A Dual Mode Ultrasound and Electrical Capacitance Process Tomography Sensor

An electrical capacitance tomography (ECT) sensor consists of a number of electrodes, which are usually mounted around the external or internal periphery of a circular insulated pipe. Therefore, the diameter of a conventional ECT sensor is fixed. This paper presents a new structure of ECT sensor, which can achieve adjustable inner diameter of the sensor within a certain range, by re-engineering the traditional structure, and therefore the electrode-to-gap ratio (EGR) of the sensor is changed. The relationship between EGR and image quality was studied by simulation. A prototype ECT sensor with variable diameter was fabricated and evaluated with an impedance-analyzer based ECT system. The experimental results show that the ECT sensor with variable diameter can provide similar reconstructed images to a conventional ECT sensor, when the sensor diameter varies in a certain range, i.e. EGR above 6:1. Therefore, this new structure can enable the ECT sensor to be adapted to the change in diameter of the measured objects.

Ultrasound transmission tomography promises a high potential and novel imaging method for early breast cancer diagnosis; it can quantitatively characterize tissues or materials by the attenuation and speed of sound (SoS). Reconstruction of ultrasound transmission tomography is an inverse problem that can be solved iteratively based on a paraxial approximation of the Helmholtz equation as forward model, which is highly non-linear and time-consuming. In order to address these problems and reconstruct desired images, we design a dual domain network architecture for ultrasound transmission tomography reconstruction. It can enhance the information of measurement domain and directly reconstruct from pressure field measurements without using any initialization of reconstruction and fully connected layer. We train the network on simulated ImageNet data and transfer it for ultrasound transmission tomography images to avoid overfitting when the amount of ultrasound transmission tomography images is limited. Our experimental results demonstrate that a dual domain network produces significant improvements over state-of-the-art methods. It improves the measured structural similarity measure (SSIM) from 0.54 to 0.90 and normalized root mean squared error (nRMSE) from 0.49 to 0.01 on average concerning the SoS reconstruction, and from 0.46 to 0.98 for SSIM, from 353 to 0.03 for nRMSE on average concerning the attenuation reconstruction.

This article describes the recent progress in research and development on electrical capacitance tomography (ECT). Specifically, the article highlights several aspects of ECT including the electrical capacitance volume tomography (ECVT), 3D sensor design, 3D neural network multicriterion image reconstruction technique (3D-NN-MOIRT), multimodal imaging based on ECT and ECVT sensors, static-charge effects and the scheme of their elimination in the ECT image reconstruction, and multiphase flow imaging applications. The multimodal capability that enables permittivity and conductivity imaging to be simultaneously conducted is illustrated. The simulation and experimental results are presented to provide quantitative and/or qualitative assessment of the significance of various ECT techniques. The employment of ECVT in conjunction with using electrical capacitance based imaging sensors is shown to represent a favorable tool for industrial multiphase flow imaging.

This study addresses the issue of energy optimization by investigating solutions for the reduction of energy consumption in the diagnostics and monitoring of technological processes. The implementation of advanced process control is identified as a key approach for achieving energy savings and improving product quality, process efficiency, and production flexibility. The goal of this research is to develop a cost-effective system with a minimal number of ultrasound sensors, thus reducing the energy consumption of the overall system. To accomplish this, a novel method for obtaining high-resolution reconstruction in transmission ultrasound tomography (t-UST) is proposed. The method involves utilizing a convolutional neural network to take low-resolution measurements as input and output high-resolution sinograms that are used for tomography image reconstruction. This approach allows for the construction of a super-resolution sinogram by utilizing information hidden in the low-resolution measurement. The model is trained on simulation data and validated on real measurement data. The results of this technique demonstrate significant improvement compared to state-of-the-art methods. The study also highlights that UST measurements contain more information than previously thought, and this hidden information can be extracted and utilized with the use of machine learning techniques to further improve image quality and object recognition.

Electrical capacitance tomography (ECT) has been developed successfully for industrial applications. While most ECT sensors employ a circular structure with a closed sensing area, some other structures like square and parallel are needed for some particular applications. This paper describes a parallel structure ECT sensor, which can provide incomplete measurement data only. The performance of this parallel ECT sensor is discussed based on simulation study with 2D FEM models. Images of different permittivity distributions are generated by linear back-projection (LBP) and Landweber iteration algorithms. The effect of the effective sensing area and distance of parallel plates are also discussed. Both capacitance residual and correlation coefficient are used to evaluate the image quality. The results show that (1) the width of the sensing area should be the same as the shielding layer in order to acquire high quality image and (2) the distance between two parallel plates is suggested being equal to the shielding layer to compromise the sensing space and the sensitivity of the central region.

Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost, capability of forming real time imaging, and the continuing improvements in image quality. However; the usefulness of ultrasound imaging is degraded by the presence of signal dependant noise known as speckle. It is well-known that speckle is a multiplicative noise that degrades the visual evaluation in ultrasound imaging. In ultrasound (US) imaging, denoising is intended to improve quantitative image analysis techniques. In this paper, a new version of the Non Local (NL-) means filter adapted for US images is proposed based on Similarity function depend on specific characteristics of the variance speckle noise in ultrasound images. The proposed method has been compared with Median, Wavelet, Mean and variance local statistics, Geometric, Anisotropic diffusion filtering, and Non ' local means filter using quantitative parameters. From the visual results and image quality evaluation metrics obtained over real images we can conclude that the modified(NL-) means filter can be successfully used for ultrasound image denoising, and performs better results than all other methods while still retaining the structural details and retains the edges and textures very well while removing speckle noise.

Ultrasound (US) imaging application in medicine and other fields is enormous. It has several advantages over other medical imaging modalities. The use of US in diagnosis is well established because of its noninvasive nature, portable, accurate, low-cost imaging modality, capable of forming real-time imaging and continuing improvement in image quality. Medical images and satellite images are usually degraded by noise during image acquisition and transmission process. It is estimated that 1 out of every form medical diagnostic image studies in the world involves ultrasonic techniques. The objectives of this article are to give an overview of the types of speckle reduction techniques in US imaging, present a new technique of speckle reduction, and carry out a comparative evaluation of despeckle filtering based on image quality metrics. A new speckle suppression method and coherence enhancement of medical US image are proposed: 9 despeckled filtering techniques and 5 edge detection operators, with the result evaluated by image quality metrics. The best edge detection hybrid with best filter, quality evaluation metrics has been found that the proposed method performance better than all other methods, while the structural details and result preserving of small and important image feature that contain diagnostic information in a better way than other despeckling filter.

Electrical capacitance tomography (ECT) is used to obtain information about the distribution of a mixture of dielectric materials inside a vessel or pipe. ECT has several advantages over other reconstruction algorithms and has found many applications in the industrial fields. However, there are some difficulties with image reconstruction in ECT: The relationship between the permittivity distribution and measured capacitance is nonlinear. And inverse problem is ill-posed so that the inverse solution is sensitive to measurement error. To cope with these difficulties iterative image reconstruction algorithms have been developed. In general, the iterative reconstruction algorithms in ECT have comparatively good-quality in reconstructed images but result in intensive computational burden. This paper presents the iterative image reconstruction algorithm for ECT that can enhance the speed of image reconstruction without degradation in the quality of reconstructed image. The main contribution of the proposed algorithm is new weighting matrices, which are obtained by the interpolation of the grouped electrical field centre lines (EFCLs). Extensive simulation results have demonstrated that proposed algorithm provides improved reconstruction performance in terms of computational time and image quality.

To improve the quality of the reconstruction image for discontinuous media distribution areas, a total variation (TV) regularization based on bounded variation function was employed to solve the ill-posed problem of electrical capacitance tomography (ECT). By using TV regularization, an Euler equation, a non-linear partial differential equation, is derived to describe the ECT problem. However, it is very time consuming, if possible, for traditional methods to solve this Euler equation. This paper presents a new fixed-point iterative algorithm which can get the solution stably and rapidly. Numerical results show that the presented method improves the quality of the reconstruction image for discontinuous media distribution areas in ECT image reconstruction, and leads to the common boundary between different media clearer.Keywordselectrical capacitance tomography (ECT)image reconstructionill-posedtotal variation regularizationfixed-point iterative algorithm

Nowadays, the optimization of energy consumption and resources is one of the most urgent topics in worldwide industry. The energy consumption monitoring and control in various multiphase flow industrial applications, where a proper flow characteristic and an optimal phase mixture control is crucial, is hard to perform due to the physical and chemical complexity of the processes. The Electrical Capacitance Tomography (ECT) is one of the relatively cheap non-invasive measurement methods that can help in the monitoring and control of optimal energy and resources dozing in industrial processes. ECT diagnostics systems use unique sensors that can non-intrusively detect spatial capacitance changes caused by spatial changes in the electrical permittivity of industrial process components. One of the latest ECT extensions is a three-dimensional measurement strategy that uses a multilayer structure of the capacitance sensor. In this paper, the authors propose a novel approach to the 3D ECT sensors fabrication process that uses 3D computer modelling and 3D printing to easily get any sensor shape, electrode layout, scale and shielding strategy. This study compares the measurement abilities of a 3D ECT sensor fabricated using a traditional hand-made technique with the 3D printed device. The results have proven the potential of the new 3D print-based sensor regarding its significant fabrication time reduction as well as the improvement of the overall 3D ECT sensor measurement accuracy and stability.

Pipelines made of dielectric materials such as Polyethylene (PE) are becoming increasingly popular. With no suitable inspection technique for dielectric pipes, there is an urgent need to develop new technology for their inspection. This paper presents a novel pipe inspection technique using Electrical Capacitance Tomography (ECT) imaging. Traditionally ECT is used for industrial process tomography as a low resolution but fast tomographic imaging technique. Typically commercial ECT can provide a resolution of approximately 10 percent of the imaging region. In this paper a limited region tomography technique is developed take into account prior knowledge about the geometry of the pipe. This has signiflcantly enhanced the imaging resolution of the ECT system, making it a viable pipe inspection solution. The experimental results in this study demonstrate an interior wall loss area as small as 0.195 percent of the ECT cross sectional imaging region is repeatable and can be reliably detected. A narrowband pass fllter method (NPFM) is used as a means to limit the region for the ECT algorithm. This results in an unprecedented resolution, making ECT a viable non-destructive evaluation (NDE) technique for plastic pipes. The NDE application of the ECT for PE pipes is demonstrated in this paper with several experimental results. A wall loss of depth of 1.5mm could be detected for an ECT sensor array of 150mm in diameter, showing a high resolution and high deflnition ECT (HD-ECT) imaging that has not been reported before.

Measurement techniques are vital for the control and operation of multiphase oil–water flow in pipes. The development of such techniques depends on laboratory experiments involving flow visualization, liquid fraction (‘hold-up’), phase slip and pressure drop measurements. They provide valuable information by revealing the physics, spatial and temporal structures of complex multiphase flow phenomena.This paper presents the hold-up measurement of oil–water flow in pipelines using gamma densitometry and electrical capacitance tomography (ECT) sensors. The experiments were carried out with different pipe inclinations from −5° to +6° for selected mixture velocities (0.2–1.5 m s−1), and at selected watercuts (0.05–0.95). Mineral oil (Exxsol D60) and water were used as test fluids. Nine flow patterns were identified including a new pattern called stratified wavy and mixed interface flow. As a third direct method, visual observations and high-speed videos were used for the flow regime and interface identification.ECT and gamma densitometry hold-up measurements show similar trends for changes in pipeline inclinations. Changing the pipe inclination affected the flow mostly at lower mixture velocities and caused a change of flow patterns, allowing the highest change of hold-up. ECT hold-up measurements overpredict the gamma densitometry measurements at higher input water cuts and underpredict at intermediate water cuts. Gamma hold-up results showed good agreement with the literature results, having a maximum deviation of 6%, while it was as high as 22% for ECT in comparison to gamma densitometry.Uncertainty analysis of the measurement techniques was carried out with single-phase oil flow. This shows that the measurement error associated with gamma densitometry is approximately 3.2%, which includes 1.3% statistical error and 2.9% error identified as electromagnetically induced noise in electronics. Thus, gamma densitometry can predict hold-up with a higher accuracy in comparison to ECT when applied to oil–water systems at minimized electromagnetic noise.

The electrical capacitance tomography (ECT) technique has been extensively studied for real-time tomographic imaging of various industrial processes. Due to the ‘soft-field’ and under-determined problems in the image reconstruction, the tomographic images of ECT are usually low in the spatial resolution when compared with its radioactive counterparts, i.e. $\gamma $ -ray tomography and computed tomography. This paper presents an ECT sensor that consists of 8 external electrodes and 8 internal electrodes, with enhanced image quality at the center of imaging region and better accuracy on phase fraction measurement. The internal electrodes are placed on cross planes inside the investigated vessel. In this way, the signal-to-noise ratio of measurement channels as well as image quality are improved. Numerical simulations show that the proposed sensor can achieve better reconstructed images than a conventional 12-electrode sensor. In addition, the phase fraction calculation using ECT data can also benefit from the internal electrodes and corresponding measurements, which is an important parameter for multiphase flow processes.

Improving Image Quality by Deconvolution Recovery Filter in Ultrasound Imaging.

1 - Electrical Capacitance Tomography