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Selected Papers from the 9th World Congress on Industrial Process Tomography

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 May 2019) | Viewed by 54015

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Manuchehr Soleimani

E-Mail Website
Guest Editor
EEE Department, University of Bath, Bath BA1 8BE, UK
Interests: inverse problems; tomography; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Thomas Wondrak

E-Mail Website
Guest Editor
Helmholtz-Zentrum Dresden-Rossendorf, Institut für Fluiddynamik, Abt. Magnetohydrodynamik, 01328 Dresden, Germany
Interests: metal flow imaging
Prof. Dr. Chao Tan

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Interests: process measurement and instrumentation; process tomography
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industrial Process Tomography (IPT) is a set of multi-dimensional sensor technologies that aim to provide unparalleled internal information of industrial processes used in many business sectors. The World Congress on Industrial Process Tomography (WCIPT) is the flagship conference of the International Society for Industrial Process Tomography (ISIPT. www.isipt.org), which is held every two years. After successful previous events: UK (1999), Germany (2001), Canada (2003), Japan (2005), Norway (2007), China (2010), Poland (2013), and Brazil (2016), this year, WCIPT-2018 will take place in Bath, UK, under the chairmanship of Prof. Manuchehr Soleimani.

This congress focuses on the state-of-the-art of industrial process tomography and its applications in various fields:

  1. New Generation Systems for Wider Support of Industrial Applications:
    1. Multi-modal and multi-spectral methods addressing complex process distributions.
    2. Multi-dimensional systems that radically extend length and/or temporal scales. 
    3. Smart tomographic systems that provide direct application data, or process control.
    4. Human-machine interaction in IPT systems.
    5. Machine learning from IPT data.
  2. New Developments in Foundational System Elements for Enhanced Process Interaction:
    1. Excitation and response sensing methods and topologies for all modes: e.g. acoustic, electrical, hard radiation, magnetic resonance, and positron-emission.
    2. Data acquisition architectures to enhance system performance for focussed IPT products.
    3. Integrated system design and packaging for special application needs such as intrinsic safety.
    4. Raw data processing such as direct inversion and high-speed reconstruction methods.
    5. Interpretation data processing yielding industry relevant information.
  3. Pioneering Industrial Case Studies
    1. Holistic study of industrial application for pilot investigation.
    2. Holistic study of industrial application for online control.

Prof. Dr. Manuchehr Soleimani
Dr. Thomas Wondrak
Prof. Dr. Chao Tan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Industrial process tomography
  • Super-sensing
  • Soft field tomography
  • Hard field tomography

Published Papers (15 papers)

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Editorial

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3 pages, 161 KiB  
Editorial
Selected Papers from the 9th World Congress on Industrial Process Tomography
by Manuchehr Soleimani, Thomas Wondrak and Chao Tan
Sensors 2019, 19(17), 3804; https://doi.org/10.3390/s19173804 - 03 Sep 2019
Cited by 1 | Viewed by 2101
Abstract
Industrial process tomography (IPT) is a set of multi-dimensional sensor technologies and methods that aim to provide unparalleled internal information on industrial processes used in many sectors [...] Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)

Research

Jump to: Editorial

19 pages, 11559 KiB  
Article
On the Implementation of Simultaneous Multi-Frequency Excitations and Measurements for Electrical Impedance Tomography
by Mathieu Darnajou, Antoine Dupré, Chunhui Dang, Guillaume Ricciardi, Salah Bourennane and Cédric Bellis
Sensors 2019, 19(17), 3679; https://doi.org/10.3390/s19173679 - 24 Aug 2019
Cited by 13 | Viewed by 3747
Abstract
The investigation of quickly-evolving flow patterns in high-pressure and high-temperature flow rigs requires the use of a high-speed and non-intrusive imaging technique. Electrical Impedance Tomography (EIT) allows reconstructing the admittivity distribution characterizing a flow from the knowledge of currents and voltages on its [...] Read more.
The investigation of quickly-evolving flow patterns in high-pressure and high-temperature flow rigs requires the use of a high-speed and non-intrusive imaging technique. Electrical Impedance Tomography (EIT) allows reconstructing the admittivity distribution characterizing a flow from the knowledge of currents and voltages on its periphery. The need for images at high frame rates leads to the strategy of simultaneous multi-frequency voltage excitations and simultaneous current measurements, which are discriminated using fast Fourier transforms. The present study introduces the theory for a 16-electrode simultaneous EIT system, which is then built based on a field programmable gate array data acquisition system. An analysis of the propagation of uncertainties through the measurement process is investigated, and experimental results with fifteen simultaneous signals are presented. It is shown that the signals are successfully retrieved experimentally at a rate of 1953 frames per second. The associated signal-to-noise ratio varies from 59.6–69.1 dB, depending on the generated frequency. These preliminary results confirm the relevance and the feasibility of simultaneous multi-frequency excitations and measurements in EIT as a means to significantly increase the imaging rate. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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18 pages, 9193 KiB  
Article
3D-Printed Multilayer Sensor Structure for Electrical Capacitance Tomography
by Aleksandra Kowalska, Robert Banasiak, Andrzej Romanowski and Dominik Sankowski
Sensors 2019, 19(15), 3416; https://doi.org/10.3390/s19153416 - 04 Aug 2019
Cited by 25 | Viewed by 4446
Abstract
Presently, Electrical Capacitance Tomography (ECT) is positioned as a relatively mature and inexpensive tool for the diagnosis of non-conductive industrial processes. For most industrial applications, a hand-made approach for an ECT sensor and its 3D extended structure fabrication is used. Moreover, a hand-made [...] Read more.
Presently, Electrical Capacitance Tomography (ECT) is positioned as a relatively mature and inexpensive tool for the diagnosis of non-conductive industrial processes. For most industrial applications, a hand-made approach for an ECT sensor and its 3D extended structure fabrication is used. Moreover, a hand-made procedure is often inaccurate, complicated, and time-consuming. Another drawback is that a hand-made ECT sensor’s geometrical parameters, mounting base profile thickness, and electrode array shape usually depends on the structure of industrial test objects, tanks, and containers available on the market. Most of the traditionally fabricated capacitance tomography sensors offer external measurements only with electrodes localized outside of the test object. Although internal measurement is possible, it is often difficult to implement. This leads to limited in-depth scanning abilities and poor sensitivity distribution of traditionally fabricated ECT sensors. In this work we propose, demonstrate, and validate experimentally a new 3D ECT sensor fabrication process. The proposed solution uses a computational workflow that incorporates both 3D computer modeling and 3D-printing techniques. Such a 3D-printed structure can be of any shape, and the electrode layout can be easily fitted to a broad range of industrial applications. A developed solution offers an internal measurement due to negligible thickness of sensor mount base profile. This paper analyses and compares measurement capabilities of a traditionally fabricated 3D ECT sensor with novel 3D-printed design. The authors compared two types of the 3D ECT sensors using experimental capacitance measurements for a set of low-contrast and high-contrast permittivity distribution phantoms. The comparison demonstrates advantages and benefits of using the new 3D-printed spatial capacitance sensor regarding the significant fabrication time reduction as well as the improvement of overall measurement accuracy and stability. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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18 pages, 4928 KiB  
Article
X-ray Imaging Analysis of Silo Flow Parameters Based on Trace Particles Using Targeted Crowdsourcing
by Andrzej Romanowski, Piotr Łuczak and Krzysztof Grudzień
Sensors 2019, 19(15), 3317; https://doi.org/10.3390/s19153317 - 28 Jul 2019
Cited by 22 | Viewed by 3523
Abstract
This paper presents a novel method for tomographic measurement and data analysis based on crowdsourcing. X-ray radiography imaging was initially applied to determine silo flow parameters. We used traced particles immersed in the bulk to investigate gravitational silo flow. The reconstructed images were [...] Read more.
This paper presents a novel method for tomographic measurement and data analysis based on crowdsourcing. X-ray radiography imaging was initially applied to determine silo flow parameters. We used traced particles immersed in the bulk to investigate gravitational silo flow. The reconstructed images were not perfect, due to inhomogeneous silo filling and nonlinear attenuation of the X-rays on the way to the detector. Automatic processing of such data is not feasible. Therefore, we used crowdsourcing for human-driven annotation of the trace particles. As we aimed to extract meaningful flow parameters, we developed a modified crowdsourcing annotation method, focusing on selected important areas of the silo pictures only. We call this method “targeted crowdsourcing”, and it enables more efficient crowd work, as it is focused on the most important areas of the image that allow determination of the flow parameters. The results show that it is possible to analyze volumetric material structure movement based on 2D radiography data showing the location and movement of tiny metal trace particles. A quantitative description of the flow obtained from the horizontal and vertical velocity components was derived for different parts of the model silo volume. Targeting the attention of crowd workers towards either a specific zone or a particular particle speeds up the pre-processing stage while preserving the same quality of the output, quantified by important flow parameters. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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18 pages, 64934 KiB  
Article
Smart Water Meter Using Electrical Resistance Tomography
by Chenning Wu, Martin Hutton and Manuchehr Soleimani
Sensors 2019, 19(14), 3043; https://doi.org/10.3390/s19143043 - 10 Jul 2019
Cited by 7 | Viewed by 3672
Abstract
Smart flow monitoring is critical for sewer system management. Obstructions and restrictions to flow in discharge pipes are common and costly. We propose the use of electrical resistance tomography modality for the task of smart wastewater metering. This paper presents the electronics hardware [...] Read more.
Smart flow monitoring is critical for sewer system management. Obstructions and restrictions to flow in discharge pipes are common and costly. We propose the use of electrical resistance tomography modality for the task of smart wastewater metering. This paper presents the electronics hardware design and bespoke signal processing to create an embedded sensor for measuring flow rates and flow properties, such as constituent materials in sewage or grey water discharge pipes of diameters larger than 250 mm. The dedicated analogue signal conditioning module, zero-cross switching scheme, and real-time operating system enable the system to perform low-cost serial measurements while still providing the capability of real-time capturing. The system performance was evaluated via both stationary and dynamic experiments. A data acquisition speed of 14 frames per second (fps) was achieved with an overall signal to noise ratio of at least 59.54 dB. The smallest sample size reported was 0.04% of the domain size in stationary tests, illustrating good resolution. Movements have been successfully captured in dynamic tests, with a clear definition being achieved of objects in each reconstructed image, as well as a fine overall visualization of movement. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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17 pages, 4271 KiB  
Article
Nanoparticle Assisted EOR during Sand-Pack Flooding: Electrical Tomography to Assess Flow Dynamics and Oil Recovery
by Phillip Nwufoh, Zhongliang Hu, Dongsheng Wen and Mi Wang
Sensors 2019, 19(14), 3036; https://doi.org/10.3390/s19143036 - 10 Jul 2019
Cited by 7 | Viewed by 3274
Abstract
Silica nanoparticles have been shown to exhibit many characteristics that allow for additional oil to be recovered during sand-pack flooding experiments. Additionally various imaging techniques have been employed in the past to visually compare flooding procedures including x-ray computed tomography and magnetic resonance [...] Read more.
Silica nanoparticles have been shown to exhibit many characteristics that allow for additional oil to be recovered during sand-pack flooding experiments. Additionally various imaging techniques have been employed in the past to visually compare flooding procedures including x-ray computed tomography and magnetic resonance imaging; however, these techniques require the sample to be destroyed or sliced after the flooding experiment finishes. Electrical resistance tomography (ERT) overcomes these limitations by offering a non-destructive visualization method allowing for online images to be taken during the flooding process by the determination of spatial distribution of electrical resistivity, thus making it suitable for sand-packs. During the scope of this research a new sand-pack system and methodology was created which utilized ERT as a monitoring tool. Two concentrations, 0.5 wt% and 1.0 wt%, of SiO2 nanoparticles were compared with runs using only brine to compare the recovery efficiency and explore the ability of ERT to monitor the flooding process. Electrical resistance tomography was found to be an effective tool in monitoring local recovery efficiency revealing 1.0 wt% SiO2 to be more effective than 0.5 wt% and brine only runs during the scope of this research. A new method involving the slope function in excel was used to compare the effects of nanofluids on resistivity trends also revealing information about the rate of recovery against time. SiO2 nanofluid recovery mechanisms such interfacial tension reduction and viscosity enhancement were then considered to explain why the nanofluids resulted in greater oil recovery. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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17 pages, 45097 KiB  
Article
Monitoring Surface Defects Deformations and Displacements in Hot Steel Using Magnetic Induction Tomography
by Fang Li, Stefano Spagnul, Victor Odedo and Manuchehr Soleimani
Sensors 2019, 19(13), 3005; https://doi.org/10.3390/s19133005 - 08 Jul 2019
Cited by 7 | Viewed by 3368
Abstract
Magnetic Induction Tomography (MIT) is a non-invasive imaging technique that has been widely applied for imaging materials with high electrical conductivity contrasts. Steel production is among an increasing number of applications that require a contactless method for monitoring the casting process due to [...] Read more.
Magnetic Induction Tomography (MIT) is a non-invasive imaging technique that has been widely applied for imaging materials with high electrical conductivity contrasts. Steel production is among an increasing number of applications that require a contactless method for monitoring the casting process due to the high temperature of hot steel. In this paper, an MIT technique is proposed for detecting defects and deformations in the external surfaces of metal, which has the potential to be used to monitor the external surface of hot steel during the continuous casting process. The Total Variation (TV) reconstruction algorithm was developed to image the conductivity distributions. Nonetheless, the reconstructed image of the deformed square metal obtained using the TV algorithm directly does not yield resonable images of the surface deformation. However, differential images obtained by subtracting the image of a perfect square metal with no deformations from the image obtained for a deformed square metal does provide accurate and repeatable deformation information. It is possible to obtain a more precise image of surface deformation by thresholding the differential image. This TV-based threshold-differencing method has been analysed and verified from both simulation and experimental tests. The simulation results reported that 0.92 % of the image region can be detected, and the experimental results indicated a 0.57 % detectability. Use of the proposed method was demonstareted in a MIT device which was used in continuous casting set up. The paper shows results from computer simulation, lab based cold tests, and real life data from continoeus cating demonstating the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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15 pages, 9779 KiB  
Article
Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography
by Jan Porzuczek
Sensors 2019, 19(12), 2807; https://doi.org/10.3390/s19122807 - 23 Jun 2019
Cited by 13 | Viewed by 3291
Abstract
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). [...] Read more.
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. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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16 pages, 8755 KiB  
Article
Detection of Single Steel Strand Distribution in Grouting Duct Based on Capacitive Sensing Technique
by Nan Li, Mingchen Cao, Hangben Du, Cunfu He and Bin Wu
Sensors 2019, 19(11), 2564; https://doi.org/10.3390/s19112564 - 05 Jun 2019
Cited by 8 | Viewed by 2867
Abstract
Grouting ducts (containing steel strands) are widely used to increase the structural strengths of infrastructures. The determination of the steel strand’s integrity inside of ducts and the grouting quality are important for a strength evaluation of the structure. In this study, a capacitive [...] Read more.
Grouting ducts (containing steel strands) are widely used to increase the structural strengths of infrastructures. The determination of the steel strand’s integrity inside of ducts and the grouting quality are important for a strength evaluation of the structure. In this study, a capacitive sensing technique was applied to identify the cross-sectional distribution of the steel strands. The distribution was expressed in polar coordinates in an external post-tensioned pre-stressed duct model. An improved capacitive sensor structure was designed, which consisted of four electrodes, and different electrode-pairs were used to determine various locations’ information of the steel strands. Two rounds of measurements were conducted using the designed sensor to detect the angle (θ) and center distance (r) of the steel strand in the duct. The simulated and experimental results are presented and analyzed. In general, it is difficult to locate the angle of a steel strand directly from first-round capacitance measurements by analyzing the experimental results. Our method based on Q-factor analysis was presented for the position detection of a steel bar in an external post-tensioned pre-stressed duct. The center distance of the steel bar could be identified by second-round capacitance measurements. The processed results verified the effectiveness of the proposed capacitive sensor structure. Thus, the capacitive sensing technique exhibited potential for steel strand cross-section distribution detection in external post-tensioned pre-stressed ducts. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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20 pages, 3468 KiB  
Article
On the Design of a New Simulated Inductor Using a Contactless Electrical Tomography System as an Example
by Xin Ye, Yuxin Wang, Xiao-Yu Tang, Haifeng Ji, Baoliang Wang and Zhiyao Huang
Sensors 2019, 19(11), 2463; https://doi.org/10.3390/s19112463 - 29 May 2019
Cited by 7 | Viewed by 3146
Abstract
This work reports a new simulated inductor which is suitable for a Contactless Electrical Tomography (CET) system and can effectively overcome the unfavorable influence of coupling capacitance on the measurement results. By detailed analysis and comparison, it is found that the grounded simulated [...] Read more.
This work reports a new simulated inductor which is suitable for a Contactless Electrical Tomography (CET) system and can effectively overcome the unfavorable influence of coupling capacitance on the measurement results. By detailed analysis and comparison, it is found that the grounded simulated inductor has a simple circuit construction but its output current is not equal to its input current, while the floating simulated inductor can be used as an independent inductor module but its circuit structure is relatively complex. A new simulated inductor is designed by compensating the currents from the common node of an introduced independent power source to the main circuit. The new simulated inductor combines the advantages of the grounded simulated inductor and the floating simulated inductor. It has the simple construction similar to that of the grounded simulated inductor and its input current is equal to the output current, which means it can be used as an independent module. The impedance measurement and practical image reconstruction experiments were carried out to verify the effectiveness of the new simulated inductor. The experimental results show that the design of the new simulated inductor is successful, and the performance of the impedance measurement is satisfactory. The signal-to-noise ratio of the CET system is improved. Meanwhile, the research work also indicates that in the case when the independent power source is not available, the new simulated inductor is also an effective alternative method. But the phase difference between input signal and output signal is approximately 90° when the elimination principle is realized. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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22 pages, 8306 KiB  
Article
Focusing Sensor Design for Open Electrical Impedance Tomography Based on Shape Conformal Transformation
by Yu Wang, Shangjie Ren and Feng Dong
Sensors 2019, 19(9), 2060; https://doi.org/10.3390/s19092060 - 02 May 2019
Cited by 9 | Viewed by 3363
Abstract
Electrical Impedance Tomography (EIT) is a non-invasive detection method to image the conductivity changes inside an observation region by using the electrical measurements at the boundary of this region. In some applications of EIT, the observation domain is infinite and is only accessible [...] Read more.
Electrical Impedance Tomography (EIT) is a non-invasive detection method to image the conductivity changes inside an observation region by using the electrical measurements at the boundary of this region. In some applications of EIT, the observation domain is infinite and is only accessible from one side, which leads to the so-called open EIT (OEIT) problem. Compared with conventional EIT problems, the observation region in OEIT can only be measured from limited projection directions, which makes high resolution imaging much more challenging. To improve the imaging quality of OEIT, a focusing sensor design strategy is proposed based on shape conformal theory. The conformal bijection is used to map a standard EIT sensor defined at a unit circle to a focusing OEIT sensor defined at an upper half plane. A series of numerical and experimental testes are conducted. Compared with the traditional sensor structure, the proposed focusing sensor has higher spatial resolution at the near-electrode region and is good at distinguishing multi-inclusions which are close to each other. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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16 pages, 8470 KiB  
Article
Adaptive Selection of Truncation Radius in Calderon’s Method for Direct Image Reconstruction in Electrical Capacitance Tomography
by Shijie Sun, Lijun Xu, Zhang Cao, Jiangtao Sun and Wenbin Tian
Sensors 2019, 19(9), 2014; https://doi.org/10.3390/s19092014 - 29 Apr 2019
Cited by 3 | Viewed by 2762
Abstract
Calderon’s method has been successfully used for the direct image reconstruction in electrical capacitance tomography. In the method, the truncation radius adopted in numerical integral greatly influences the reconstruction results. In the past, the truncation radius is selected as a constant empirically according [...] Read more.
Calderon’s method has been successfully used for the direct image reconstruction in electrical capacitance tomography. In the method, the truncation radius adopted in numerical integral greatly influences the reconstruction results. In the past, the truncation radius is selected as a constant empirically according to the permittivity distribution pattern and noise level. In this paper, the influence of the truncation radius in Calderon’s method on the reconstruction results was first analyzed by numerical simulation. Then, a strategy for adaptive selection of the truncation radius was proposed. The amplitude information of the elements in the scattering transform matrix computed from the Dirichlet-to-Neumann (DN) map was used to determine the range for the truncation radius selection, and the phase information was further used to select a proper truncation radius value within this selection range. Finally, experiments were carried out to verify the strategy. Experimental results showed that small relative image error and good visual effect could be obtained by using the truncation radius selected by the proposed strategy. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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18 pages, 9517 KiB  
Article
A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction
by Guanghui Liang, Shangjie Ren, Shu Zhao and Feng Dong
Sensors 2019, 19(9), 1966; https://doi.org/10.3390/s19091966 - 26 Apr 2019
Cited by 26 | Viewed by 3688
Abstract
An image reconstruction method is proposed based on Lagrange-Newton method for electrical impedance tomography (EIT) and ultrasound tomography (UT) dual-modality imaging. Since the change in conductivity distribution is usually accompanied with the change in acoustic impedance distribution, the reconstruction targets of EIT and [...] Read more.
An image reconstruction method is proposed based on Lagrange-Newton method for electrical impedance tomography (EIT) and ultrasound tomography (UT) dual-modality imaging. Since the change in conductivity distribution is usually accompanied with the change in acoustic impedance distribution, the reconstruction targets of EIT and UT are unified to the conductivity difference using the same mesh model. Some background medium distribution information obtained from ultrasound transmission and reflection measurements can be used to construct a hard constraint about the conductivity difference distribution. Then, the EIT/UT dual-modality inverse problem is constructed by an equality constraint equation, and the Lagrange multiplier method combining Newton-Raphson iteration is used to solve the EIT/UT dual-modality inverse problem. The numerical and experimental results show that the proposed dual-modality image reconstruction method has a better performance than the single-modality EIT method and is more robust to the measurement noise. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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21 pages, 12824 KiB  
Article
Comparison of Selected Machine Learning Algorithms for Industrial Electrical Tomography
by Tomasz Rymarczyk, Grzegorz Kłosowski, Edward Kozłowski and Paweł Tchórzewski
Sensors 2019, 19(7), 1521; https://doi.org/10.3390/s19071521 - 28 Mar 2019
Cited by 78 | Viewed by 5475
Abstract
The main goal of this work was to compare the selected machine learning methods with the classic deterministic method in the industrial field of electrical impedance tomography. The research focused on the development and comparison of algorithms and models for the analysis and [...] Read more.
The main goal of this work was to compare the selected machine learning methods with the classic deterministic method in the industrial field of electrical impedance tomography. The research focused on the development and comparison of algorithms and models for the analysis and reconstruction of data using electrical tomography. The novelty was the use of original machine learning algorithms. Their characteristic feature is the use of many separately trained subsystems, each of which generates a single pixel of the output image. Artificial Neural Network (ANN), LARS and Elastic net methods were used to solve the inverse problem. These algorithms have been modified by a corresponding increase in equations (multiply) for electrical impedance tomography using the finite element method grid. The Gauss-Newton method was used as a reference to machine learning methods. The algorithms were trained using learning data obtained through computer simulation based on real models. The results of the experiments showed that in the considered cases the best quality of reconstructions was achieved by ANN. At the same time, ANN was the slowest in terms of both the training process and the speed of image generation. Other machine learning methods were comparable with the deterministic Gauss-Newton method and with each other. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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13 pages, 7934 KiB  
Article
Multiple Wire-Mesh Sensors Applied to the Characterization of Two-Phase Flow inside a Cyclonic Flow Distribution System
by César Y. Ofuchi, Henrique K. Eidt, Carolina C. Rodrigues, Eduardo N. Dos Santos, Paulo H. D. Dos Santos, Marco J. Da Silva, Flávio Neves, Jr., Paulo Vinicius S. R. Domingos and Rigoberto E. M. Morales
Sensors 2019, 19(1), 193; https://doi.org/10.3390/s19010193 - 07 Jan 2019
Cited by 14 | Viewed by 4565
Abstract
Wire-mesh sensors are used to determine the phase fraction of gas–liquid two-phase flow in many industrial applications. In this paper, we report the use of the sensor to study the flow behavior inside an offshore oil and gas industry device for subsea phase [...] Read more.
Wire-mesh sensors are used to determine the phase fraction of gas–liquid two-phase flow in many industrial applications. In this paper, we report the use of the sensor to study the flow behavior inside an offshore oil and gas industry device for subsea phase separation. The study focused on the behavior of gas–liquid slug flow inside a flow distribution device with four outlets, which is part of the subsea phase separator system. The void fraction profile and the flow symmetry across the outlets were investigated using tomographic wire-mesh sensors and a camera. Results showed an ascendant liquid film in the cyclonic chamber with the gas phase at the center of the pipe generating a symmetrical flow. Dispersed bubbles coalesced into a gas vortex due to the centrifugal force inside the cyclonic chamber. The behavior favored the separation of smaller bubbles from the liquid bulk, which was an important parameter for gas-liquid separator sizing. The void fraction analysis of the outlets showed an even flow distribution with less than 10% difference, which was a satisfactorily result that may contribute to a reduction on the subsea gas–liquid separators size. From the outcomes of this study, detailed information regarding this type of flow distribution system was extracted. Thereby, wire-mesh sensors were successfully applied to investigate a new type of equipment for the offshore oil and gas industry. Full article
(This article belongs to the Special Issue Selected Papers from the 9th World Congress on Industrial Process Tomography)
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