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Tomographic Sensors for Industrial Process Control
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Tomographic Sensors for Industrial Process Control

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

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 40192

Special Issue Editor

Prof. Dr. Uwe Hampel

E-Mail Website
Guest Editor
Helmholtz-Zentrum Dresden-Rossendorf, Head Experimental Thermal Fluid Dynamics, Bautzner Landstraße 400, 01328 Dresden, Germany
Technische Universitaet Dresden, Chair of Imaging Techniques in Energy and Process Engineering, 01062 Dresden, Germany
Interests: thermal fluid dynamics; multiphase flow measurement; process tomography

Special Issue Information

Dear Colleagues,

Control systems in the process industry have the task of ensuring a stable processing of material streams within a well-defined sequence of operations. Such operations are, for instance, reaction, separation, crystallization, solidification, mixing, and drying. For that purpose, the contemporary process industry typically employs control systems with local sensors for, e.g., temperature, pressure, flow, and filling level. With the ongoing progress in sensor development, there is now a growing interest in using sensors with higher complexity in industrial control systems. One such category is process tomography sensors.

Process tomography is an established class of imaging techniques, used to obtain 2D or 3D information of the distribution and flow of materials in pipes and vessels. Compared to its counterparts in medical diagnostics and non-destructive testing, process tomography typically targets high scanning speed rather than high spatial resolution. In recent years, a number of different process tomography modalities have evolved. These are, for example, electrical tomography, magnetic tomography, ultrasound tomography, microwave tomography, and optical tomography. However, some of the classical tomography modalities, such as X-ray tomography, emission tomography, and magnetic resonance imaging, have also been made fast enough to study industrial processes.

With respect to industrial process control, tomographic imaging had so far been of lesser consideration as real time reconstruction and feature extraction was difficult to achieve. However, recent developments in powerful and smart massive parallel computing architectures have changed the game. Process tomography can now be turned into a powerful sensor element for tomography-based process control.

The Special Issue invites researchers from different fields to publish their latest scientific and technical achievements in the field of process control using process tomography techniques. The focus of this Special Issue is on a holistic demonstration of this technology for typical industrial processes, preferably in the fields of chemical, environmental, and energy engineering. Demonstration may be in real industrial systems or in a laboratory environment. Presented technical solutions should include tomography sensors, data processing, and control strategies with at least a proof of principle. Contributions may furthermore deal with new concepts for hardware and software, e.g., real-time tomographic sensing and data processing as well as novel theoretical control concepts for the use of tomography sensors in control loops.

Prof. Dr. Uwe Hampel
Guest Editor

Manuscript Submission Information

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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

  • process tomography sensors
  • industrial process control
  • control systems in process engineering
  • real-time image and data processing
  • feature extraction
  • parallel computing

Published Papers (16 papers)

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33 pages, 6196 KiB  
Article
Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation
by Matheus M. Garcia, Muhammad A. Sattar, Hanane Atmani, Dominique Legendre, Laurent Babout, Eckhard Schleicher, Uwe Hampel and Luis M. Portela
Sensors 2022, 22(12), 4443; https://0-doi-org.brum.beds.ac.uk/10.3390/s22124443 - 12 Jun 2022
Cited by 2 | Viewed by 1807
Abstract
The performance of multiphase flow processes is often determined by the distribution of phases inside the equipment. However, controllers in the field are typically implemented based on flow variables, which are simpler to measure, but indirectly connected to performance (e.g., pressure). Tomography has [...] Read more.
The performance of multiphase flow processes is often determined by the distribution of phases inside the equipment. However, controllers in the field are typically implemented based on flow variables, which are simpler to measure, but indirectly connected to performance (e.g., pressure). Tomography has been used in the study of the distribution of phases of multiphase flows for decades, but only recently, the temporal resolution of the technique was sufficient for real-time reconstructions of the flow. Due to the strong connection between the performance and distribution of phases, it is expected that the introduction of tomography to the real-time control of multiphase flows will lead to substantial improvements in the system performance in relation to the current controllers in the field. This paper uses a gas–liquid inline swirl separator to analyze the possibilities and limitations of tomography-based real-time control of multiphase flow processes. Experiments were performed in the separator using a wire-mesh sensor (WMS) and a high-speed camera to show that multiphase flows have two components in their dynamics: one intrinsic to its nonlinear physics, occurring independent of external process disturbances, and one due to process disturbances (e.g., changes in the flow rates of the installation). Moreover, it is shown that the intrinsic dynamics propagate from upstream to inside the separator and can be used in predictive and feedforward control strategies. In addition to the WMS experiments, a proportional–integral feedback controller based on electrical resistance tomography (ERT) was implemented in the separator, with successful results in relation to the control of the distribution of phases and impact on the performance of the process: the capture of gas was increased from 76% to 93% of the total gas with the tomography-based controller. The results obtained with the inline swirl separator are extended in the perspective of the tomography-based control of quasi-1D multiphase flows. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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22 pages, 10357 KiB  
Article
Monitoring and Visualization of Crystallization Processes Using Electrical Resistance Tomography: CaCO3 and Sucrose Crystallization Case Studies
by Guruprasad Rao, Soheil Aghajanian, Yuchong Zhang, Lidia Jackowska-Strumiłło, Tuomas Koiranen and Morten Fjeld
Sensors 2022, 22(12), 4431; https://0-doi-org.brum.beds.ac.uk/10.3390/s22124431 - 11 Jun 2022
Viewed by 1939
Abstract
In the current research work, electrical resistance tomography (ERT) was employed for monitoring and visualization of crystallization processes. A first-of-its-kind MATLAB-based interactive GUI application “ERT-Vis” is presented. Two case studies involving varied crystallization methods were undertaken. The experiments were designed and performed involving [...] Read more.
In the current research work, electrical resistance tomography (ERT) was employed for monitoring and visualization of crystallization processes. A first-of-its-kind MATLAB-based interactive GUI application “ERT-Vis” is presented. Two case studies involving varied crystallization methods were undertaken. The experiments were designed and performed involving calcium carbonate reactive (precipitative) crystallization for the high conductivity solution-solute media, and the cooling crystallization of sucrose representing the lower conductivity solution–solute combination. The software successfully provided key insights regarding the process in both crystallization systems. It could detect and separate the solid concentration distributions in the low as well as high conductivity solutions using the visual analytics tools provided. The performance and utility of the software were studied using a software evaluation case study involving domain experts. Participant feedback indicated that ERT-Vis software helps by reconstructing images instantaneously, interactively visualizing, and evaluating the output of the crystallization process monitoring data. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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21 pages, 5571 KiB  
Article
Contactless Inductive Flow Tomography for Real-Time Control of Electromagnetic Actuators in Metal Casting
by Ivan Glavinić, Vladimir Galindo, Frank Stefani, Sven Eckert and Thomas Wondrak
Sensors 2022, 22(11), 4155; https://0-doi-org.brum.beds.ac.uk/10.3390/s22114155 - 30 May 2022
Cited by 4 | Viewed by 1678
Abstract
Flow control of liquid metals based on the actual flow condition is important in many metallurgical applications. For instance, the liquid steel flow in the mould of a continuous caster strongly influences the product quality. The flow can be modified by an electromagnetic [...] Read more.
Flow control of liquid metals based on the actual flow condition is important in many metallurgical applications. For instance, the liquid steel flow in the mould of a continuous caster strongly influences the product quality. The flow can be modified by an electromagnetic brake (EMBr). However, due to the lack of appropriate flow measurement techniques, the control of those actuators is usually not based on the actual flow condition. This article describes the recent developments of the Contactless Inductive Flow Tomography (CIFT) towards a real-time monitoring system, which can be used as an input to the control loop for an EMBr. CIFT relies on measuring the flow-induced perturbation of an applied magnetic field and the solution of an underlying linear inverse problem. In order to implement the CIFT reconstructions in combination with EMBr, two issues have to be solved: (i) compensation of the effects of the change in EMBr strength on the CIFT measurement system and (ii) a real-time solution of the inverse problem. We present solutions of both problems for a model of a continuous caster with a ruler-type EMBr. The EMBr introduces offsets of the measured magnetic field that are several orders of magnitude larger than the very flow-induced perturbations. The offset stems from the ferromagnetic hysteresis exhibited by the ferrous parts of the EMBr in the proximity of the measurement coils. Compensation of the offset was successfully achieved by implementing a numerical model of hysteresis to predict the offset. Real-time reconstruction was achieved by precalculating the computationally heavy matrix inverses for a predefined set of regularization parameters and choosing the optimal one in every measurement frame. Finally, we show that this approach does not hinder the reconstruction quality. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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15 pages, 4844 KiB  
Article
Laboratory Investigation of Tomography-Controlled Continuous Steel Casting
by Ivan Glavinić, Imamul Muttakin, Shereen Abouelazayem, Artem Blishchik, Frank Stefani, Sven Eckert, Manuchehr Soleimani, Iheb Saidani, Jaroslav Hlava, Saša Kenjereš and Thomas Wondrak
Sensors 2022, 22(6), 2195; https://0-doi-org.brum.beds.ac.uk/10.3390/s22062195 - 11 Mar 2022
Cited by 6 | Viewed by 2233
Abstract
More than 96% of steel in the world is produced via the method of continuous casting. The flow condition in the mould, where the initial solidification occurs, has a significant impact on the quality of steel products. It is important to have timely, [...] Read more.
More than 96% of steel in the world is produced via the method of continuous casting. The flow condition in the mould, where the initial solidification occurs, has a significant impact on the quality of steel products. It is important to have timely, and perhaps automated, control of the flow during casting. This work presents a new concept of using contactless inductive flow tomography (CIFT) as a sensor for a novel controller, which alters the strength of an electromagnetic brake (EMBr) of ruler type based on the reconstructed flow structure in the mould. The method was developed for the small-scale Liquid Metal Model for Continuous Casting (mini-LIMMCAST) facility available at the Helmholtz-Zentrum Dresden-Rossendorf. As an example of an undesired flow condition, clogging of the submerged entry nozzle (SEN) was modelled by partly closing one of the side ports of the SEN; in combination with an active EMBr, the jet penetrates deeper into the mould than when the EMBr is switched off. Corresponding flow patterns are detected by extracting the impingement position of the jets at the narrow faces of the mould from the CIFT reconstruction. The controller is designed to detect to undesired flow condition and switch off the EMBr. The temporal resolution of CIFT is 0.5 s. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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24 pages, 7041 KiB  
Article
A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows
by Muhammad Awais Sattar, Matheus Martinez Garcia, Luis M. Portela and Laurent Babout
Sensors 2022, 22(5), 1834; https://0-doi-org.brum.beds.ac.uk/10.3390/s22051834 - 25 Feb 2022
Cited by 5 | Viewed by 1766
Abstract
Electrical resistance tomography (ERT) has been used in the literature to monitor the gas–liquid separation. However, the image reconstruction algorithms used in the studies take a considerable amount of time to generate the tomograms, which is far above the time scales of the [...] Read more.
Electrical resistance tomography (ERT) has been used in the literature to monitor the gas–liquid separation. However, the image reconstruction algorithms used in the studies take a considerable amount of time to generate the tomograms, which is far above the time scales of the flow inside the inline separator and, as a consequence, the technique is not fast enough to capture all the relevant dynamics of the process, vital for control applications. This article proposes a new strategy based on the physics behind the measurement and simple logics to monitor the separation with a high temporal resolution by minimizing both the amount of data and the calculations required to reconstruct one frame of the flow. To demonstrate its potential, the electronics of an ERT system are used together with a high-speed camera to measure the flow inside an inline swirl separator. For the 16-electrode system used in this study, only 12 measurements are required to reconstruct the whole flow distribution with the proposed algorithm, 10× less than the minimum number of measurements of ERT (120). In terms of computational effort, the technique was shown to be 1000× faster than solving the inverse problem non-iteratively via the Gauss–Newton approach, one of the computationally cheapest techniques available. Therefore, this novel algorithm has the potential to achieve measurement speeds in the order of 104 times the ERT speed in the context of inline swirl separation, pointing to flow measurements at around 10kHz while keeping the average estimation error below 6 mm in the worst-case scenario. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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14 pages, 5841 KiB  
Article
Non-Contact Paper Thickness and Quality Monitoring Based on Mid-Infrared Optical Coherence Tomography and THz Time Domain Spectroscopy
by Rasmus Eilkær Hansen, Thorsten Bæk, Simon Lehnskov Lange, Niels Møller Israelsen, Markku Mäntylä, Ole Bang and Christian Rosenberg Petersen
Sensors 2022, 22(4), 1549; https://0-doi-org.brum.beds.ac.uk/10.3390/s22041549 - 17 Feb 2022
Cited by 5 | Viewed by 2774
Abstract
In industrial paper production, online monitoring of a range of quality parameters is essential for ensuring that the performance and appearance of the final product is suitable for a given application. In this article, two optical sensing techniques are investigated for non-destructive, non-contact [...] Read more.
In industrial paper production, online monitoring of a range of quality parameters is essential for ensuring that the performance and appearance of the final product is suitable for a given application. In this article, two optical sensing techniques are investigated for non-destructive, non-contact characterization of paper thickness, surface roughness, and production defects. The first technique is optical coherence tomography based on a mid-infrared supercontinuum laser, which can cover thicknesses from ~20–90 μm and provide information about the surface finish. Detection of subsurface voids, cuts, and oil contamination was also demonstrated. The second technique is terahertz time domain spectroscopy, which is used to measure paper thicknesses of up to 443 μm. A proof-of-concept thickness measurement in freely suspended paper was also demonstrated. These demonstrations highlight the added functionality and potential of tomographic optical sensing methods towards industrial non-contact quality monitoring. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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16 pages, 13033 KiB  
Article
On-Line Multi-Frequency Electrical Resistance Tomography (mfERT) Device for Crystalline Phase Imaging in High-Temperature Molten Oxide
by Prima Asmara Sejati, Noritaka Saito, Yosephus Ardean Kurnianto Prayitno, Koji Tanaka, Panji Nursetia Darma, Miku Arisato, Kunihiko Nakashima and Masahiro Takei
Sensors 2022, 22(3), 1025; https://0-doi-org.brum.beds.ac.uk/10.3390/s22031025 - 28 Jan 2022
Cited by 9 | Viewed by 2260
Abstract
An on-line multi-frequency electrical resistance tomography (mfERT) device with a melt-resistive sensor and noise reduction hardware has been proposed for crystalline phase imaging in high-temperature molten oxide. The melt-resistive sensor consists of eight electrodes made of platinum-rhodium (Pt-20mass%Rh) alloy covered by [...] Read more.
An on-line multi-frequency electrical resistance tomography (mfERT) device with a melt-resistive sensor and noise reduction hardware has been proposed for crystalline phase imaging in high-temperature molten oxide. The melt-resistive sensor consists of eight electrodes made of platinum-rhodium (Pt-20mass%Rh) alloy covered by non-conductive aluminum oxide (Al2O3) to prevent an electrical short. The noise reduction hardware has been designed by two approaches: (1) total harmonic distortion (THD) for the robust multiplexer, and (2) a current injection frequency pair: low fL and high fH, for thermal noise compensation. THD is determined by a percentage evaluation of k-th harmonic distortions of ZnO at f=0.1~10,000 Hz. The fL and fH are determined by the thermal noise behavior estimation at different temperatures. At  f <100 Hz, the THD percentage is relatively high and fluctuates; otherwise, THD dramatically declines, nearly reaching zero. At the determined fL≥ 10,000 Hz and fH≈ 1,000,000 Hz, thermal noise is significantly compensated. The on-line mfERT was tested in the experiments of a non-conductive Al2O3 rod dipped into conductive molten zinc-borate (60ZnO-40B2O3) at 1000~1200 °C. As a result, the on-line mfERT is able to reconstruct the Al2O3 rod inclusion images in the high-temperature fields with low error, ςfL, T = 5.99%, at 1000 °C, and an average error ⟨ςfL⟩ = 9.2%. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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22 pages, 13852 KiB  
Article
A Model-Based Analysis of Capacitive Flow Metering for Pneumatic Conveying Systems: A Comparison between Calibration-Based and Tomographic Approaches
by Thomas Suppan, Markus Neumayer, Thomas Bretterklieber, Stefan Puttinger and Hannes Wegleiter
Sensors 2022, 22(3), 856; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030856 - 23 Jan 2022
Cited by 8 | Viewed by 2474
Abstract
Pneumatic conveying is a standard transportation technique for bulk materials in various industrial fields. Flow metering is crucial for the efficient and reliable operation of such systems and for process control. Capacitive measurement systems are often proposed for this application. In this method, [...] Read more.
Pneumatic conveying is a standard transportation technique for bulk materials in various industrial fields. Flow metering is crucial for the efficient and reliable operation of such systems and for process control. Capacitive measurement systems are often proposed for this application. In this method, electrodes are placed on the conveyor systems transport line and capacitive signals are sensed. The design of the sensor with regard to the arrangement and the number of electrodes as well as the evaluation of the capacitive sensor signals can be divided into two categories. Calibration-based flow meters use regression methods for signal processing, which are parametrized from calibration measurements on test rigs. Their performance is limited by the extend of the calibration measurements. Electrical capacitance tomography based flow meters use model-based signal processing techniques to obtain estimates about the spatial material distribution within the sensor. In contrast to their calibration-based counterparts, this approach requires more effort with respect to modeling and instrumentation, as typically a larger number of measurement signals has to be acquired. In this work we present a comparative analysis of the two approaches, which is based on measurement experiments and a holistic system model for flow metering. For the model-based analysis Monte Carlo simulations are conducted, where randomly generated pneumatic conveying flow patterns are simulated to analyze the sensor and algorithm behavior. The results demonstrate the potential benefit of electrical capacitance tomography based flow meters over a calibration-based instrument design. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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20 pages, 2863 KiB  
Article
An Electromagnetic Time-Reversal Imaging Algorithm for Moisture Detection in Polymer Foam in an Industrial Microwave Drying System
by Adel Omrani, Rahul Yadav, Guido Link, Timo Lähivaara, Marko Vauhkonen and John Jelonnek
Sensors 2021, 21(21), 7409; https://0-doi-org.brum.beds.ac.uk/10.3390/s21217409 - 08 Nov 2021
Cited by 5 | Viewed by 2690
Abstract
Microwave tomography (MWT) based control is a novel idea in industrial heating systems for drying polymer foam. In this work, an X-band MWT module is designed and developed using a fixed antenna array configuration and integrated with the HEPHAISTOS industrial heating system. A [...] Read more.
Microwave tomography (MWT) based control is a novel idea in industrial heating systems for drying polymer foam. In this work, an X-band MWT module is designed and developed using a fixed antenna array configuration and integrated with the HEPHAISTOS industrial heating system. A decomposition of the time-reversal operator (DORT) algorithm with a proper Green’s function of multilayered media is utilized to localize the moisture location. The derived Green’s function can be applied to the media with low or high contrast layers. It is shown that the time-reversal imaging (TRI) with the proposed Green’s function can be applied to the multilayered media with a moderately rough surface. Moreover, a single frequency TRI is proposed to decrease the measurement time. Numerical results for different moisture scenarios are presented to demonstrate the efficacy of the proposed method. The developed method is then tested on the experimental data for different moisture scenarios from our developed MWT experimental prototype. Image reconstruction results show promising capabilities of the TRI algorithm in estimating the moisture location in the polymer foam. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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16 pages, 5143 KiB  
Article
System Identification of Conveyor Belt Microwave Drying Process of Polymer Foams Using Electrical Capacitance Tomography
by Marzieh Hosseini, Anna Kaasinen, Mahdi Aliyari Shoorehdeli, Guido Link, Timo Lähivaara and Marko Vauhkonen
Sensors 2021, 21(21), 7170; https://0-doi-org.brum.beds.ac.uk/10.3390/s21217170 - 28 Oct 2021
Cited by 6 | Viewed by 2407
Abstract
The microwave drying process has a wide application in industry, including drying polymer foams after the impregnation process for sealings in the construction industry. The objective of the drying process is to reach a certain moisture in the foam by adjusting the power [...] Read more.
The microwave drying process has a wide application in industry, including drying polymer foams after the impregnation process for sealings in the construction industry. The objective of the drying process is to reach a certain moisture in the foam by adjusting the power levels of the microwave sources. A moisture controller can be designed to achieve this goal; however, a process model is required to design model-based controllers. Since complex physics governs the microwave drying process, system identification tools are employed in this paper to exploit the process input and output information and find a simplified yet accurate model of the process. The moisture content of the foam that is the process output is measured using a designed electrical capacitance tomography (ECT) sensor. The ECT sensor estimates the 2D permittivity distribution of moving foams, which correlates with the foam moisture. Experiments are conducted to collect the ECT measurements while giving different inputs to the microwave sources. A state-space model is estimated using one of the collected datasets and is validated using the other datasets. The comparison between the model response and the actual measurements shows that the model is accurate enough to design a controller for the microwave drying process. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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21 pages, 30282 KiB  
Article
An Ultrasound Tomography Method for Monitoring CO2 Capture Process Involving Stirring and CaCO3 Precipitation
by Panagiotis Koulountzios, Soheil Aghajanian, Tomasz Rymarczyk, Tuomas Koiranen and Manuchehr Soleimani
Sensors 2021, 21(21), 6995; https://0-doi-org.brum.beds.ac.uk/10.3390/s21216995 - 21 Oct 2021
Cited by 29 | Viewed by 2505
Abstract
In this work, an ultrasound computed tomography (USCT) system was employed to investigate the fast-kinetic reactive crystallization process of calcium carbonate. USCT measurements and reconstruction provided key insights into the bulk particle distribution inside the stirred tank reactor and could be used to [...] Read more.
In this work, an ultrasound computed tomography (USCT) system was employed to investigate the fast-kinetic reactive crystallization process of calcium carbonate. USCT measurements and reconstruction provided key insights into the bulk particle distribution inside the stirred tank reactor and could be used to estimate the settling rate and settling time of the particles. To establish the utility of the USCT system for dynamical crystallization processes, first, the experimental imaging tasks were carried out with the stirred solid beads, as well as the feeding and stirring of the CaCO3 crystals. The feeding region, the mixing process, and the particles settling time could be detected from USCT data. Reactive crystallization experiments for CO2 capture were then conducted. Moreover, there was further potential for quantitative characterization of the suspension density in this process. USCT-based reconstructions were investigated for several experimental scenarios and operating conditions. This study demonstrates a real-time monitoring and fault detection application of USCT for reactive crystallization processes. As a robust noninvasive and nonintrusive tool, real-time signal analysis and reconstruction can be beneficial in the development of monitoring and control systems with real-world applications for crystallization processes. A diverse range of experimental studies shown here demonstrate the versatility of the USCT system in process application, hoping to unlock the commercial and industrial utility of the USCT devices. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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20 pages, 5186 KiB  
Article
Real-Time Fault Detection and Diagnosis of CaCO3 Reactive Crystallization Process by Electrical Resistance Tomography Measurements
by Soheil Aghajanian, Guruprasad Rao, Vesa Ruuskanen, Radosław Wajman, Lidia Jackowska-Strumillo and Tuomas Koiranen
Sensors 2021, 21(21), 6958; https://0-doi-org.brum.beds.ac.uk/10.3390/s21216958 - 20 Oct 2021
Cited by 4 | Viewed by 2140
Abstract
In the present research work, an electrical resistance tomography (ERT) system is utilized as a means for real-time fault detection and diagnosis (FDD) during a reactive crystallization process. The calcium carbonate crystallization is part of the carbon capture and utilization scheme where process [...] Read more.
In the present research work, an electrical resistance tomography (ERT) system is utilized as a means for real-time fault detection and diagnosis (FDD) during a reactive crystallization process. The calcium carbonate crystallization is part of the carbon capture and utilization scheme where process monitoring and malfunction diagnostics strategies are presented. The graphical logic representation of the fault tree analysis methodology is used to develop the system failure states. The measurement consistency due to the use of a single electrode from a set of ERT electrodes for malfunction identification is experimentally and quantitatively investigated based on the sensor sensitivity and standard deviation criteria. Electrical current measurements are employed to develop a LabVIEW-based process automation program by using the process-specific knowledge and historical process data. Averaged electrical current is correlated to the mechanical failure of the stirrer through standard deviation evaluation, and slopes of the measured data are used to monitor the pump and concentrations status. The performance of the implemented methodology for detecting the induced faults and abnormalities is tested at different operating conditions, and a basic signal-based alarming technique is developed. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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17 pages, 13013 KiB  
Article
Microwave Tomography Using Neural Networks for Its Application in an Industrial Microwave Drying System
by Rahul Yadav, Adel Omrani, Guido Link, Marko Vauhkonen and Timo Lähivaara
Sensors 2021, 21(20), 6919; https://0-doi-org.brum.beds.ac.uk/10.3390/s21206919 - 19 Oct 2021
Cited by 8 | Viewed by 2789
Abstract
The article presents an application of microwave tomography (MWT) in an industrial drying system to develop tomographic-based process control. The imaging modality is applied to estimate moisture distribution in a polymer foam undergoing drying process. Our Leading challenges are fast data acquisition from [...] Read more.
The article presents an application of microwave tomography (MWT) in an industrial drying system to develop tomographic-based process control. The imaging modality is applied to estimate moisture distribution in a polymer foam undergoing drying process. Our Leading challenges are fast data acquisition from the MWT sensors and real-time image reconstruction of the process. Thus, a limited number of sensors are chosen for the MWT and are placed only on top of the polymer foam to enable fast data acquisition. For real-time estimation, we present a neural network-based reconstruction scheme to estimate moisture distribution in a polymer foam. Training data for the neural network is generated using a physics-based electromagnetic scattering model and a parametric model for moisture sample generation. Numerical data for different moisture scenarios are considered to validate and test the performance of the network. Further, the trained network performance is evaluated with data from our developed prototype of the MWT sensor array. The experimental results show that the network has good accuracy and generalization capabilities. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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15 pages, 3368 KiB  
Article
Supporting Visualization Analysis in Industrial Process Tomography by Using Augmented Reality—A Case Study of an Industrial Microwave Drying System
by Yuchong Zhang, Adel Omrani, Rahul Yadav and Morten Fjeld
Sensors 2021, 21(19), 6515; https://0-doi-org.brum.beds.ac.uk/10.3390/s21196515 - 29 Sep 2021
Cited by 11 | Viewed by 2578
Abstract
Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this [...] Read more.
Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this article, we propose a complete data processing and visualizing workflow regarding a specific case—microwave tomography (MWT) controlled industrial microwave drying system. Furthermore, we present the up-to-date augmented reality (AR) technique to support the corresponding data visualization and on-site analysis. As a pioneering study of using AR to benefit IPT systems, the proposed AR module provides straightforward and comprehensible visualizations pertaining to the process data to the related users. Inside the dataflow of the case, a time reversal imaging algorithm, a post-imaging segmentation, and a volumetric visualization module are included. For the time reversal algorithm, we exhaustively introduce each step for MWT image reconstruction and then present the simulated results. For the post-imaging segmentation, an automatic tomographic segmentation algorithm is utilized to reveal the significant information contained in the reconstructed images. For volumetric visualization, the 3D generated information is displayed. Finally, the proposed AR system is integrated with the on-going process data, including reconstructed, segmented, and volumetric images, which are used for facilitating interactive on-site data analysis for domain users. The central part of the AR system is implemented by a mobile app that is currently supported on iOS/Android platforms. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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Review

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33 pages, 3589 KiB  
Review
Control Systems with Tomographic Sensors—A Review
by Jaroslav Hlava and Shereen Abouelazayem
Sensors 2022, 22(8), 2847; https://0-doi-org.brum.beds.ac.uk/10.3390/s22082847 - 07 Apr 2022
Viewed by 1909
Abstract
Industrial process tomography offers two key advantages over conventional sensing systems. Firstly, process tomography systems provide information about 2D or 3D distributions of the variables of interest. Secondly, tomography looks inside the processes without penetrating them physically, i.e., sensing is possible despite harsh [...] Read more.
Industrial process tomography offers two key advantages over conventional sensing systems. Firstly, process tomography systems provide information about 2D or 3D distributions of the variables of interest. Secondly, tomography looks inside the processes without penetrating them physically, i.e., sensing is possible despite harsh process conditions, and the operation of the process is not disturbed by intrusive sensors. These advantages open new perspectives for the field of process control, and the potential of closed-loop control applications is one of the main driving forces behind the development of industrial tomography. Despite these advantages and decades of development, closed-loop control applications of tomography are still not really common. This article provides an overview of the current state-of-the-art in the field of control systems with tomographic sensors. An attempt is made to classify the different control approaches, critically assess their strengths and weak points, and outline which directions may lead to increased future utilization of industrial tomography in the closed-loop feedback control. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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22 pages, 4485 KiB  
Review
A Review on Fast Tomographic Imaging Techniques and Their Potential Application in Industrial Process Control
by Uwe Hampel, Laurent Babout, Robert Banasiak, Eckhard Schleicher, Manuchehr Soleimani, Thomas Wondrak, Marko Vauhkonen, Timo Lähivaara, Chao Tan, Brian Hoyle and Alexander Penn
Sensors 2022, 22(6), 2309; https://0-doi-org.brum.beds.ac.uk/10.3390/s22062309 - 16 Mar 2022
Cited by 17 | Viewed by 3400
Abstract
With the ongoing digitalization of industry, imaging sensors are becoming increasingly important for industrial process control. In addition to direct imaging techniques such as those provided by video or infrared cameras, tomographic sensors are of interest in the process industry where harsh process [...] Read more.
With the ongoing digitalization of industry, imaging sensors are becoming increasingly important for industrial process control. In addition to direct imaging techniques such as those provided by video or infrared cameras, tomographic sensors are of interest in the process industry where harsh process conditions and opaque fluids require non-intrusive and non-optical sensing techniques. Because most tomographic sensors rely on complex and often time-multiplexed excitation and measurement schemes and require computationally intensive image reconstruction, their application in the control of highly dynamic processes is often hindered. This article provides an overview of the current state of the art in fast process tomography and its potential for use in industry. Full article
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
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