Industrial Process Tomography Research Articles

Optimization of Transducer Array for Cross-Sectional Velocity Field Reconstruction in Acoustic Tomography

As a part of industrial process tomography, acoustic tomography (AT) is a promising method for high-quality velocity field measurement, which is widely utilized in the monitoring of multiphase flow, atmospheric environment, and so on. However, subjected to the safety and reliability requirements of furnaces or industrial pipes, the number of installed transducers is restricted, which results in sparse valid data, and, thus, ill-posed and rank-deficient limited-data linear AT. Therefore, special attention should be given to the transducer arrangement in the framework construction module to maximize the reconstruction accuracy. Unlike methods that minimize relative reconstruction error including true value of interesting field, finding an alternative prior knowledge-based predictor that maps the reconstruction error is more practical and preferred. In this work, based on the prior information that the linear independence of vectors incorporates maximum measurement information, a linear independence degree (LID) metric is proposed to optimize the transducer array. It contains no prior information about flow velocity fields, which enables the procedure to be performed in an off-line mode. A covariance matrix adaptation evolution strategy (CMA-ES) algorithm is employed to solve this minimization problem. Proof-of-concept demonstrations, including representative synthetic vortical flow fields with a biased single vortex or with double vortices and experimental data-based velocity field, are performed by comparison with existing representative optimization strategies. Qualitative and quantitative results show the feasibility and robustness of the LID metric in improving imaging accuracy of arbitrary practical velocity fields based on AT. This prior metric is expected to provide guidance for better diagnosis of multiphase flow and optimization of industrial flow process.

Special issue on the 10th world congress on industrial process tomography

Special issue on the 10th world congress on industrial process tomography

Control Systems with Tomographic Sensors-A Review.

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.

Supporting Visualization Analysis in Industrial Process Tomography by Using Augmented Reality-A Case Study of an Industrial Microwave Drying System.

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.

Coplanar electrical/ultrasonic dual-modality tomography for water continuous gas/oil/water three-phase distribution imaging

Multiphase distributions are common in industrial processes, such as the gas/oil/water three-phase flow, where the visualization of three media is of great significance for state monitoring and fault prediction of industrial production processes. Industrial process tomography possesses unique advantages of non-invasive, non-radiation, and low-cost in multiphase distribution imaging, attracting more and more attention. Due to the complexity of the physical parameters of gas/oil/water three media, traditional single-modality tomography technology is usually difficult to reconstruct and distinguish three media simultaneously. To overcome this problem, an electrical/ultrasonic dual-modality tomography method is proposed, where a coplanar dual-modality sensor is designed to obtain electrical and ultrasonic measurement data. To achieve image fusion, the same mesh model is used in electrical resistance tomography (ERT) and ultrasonic transmission tomography (UTT) inverse problems. The logistic regression and two-dimensional wavelet-transform fusion methods are proposed to fuse the ERT and UTT reconstructed images and visualize the gas/oil/water three media. Numerical and experimental tests are conducted, and image reconstruction results show that the proposed coplanar electrical/ultrasonic dual-modality tomography method can simultaneously reconstruct and distinguish three media in water continuous gas/oil/water three-phase distribution. Especially, the proposed logistic regression and two-dimensional wavelet-transform fusion methods can also improve the imaging quality compared with the traditional single-modality and weighted-average fusion methods.

Improved scatter correction model for high attenuation gamma-ray tomography measurements

In this study a state-of-the-art gamma-ray tomography (GRT) unit was used to measure the solids concentration distributions of high density, high attenuation clay/water/sand slurries in a 4 in. (100 mm) diameter recirculating pipe loop. The presence of neighbouring radiation sources on the GRT results in a scattered radiation contribution to the total intensity measured at each detector. The scattered radiation decreases the signal-to-noise ratio of the measured radiation intensity and introduces error in the measured tomography data and the reconstructed tomograms (Maad et al 2008 Meas. Sci. Technol. 19 6). Because of the high attenuation of the materials being measured, the scatter contribution was a significant fraction of the total radiation measured at each detector. To correct for the scattered radiation contribution in the measurements, a test campaign was undertaken to characterize and model the scattering behaviour of the GRT at the Saskatchewan Research Council. The scattered radiation was measured experimentally from empty pipe, water filled pipe and a number of flowing clay/water/sand slurries at densities ranging from 1206 kg m−3 to 1580 kg m−3. A semi-empirical scatter correction model has been developed which allows the scattered contribution at each detector to be calculated iteratively based on the measured uncorrected attenuated radiation intensity. This article is an extension of the work presented at the 9th World Congress for Industrial Process Tomography (Spelay et al 2018 Proc. 9th World Congress Industrial Process Tomography p 14).

Development of an automated source port in IoT for application in industrial process tomography

Computed tomography technology uses an electromagnetic radiation source or particulate radiation source, to analyze / study different samples that can range from living organisms to the most diverse objects (rocks, phantoms, etc.). The use of the radioactive materials may cause harm to the operator if he is exposed to the source of radiation, so aiming at the safety of the operator, the objective of this work is to develop an Internet of Things automation system for the opening of the Industrial Process Tomography source port for industrial tomography applications. Thus, this system can drive the stepper motors through this platform can be opened at a safe distance to the operator, avoiding the operator to take radiation dose to perform this operation. For the IPT project, five source ports were made so that each was positioned diametrically opposite each array of detectors. In this project we used 192Ir sources that have activity of 18,500 MBq and that were produced in the reactor IEA-R1, from the neutron bombardment of the pellet containing stable isotope 191Ir. The main characteristics of 192Ir are: half-life of 74.2 days; radiation energy from 0.13 to 0.65 MeV. For the safety of the operator during the opening of the sources, an automated opening system with IoT that can be activated with software installed on the tomography or by a smartphone application by the MQTT protocol, which makes it possible to be monitored in real time at long distance showing the opening and closing status of each source port.

Multifrequency Ultrasonic Tomography for Oil–Gas–Water Three-Phase Distribution Imaging Using Transmissive Attenuation Spectrum

Industrial process tomography (PT) possesses unique advantages in multiphase distribution imaging. Oil–gas–water three-phase distribution has coexisting high-impedance contrast and low-impedance contrast medium, possessing a challenge to traditional PT sensing technique. An original concept of multifrequency ultrasonic tomography (MFUT) is proposed, which reconstructs oil–gas–water three-phase distribution with the single modality of UT. Operated in the transmissive ultrasonic tomography (UT) framework, the proposed MFUT quantifies attenuation spectrum response under frequency-modulated chirp signal excitation and extracts fluid absorption coefficient through partial differential modeling of frequency attenuation response. Artifacts introduced by lateral scattering is further alleviated through beam angle modification during assembling of the sensitivity matrix. Thus, the MFUT method is theoretically less sensitive to nonlinear error introduced by the reflection/refraction/scattering effect. In numerical and experimental results, quantitative attenuation characterization offers MFUT the capability of reconstructing gas–water/oil–water/oil–gas–water multiphase distribution with higher accuracy, boundary preservation, and image purity. Synthetic modeling of spectral attenuation also outperforms the single-frequency image fusion and frequency difference reconstruction, from which the MFUT is proven feasible to investigate a multiphase system.

Absolute reconstruction of Ultrasonic Tomography for oil-water biphasic medium imaging using modified ray-tracing technique

Oil-water biphasic medium widely existed in mining and transportation process of petroleum industry, where visualized measurement processes vital importance in production increase, state monitoring and fault prognosis. Ultrasonic Tomography (UT) is a non-invasive and non-radioactive sensing modality in industrial Process Tomography, which is demonstrated as a competitive monitoring technique with great potential. However, facing the refraction effect of Ultrasound wave at oil-water interfaces, the accuracy of reconstruction algorithm is with large error and serious artifacts. To address the issue, a modified ray-tracing image reconstruction algorithm is proposed. The amplitude attenuation during ultrasound propagation in nonhomogeneous medium is quantitatively modeled to form absolute UT model. With ray tracing strategy applied and improved, the nonlinear refraction effect is characterized in the form of iterative update of sensitivity matrix, followed by which the sound speed mapping transfers reconstructed attenuation images to sound speed distribution for ray tracing computation. Numerical tests indicate that the proposed method significantly improves reconstruction accuracy through projection-based, regularization-based and algebraic-based inverse algorithms, which demonstrate its benefits in conducting oil-water biphasic medium imaging.

Editorial for selected papers from the 9th World Congress on Industrial Process Tomography: Guest Editor Chao Tan

Editorial for selected papers from the 9th World Congress on Industrial Process Tomography: Guest Editor Chao Tan

Image Reconstruction Algorithm Based on PSO-Tuned Fuzzy Inference System for Electrical Capacitance Tomography

Electrical Capacitance Tomography (ECT) is a well-established industrial process tomography technique. Image reconstruction for the ECT is a nonlinear problem, and the inverse problem is usually ill-posed and ill-conditioned. Hence, the solutions for the ECT are not unique and highly sensitive to the measurement noise. In this paper, a novel tuned fuzzy algorithm is proposed for reconstructing accurate images to monitor the distribution of the multi-phase flow in the industrial process. The proposed algorithm utilizes a Tuned Fuzzy Inference System (TFIS) to overcome the nonlinear characteristics of the ECT system. The optimal parameters of the fuzzy membership functions are obtained using the Particle Swarm Optimization (PSO) technique. In the past few decades, the naturally inspired intelligent swarm algorithms got more attention due to their wide spectrum of research for real-world complex problems optimization. The proposed PSO-tuned fuzzy algorithm is fast since it does not require solving the forward problem to update the sensitivity matrix. Comparing the results with traditional reconstruction algorithms, the proposed algorithm performs better in visual effects and imaging quality, since the image edges and details are better preserved.

Nonlinear Ultrasonic Transmissive Tomography for Low-Contrast Biphasic Medium Imaging Using Continuous-Wave Excitation

Industrial process tomography possesses unique advantages in biphasic medium measurement and has received broad attention in the past decades. Aiming at the widely existing low-contrast biphasic medium, this article proposes a nonlinear ultrasonic transmissive tomography (UTT) approach using continuous-wave excitation. Considering the refraction effect at the biphasic interface, the reconstruction method with nonlinear forward problem and the prototype-based resolution enhancement algorithm is proposed with higher accuracy, resolution, and speed. The UTT system is improved with a high-voltage excitation module and fan-beam transducer array to evaluate the proposed method, where the performance is qualitatively and quantitatively compared with the state-of-the-art reconstruction algorithms and measurement techniques from different perspectives. The results show that the reconstruction performance is significantly improved where the size, shape, and position of the dispersed medium can be accurately discriminated. Accordingly, the ultrasonic tomography with continuous-wave excitation is proved to be feasible and efficient in the visualized measurement of low-contrast biphasic medium.

A Dual-Modality Integrated Sensor for Electrical Capacitance Tomography and Electromagnetic Tomography

Process tomography techniques play an important role in visualizing and monitoring industrial processes, which help to produce high quality product without affecting the work flow in plants. The industrial process tomography techniques, i.e. , electrical tomography and computerized tomography, have been widely applied. Such tomographic tools can be used to investigate various types of multi-phase flows, in which the components may differentiate in density, conductivity, and permittivity. In a gas-liquid-solid flow, however, it is usually difficult for the existing tomographic tools to visualize the distributions of all three phases. In addition, it is necessary to assume some simplifications, i.e. , by viewing two disperse phases as one unified phase. The objective of this research is to provide a dual-modality imaging tool by combining electrical capacitance tomography (ECT) and electromagnetic tomography (EMT). First, an integrated dual-modality sensor was designed and implemented on the same cross-section of the process vessel. Subsequently, dual-modality tomographic measurements were collected by a custom-built multi-channel impedance measurement system. The performance of the dual-modality sensor was verified by numerical simulations and experimental tests, showing that it can produce reliable ECT and EMT measurements at a satisfying signal-to-noise ratio. The complementary tomographic images can be obtained from ECT and EMT, and the distributions of two disperse phases, i.e. , gas and solid phases, can be observed. The preliminary image fusion results were also given by combining the information from both the ECT and EMT images.

Impedance matched electrical capacitance tomography system: front-end design and system analysis

Electrical capacitance tomography (ECT) is a well-established technique for process monitoring, which enables the visualization of spatial material distributions within a region of interest, e.g. a pipeline. Switched capacitor (SC) circuits or continuous displacement current measurements are used to measure the coupling capacitances within the ECT sensor. In order to measure the coupling capacitances with high accuracy, the circuit concepts make use of fast excitation signals, e.g. fast transients in SC circuits or high excitation frequency signals in continuous displacement current measurements. For industrial process tomography in harsh environments a spatial separation between the sensor and the front-end circuitry is favorable. Consequently, the measurement circuitry and the sensor are connected by means of coaxial cables. For high excitation frequencies, transmission line effects like standing waves, reflections, or impedance transformation effects appear, leading to undefined signal conditions in the measurement system. It can be shown that the undefined signal propagation can lead to significant measurement errors. In this paper we present an impedance matched front-end circuitry, i.e. the source impedance of the excitation source and the input impedance of the measurement circuitry are matched to the wave impedance of the transmission lines. Due to the matching the signal propagation becomes defined, allowing the use of arbitrary cable lengths and excitation signals. We present the design of an impedance matched front-end for ECT and study the behavior of the excitation system and the measurement system. Comparative measurements from a demonstrator are presented. Finally we study the measurement error of the system and show the validity of the impedance matched system approach.

The use of elastic net and neural networks in industrial process tomography

The use of elastic net and neural networks in industrial process tomography

Enhancing Resolution of Electrical Capacitive Sensors for Multiphase Flows by Fine-Stepped Electronic Scanning of Synthetic Electrodes

Electrical capacitance tomography (ECT) exhibits several attractive features that are important for industrial process tomography applications. These features include low cost, high speed, and nonintrusive nature. However, due to its soft-field character, a relatively low image resolution is an outstanding challenge for ECT. While many efforts have been made to tackle this challenge by improvements in image reconstruction algorithms, relatively less has been done to enhance the basic ECT hardware sensor configuration and data acquisition process. In this paper, a new measurement acquisition strategy is introduced to increase image resolution when using adaptive ECT (AECT). The proposed strategy is based on the manipulation of synthetic electrodes plates (“metaplates”) formed by a set of combined smaller physical electrodes (segments). The synthetic electrodes are sequentially activated with partial overlap of constituent segments to provide a fine-stepped axial and/or azimuthal electronic scan along the entire sensor. Consequently, an increased number of independent capacitance measurements are made available. Reconstruction results using the proposed measurement acquisition strategy (AECT) are shown to illustrate the enhanced resolution and stability in the imaging of objects compared to conventional ECT sensors.

Special Section on the 8th World Congress on Industrial Process Tomography (WCIPT8)

Special Section on the 8th World Congress on Industrial Process Tomography (WCIPT8)

Performance evaluation of process tomography system for cold flow catalytic column

In a typical catalytic trickle bed type of process reactor, capturing representations of steady-state flow features as well as situations like channelling or bypassing is a challenging task. Transmission-type industrial process tomography (PT) based on gamma radiation can be employed in many chemical and process industries as a tool for localizing the problem area for quick and economical troubleshooting. Industrial PT technology often makes use of either penetrating radiation like radioisotope based gamma rays, X-rays, microwaves or ultrasonic waves. We have developed a new gamma-ray transmission tomography system in collaboration with the Indian Oil Corporation Ltd. (IOCL R&D Unit, Faridabad, India). The system makes use of thirty two scintillator based gamma-ray detectors in addition to a host of other sub-systems. This paper evaluates the performance of the system considering systematic and automated data acquisition, capabilities of the reconstruction software as well as experimental verification using actual flow dynamics in the process column to map the steady state three phase liquid gas flow distribution across a plane in the presence of catalyst.

Ring artifact correction in gamma-ray process tomography imaging

Ring artifacts have been studied for X–ray based Computed Tomography (CT) systems but not on γ-ray based in-situ applications. This paper discusses application of recently proposed automatic ring artifact reduction method (Yoon et al., 2016) on previously obtained experimental projection data from a γ-ray based Industrial Process Tomography (IPT) system for a prototype catalytic column. Studies include qualitative and quantitative evaluation of the method. It is observed that ring artifacts are suppressed without loss of significant information in γ-ray PT images.

Super-sensing through industrial process tomography.

In this introduction article, we present a brief overview of industrial process tomography. This will start by linking between the concept of industrial process tomography and super-sensing. This will follow with a brief introduction to various process tomography systems and in particular electrical tomography methods. This article is part of the themed issue 'Supersensing through industrial process tomography'.