, were discussed and analyzed to achieve spatial accuracy. The development of ERT imaging modality for the purpose of monitoring crystallization in low-conductivity solutions was performed satisfactorily.

On the Performance of a Capacitively Coupled Electrical Impedance Tomography Sensor with Different Configurations.

Capacitively coupled electrical impedance tomography (CCEIT) is a new kind of electrical resistance tomography (ERT) which realizes contactless measurement by capacitive coupling and extends traditional resistance measurement to total impedance measurement. This work investigates the performance of a CCEIT sensor with three different configurations, including the unshielded configuration, the shielded configuration A (the CCEIT sensor with the external shield) and the shielded configuration B (the CCEIT sensor with both the external shield and the radial screens). The equivalent circuit models of the measurement electrode pair of the CCEIT sensor with different configurations were developed. Additionally, three CCEIT prototypes corresponding to the three configurations were developed. Both the simulation work and experiments were carried out to compare various aspects of the three CCEIT prototypes, including the sensitivity distribution, the impedance measurement and the practical imaging performance. Simulation results show that shielded configurations improve the overall average sensitivity of the sensitivity distributions. Shielded configuration A contributes to improve the uniformity of the sensitivity distributions, while shielded configuration B reduces the uniformity in most cases. Experimental results show that the shielded configurations have no significant influence on the imaging quality of the real part of impedance measurement, but do make sense in improving the imaging performance of the imaginary part and the amplitude of impedance measurement. However, configuration B (with radial screens) has no significant advantage over configuration A (without radial screens). This work provides an insight into how shielding measures influence the performance of the CCEIT sensor, in addition to playing an important role in shielding unwanted noise and disturbances. The research results can provide a useful reference for further development of CCEIT sensors.

A printed electrical impedance tomography sensor for detection of damage in composites

This paper proposes a new printed electrical impedance tomography (EIT) sensor for detection of damage in composite structure. The EIT sensor consists of a sensing area and related electrical circuits. It is directly printed on the surface of composite structure by a layer-by-layer screen printing process with graphene-doped carbon ink and silver ink. By injecting tiny currents into the EIT sensor and measuring the corresponding boundary voltages, damage information can be obtained by inverse analysis to reconstruct the distribution of conductivity change caused by damage. It has the potential to quantitatively identify the locations and sizes of multiple damage without any prior knowledge. Experimental results on a glass fiber reinforced polymer (GFRP) plate with different number of simulated damage have demonstrated the effectiveness of the printed sensor itself and the related damage detection method.

Investigation of Multi-Plane Scheme for Compensation of Fringe Effect of Electrical Resistance Tomography Sensor.

Conventional electrical resistance tomography (ERT) sensors suffer from the fringe effect, i.e., severe distortion of the electric field on both ends of the measurement electrodes, leading to a 3D sensing region for a 2D sensor. As a result, the objects outside an ERT sensor plane affect the sensing and hence image, i.e., deteriorating the image quality. To address this issue, a multiple-plane ERT sensor scheme is proposed in this paper. With this scheme, auxiliary sensor planes are used to provide references for the fringe effect of the measurement plane, for compensation by subtracting the weighed influence of the fringe effect. Simulation results show that the proposed scheme, either three-plane or two-plane sensor, can compensate for the fringe effect induced by objects outside the measurement plane with a variety of axial object distributions, i.e., several non-conductive bars or conductive bars placed at different cross-sectional and axial positions inside the sensor. Experiments were carried out. Images obtained with single-plane and multiple-plane ERT sensors are compared, and the proposed compensation scheme has been hence verified.

An adaptive electrical resistance tomography sensor with flow pattern recognition capability

The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern changes during the real-time detection of two-phase flow. In view of this problem, an adaptive ERT sensor with a dynamic structure is proposed. The electrodes of the ERT sensor are arranged in an array structure, the flow pattern recognition technique is introduced into the ERT sensor design and accordingly an ERT flow pattern recognition method based on signal sparsity is proposed. This method uses the sparse representation of the signal to express the sampling voltage of the ERT system as a sparse combination and find its sparse solution to achieve the classification of different flow patterns. With the introduction of flow identification information, the sensor has an intelligent function of adaptively and dynamically adapting the sensor structure according to the real-time flow pattern change. The experimental results show that the sensor can automatically identify four typical flow patterns: core flow, bubble flow, laminar flow and circulation flow with recognition rates of 91%, 93%, 90% and 88% respectively. For different flow patterns, the dynamically optimized sensor can significantly improve the quality of ERT image reconstruction.

Development of a Novel Linear ERT Sensor to Measure Surface Deposits

This paper investigates the feasibility of using electrical resistance tomography (ERT) to visualize the surface deposit during a cleaning-in-place (CIP) process, which is a common problem in various industries. A pilot scale cleaning rig with a purposely designed ERT test section was used for monitoring the prerinse CIP stage of cleaning milk paste adhering to a test section. The ERT test section comprises a CIP-ERT multilinear sensor consisting of four planes of eight electrodes. The industrial tomography system, P2000 ERT system, was used to collect the voltage data that were processed in a MATLAB-based ERT toolkit. 3-D images were reconstructed using the L-curve Tikhonov method. A feasibility study was conducted to evaluate the performance of the CIP-ERT sensor. Image analysis showed that ERT is suitable for monitoring and visualizing the CIP process for the materials that foul similar to milk pastes. The success of this paper contributes to a time/energy efficient industrial process as the cleaning process can be visualized and over cleaning can be avoided.

Compensation of volatile-distributed current due to variance of the unknown contact impedance in an electrical impedance tomography sensor

A weighted parameter vector χnorm based on extracellular fluid resistance in the Cole impedance model is hereby proposed in order to compensate for the volatile-distributed current. The volatile-distributed current due to variance in the unknown contact impedance in an electrical impedance tomography (EIT) sensor distorts the ideality of the frequency-dependent behavior of the object of interest, leading to inaccuracy in the reconstructed images. The sources of variance in the unknown contact impedance include the use of electrodes with inconsistent impedance values, electrochemical reaction or the improper attachment of electrodes to the object of interest. χnorm represents the current pathway lengths at zero frequency which reflects the volatile-distributed current, and it is used to determine the source of the measured impedance. The source of the unknown contact impedance can be the background object in the normal physiological condition, an inclusion object in an abnormal physiological condition or systematic error. The new reconstruction methods are derived from the frequency-difference EIT (fd-EIT) and the weighted-frequency-difference EIT (wfd-EIT) using χnorm. The new reconstruction methods are frequency-difference electrical impedance spectro-tomography (fd-EIST) and weighted-frequency-difference electrical impedance spectro-tomography (wfd-EIST). The performance of fd-EIST and wfd-EIST was evaluated by experimental and simulation studies using biomaterials with frequency measurements from f = 500 Hz to f = 100 kHz and the results were compared with those from fd-EIT and wfd-EIT. The results showed that the use of χnorm reduces the root mean square error, position error, ringing and shape deformation. It also increases the ideality of the frequency-dependent behavior, either for the inclusions or the background objects at different frequencies.

A New Design of Electrical Impedance Tomography Sensor System for Pulmonary Disease Diagnosis

AbstractAs an advanced process detection technology, electrical impedance tomography (EIT) has wide application prospects and advantages in medical imaging diagnosis. However, a series of issues need to be addressed before applying EIT for bedside monitoring. Medical diagnosis and bedside monitoring are dynamic measuring process, where the positions of measuring electrodes and the shape of the detected field are changing dynamical. Due to the inability to cope with the changeable electrode positions and various dynamic fields, existing EIT systems are mainly used for industrial detection in condition of static measurement and visualization. In this paper, we investigate the dynamic measurement and visualization of human breast in EIT field, describe the design of the measuring sensor system, and expound the measuring principle. The main component of the hardware system is a built-in servo electrical resistance tomography sensor with capacitive sliding rod, which can adapt to the crowd of different chest contour and the change of chest shape in the dynamic process of breathing. The corresponding measuring principle is extracting all real-time positions of measuring electrodes, then obtaining the dynamic boundary, finally dividing the detection field rapidly. Experimental results confirmed that the proposed system can obtain real-time location of boundary sensor and dynamically solve the problem of arbitrary-shape boundary measurement. The imaging results validate the availability of designed sensor system and the effectiveness of the corresponding measuring principle.

Electrical Resistance Tomography for Visualization of Moving Objects Using a Spatiotemporal Total Variation Regularization Algorithm.

Electrical resistance tomography (ERT) has been considered as a data collection and image reconstruction method in many multi-phase flow application areas due to its advantages of high speed, low cost and being non-invasive. In order to improve the quality of the reconstructed images, the Total Variation algorithm attracts abundant attention due to its ability to solve large piecewise and discontinuous conductivity distributions. In industrial processing tomography (IPT), techniques such as ERT have been used to extract important flow measurement information. For a moving object inside a pipe, a velocity profile can be calculated from the cross correlation between signals generated from ERT sensors. Many previous studies have used two sets of 2D ERT measurements based on pixel-pixel cross correlation, which requires two ERT systems. In this paper, a method for carrying out flow velocity measurement using a single ERT system is proposed. A novel spatiotemporal total variation regularization approach is utilised to exploit sparsity both in space and time in 4D, and a voxel-voxel cross correlation method is adopted for measurement of flow profile. Result shows that the velocity profile can be calculated with a single ERT system and that the volume fraction and movement can be monitored using the proposed method. Both semi-dynamic experimental and static simulation studies verify the suitability of the proposed method. For in plane velocity profile, a 3D image based on temporal 2D images produces velocity profile with accuracy of less than 1% error and a 4D image for 3D velocity profiling shows an error of 4%.

Experimental investigation of solid-liquid two-phase flow in cemented rock-tailings backfill using Electrical Resistance Tomography

The cemented rock-tailings backfill (CRB) technique is a rapidly advancing technique for the mine backfill process. However, the inclusion of waste rocks in backfill materials increase the transportation burden on the backfill pipeline. In particular, it can accelerate pipeline wear and significantly increases the probability of the backfill pipeline being blocked by large waste rocks. To ensure safe transportation, we proposed a visual detection method for liquid-solid two-phase flow inside a backfill pipeline based on Electrical Resistance Tomography (ERT). In particular, we established a finite element model (FEM) for the 16-electrode ERT sensor to study in detail the detection sensitivity of the ERT ‘soft field’ effect. Using orthogonal experiments, we also analyzed the effects of the solid concentration, particle size, and waste rock-to-tailing ratio on the electrical conductivity of the backfill slurry. According to the experiment results, we simulated the positions of waste rocks in the pipeline. A linear back-projection algorithm was utilized to perform the inversion imaging of the 9 sets of flow patterns in the orthogonal experiments. The research results indicate that the most important factor affecting the conductivity of backfill slurry is the ratio of waste rock to tailings. The conductivity of the backfill slurry reached a maximum of 3.8 mS/cm for a solids concentration of 50 wt%, particle size of 25–50 mm, and waste rock-to-tailing ratio of 70/30. We found that waste rocks in the backfill pipelines could be accurately located using reconstructed images. Finally, we conclude that, with an imaging time of only 0.04 s, ERT analysis has the potential to fully meet the real-time requirement of online monitoring of the backfill slurry transportation.

Electrical Impedance Spectro-Tomography Based on Dielectric Relaxation Model

An electrical impedance spectro-tomography consists of a quasi-adjacent sensing method and a frequency-time difference imaging for relatively complex dielectric object monitoring has been proposed. A quasi-adjacent sensing method is designed to measure an electrical impedance spectroscopy based on four-wire measurement technique at the multi-electrodes electrical impedance tomography sensor. A frequency-time difference imaging for spatial distribution monitoring is needed, as the electrochemical reaction incur during the short time meanwhile the spatial geometry tends to be constant. An artificial set of phantoms were made and the proposed technique was capable to show the Cole–Cole parameters as a dielectric relaxation model on each measurement pair. Compare with the adjacent method, using the quasi-adjacent method show Re(Z) is two times higher, Imag(Z) is ten times higher, and a higher and homogeneous sensitivity map area are 60% wider. A negative resistance at high-frequency measurement also can be eliminated successfully by using the proposed method.

Experimental measurement of oil–water two-phase flow by data fusion of electrical tomography sensors and venturi tube

Oil–water two-phase flows are commonly found in the production processes of the petroleum industry. Accurate online measurement of flow rates is crucial to ensure the safety and efficiency of oil exploration and production. A research team from Tsinghua University has developed an experimental apparatus for multiphase flow measurement based on an electrical capacitance tomography (ECT) sensor, an electrical resistance tomography (ERT) sensor, and a venturi tube. This work presents the phase fraction and flow rate measurements of oil–water two-phase flows based on the developed apparatus. Full-range phase fraction can be obtained by the combination of the ECT sensor and the ERT sensor. By data fusion of differential pressures measured by venturi tube and the phase fraction, the total flow rate and single-phase flow rate can be calculated. Dynamic experiments were conducted on the multiphase flow loop in horizontal and vertical pipelines and at various flow rates.

Electrical Resistance Tomography Sensor for Highly Conductive Oil-Water Two-Phase Flow Measurement

Oil-water two-phase flows are encountered in various process industries, such as petroleum and chemical. The measurement of oil volume fraction and its distribution is of particular importance for managing oil production and water disposal and/or water reinjection. The water phase in these environments always has high electrical conductivity, which incurs significant difficulties for oil volume fraction measurement using electrical resistance tomography (ERT). In this paper, a method of solving this problem is introduced. A pilot plant scale flow loop at TUV NEL Ltd. was used to measure oil distribution and oil volume fraction in the range of 0–0.4. The total volumetric flow rate of oil and water was 30, 60, and 90 $\text{m}^{3}$ /h. High-electrical conductivity of water in 27.6 mS/cm was applied as continuous phase. The measurement results from ERT were validated by the readings of NEL’s references and flow patterns were compared with visual observation, which demonstrated that ERT was able to visualize the oil phase distribution and monitor the local and overall oil volume fraction up to 0.4.