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Multistatic imaging systems are commonly used in radar systems and microwave imaging. In these systems, many antennas are arranged three-dimensionally and connected to RF switches. The length of each transmitter (Tx) and receiver (Rx) channel differs slightly, causing artifacts in high-resolution image reconstruction. This study presents a novel method for the phase calibration of multistatic systems. This method does not require system reconstruction and can automatically perform phase calibration in a short time. This method is expected to facilitate an accurate phase measurement in multistatic systems. The approach involves phase calibration by analyzing the reflection coefficients of antenna elements in the time domain. Imaging experiments were performed on a multistatic imaging system using this calibration method, and the position and shape of a metal rod with a diameter one-fourth of a wavelength were reconstructed by simple back-projection with an accuracy beyond the diffraction limit. [ABSTRACT FROM AUTHOR]

This contribution focuses on the detection of tracer particles within non-homogeneous bulk media, aiming to enhance insights into particulate systems. Polarimetric radar measurements are employed, utilizing cross-polarizing channels in order to mitigate interference from bulk media reflections. To distinguish the tracer particle in the measurements, a resonant cross-polarizing structure is constructed, facilitating the isolation of frequency signatures from the surrounding bulk clutter. In addition to characterizing the bulk and tracer components, this study provides a detailed presentation and discussion of the measurement setup, along with the employed signal processing methods. The effectiveness of the proposed methods is demonstrated through comprehensive measurements, where a tracer particle is systematically positioned at various locations. The results affirm the feasibility and efficacy of the approach, highlighting its applicability for enhanced dynamic monitoring in particulate systems within industrial processes. [ABSTRACT FROM AUTHOR]

Automatic human behavior monitoring is essential for surveillance cameras in public and private environments. Violent action is challenging because the available violence dataset is insufficient for deep network training. Also, human behavior contains high intra-class variations and inter-class similarities that make violence detection very challenging. In this paper, we proposed an unsupervised Spatial–Temporal Action Translation (STAT) network to accurately distinguish between behaviors and overcome the insufficient violence data problem. Our framework comprises a person detector, motion feature extractor, STAT network, and output interpretation. The proposed framework performed well in different environments because it detects objects in each frame and removes irrelevant background information. As violent motion pattern changes rapidly with high velocity, temporal features play a crucial role in the recognition, and we use it as the input of the STAT network. The STAT network has been trained with normal behavior data, translating normal motion to the spatial frame. Due to the complicated actions in violent behavior, the STAT network cannot reconstruct the violent frame correctly, and therefore, actions will be categorized by comparing the actual and reconstructed frames and measuring the reconstruction error in the output interpretation part of the framework. The proposed unsupervised framework achieved comparable accuracy and outperformed previous works in terms of generality. [ABSTRACT FROM AUTHOR]

Particle tracking in densely packed granular assemblies is of great interest in mechanical process engineering. In this contribution, a radar-based system for particle localization as an initial step towards tracking is presented. This system comprises six transmitting and receiving antennas forming a "multiple-input multiple-output" setup positioned around a cuboidal reactor. The reactor is a standard batch grate system, which contains stationary spherical polyoxymethylene particles with a 10 mm diameter and a spherical steel tracer particle with a 20 mm diameter. The tracer is positioned at various locations at an optically transparent reactor wall. Electromagnetic waves must pass through the remaining three reactor walls to detect the tracer particle. Operating in the Frequency Modulated Continuous Wave mode within a 1.5 to 8.5 GHz frequency range, we compared radar-detected tracer positions with those from camera images. The results demonstrate a vertical localization accuracy with a standard deviation of σ v e r t = 0.86 cm and a horizontal position accuracy with σ h o r = 0.17 cm. This study not only presents the achievements of radar-based particle localization but also delves into the potential and challenges of applying this technology to a specific measurement scenario within mechanical process engineering. [ABSTRACT FROM AUTHOR]

Microwave imaging has been recently proposed as alternative technology for in-line inspection of packaged products in the food industry, thanks to its non-invasiveness and the low-cost of the equipment. In this framework, simple and effective detection/imaging strategies, able to reveal the presence of foreign bodies that may have contaminated the product during the packaging stage, are needed to allow real-time and reliable detection, thus avoiding delays along the production line and limiting occurrence of false detections (either negative or positive). In this work, a novel detection/imaging approach meeting these requirements is presented. The approach performs the detection/imaging of the contaminant by exploiting the symmetries usually characterizing the food items. Such symmetries are broken by the presence of foreign bodies, thereby determining a differential signal that can be processed to reveal their presence. In so doing, the approach does not require the prior measurement of a reference, defect-free, item. With respect to the quite common case of homogeneous food packaged in circular plastic/glass jars, numerical analyses are provided to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Industrial ultrasonic tomography (UT) possesses unique benefits in nonintrusive detection of cross-sectional medium and has received broad attention in decades. Aiming at the complex bubble imaging, the conventional independent-transducer-based UT has low spatial resolution due to wide projection path and low projection number. Based on ultrasound phase array (UPA) transducers, this article proposes a sequential dynamic aperture focusing strategy for transmissive ultrasonic phase array tomography (UPAT). The emitting aperture focuses the ultrasound beam on a close distance to generate a high intensity and wide-angle acoustic field that covers multiple receivers in single excitation and further induces high amount of multiangle narrow projections, through which the measurement speed and imaging performance are substantially improved. Beyond numerical analysis on image accuracy and noise robustness, an experimental UPAT system with independent T/R channels is developed to evaluate the proposed method, where the improvement on imaging accuracy and speed are testified through qualitatively and quantitatively comparison with the state-of-art UT and the beam scanning UPAT techniques. The UPAT-focus strategy is proved to be advanced and feasible in imaging complex medium distribution. [ABSTRACT FROM AUTHOR]

Microwave tomography (MWT)-based control is a novel idea in industrial heating systems that demands fast data acquisition (DAQ) and real-time imaging algorithms. Uniform diffraction tomography (UDT) is one such technique that can provide real-time imaging. However, its single-input single-output data-based inverse scattering formulation can lead to time-consuming DAQ. In this article, a multistatic uniform diffraction tomography (MUDT) imaging algorithm is proposed for a fixed array MWT system. The MWT system is integrated into the industrial heating unit HEPHAISTOS to estimate the moisture distribution in a polymer foam. In addition, a technique is presented to retrieve the electrical properties of the targets using reconstructed information from MUDT and by investigating the singular values of multistatic scattering data. Through numerical and experimental data for the considered moisture scenarios, the MUDT approach is tested, and its comparison with the UDT approach is shown. Reconstructed results show that in comparison to UDT, the MUDT approach: 1) eliminates the need for mechanical scanning; 2) provides aliasing-free images by following Nyquist sampling criteria; and 3) can resolve multiple targets in the imaging media with significant improvement in the spatial resolution that further augments in the correct retrieval of the dielectric constants of the target. [ABSTRACT FROM AUTHOR]

This work presents the design and numerical assessment of a novel microwave imaging (MWI) system, capable of providing a full 3-D image of food/beverage products content in order to disclose the possible presence of physical contaminants, such as plastic fragments. The system here presented exploits the dielectric contrast between the food content and possible intrusions at microwave frequencies; it is based on an antenna array architecture inspecting the items in motion along a conveyor belt without interrupting the production process. The inversion problem is solved by means of linearization, assuming the viability of the Born approximation thanks to the localized intrusions, and regularization, based on the singular value decomposition of the discretized scattering operator. Furthermore, an algorithm, to balance the illumination of the considered scenario due to the nonuniform radiation of the employed antennas, is presented to enhance imaging. The system is first assessed considering an ideal case and then extended to a more realistic approach, for two different kinds of food products, with completely different dielectric properties and considering the performance of existing instrumentation for the purpose. The obtained results lay the foundations for the realization of an actual prototype. [ABSTRACT FROM AUTHOR]

When using the statistical inversion framework in microwave tomography (MWT), generally, the real and imaginary parts of the unknown dielectric constant are treated as uncorrelated and independent random variables. Thereby, in the maximum a posteriori estimates, the two recovered variables may show different structural changes inside the imaging domain. In this work, a correlated sample-based prior model is presented to incorporate the correlation of the real part with the imaginary part of the dielectric constant in the statistical inversion framework. The method is used to estimate the inhomogeneous moisture distribution (as dielectric constant) in a large cross section of polymer foam. The targeted application of MWT is in industrial drying to derive intelligent control methods based on tomographic inputs for selective heating purposes. One of the features of the proposed method shows how to integrate lab-based dielectric characterization, often available in MWT application cases, in the prior modeling. The method is validated with numerical and experimental MWT data for the considered moisture distributions. [ABSTRACT FROM AUTHOR]

Tomographic imaging of a dynamic scene is addressed for the first time in this article. The effect of dynamics of the imaged object is studied for some deformation scenarios using the conventional truncated singular value decomposition (TSVD) method, which is applied in numerous static inverse scattering problems, together with variational data assimilation (DA) methods including three‐dimensional variational (3D‐VAR) and four‐dimensional variational (4D‐VAR) techniques. Results show that the DA frameworks outperform the TSVD method, which assumes the scene static, especially for objects with higher contrast. Also, it is seen that applying the conventional TSVD method makes the image blurred and distorts it for high‐speed dynamic changes, particularly when the contrast is increased. However, the proposed DA methods seem to be robust against large deformation distortions and can still detect the object. [ABSTRACT FROM AUTHOR]

With the recent promotion of clinical applications of electrical impedance tomography (EIT) technology, more scholars have begun studying EIT technology. Although the principle of EIT technology seems simple, EIT image reconstruction is a non-linear and ill-posed problem that is quite difficult to solve because of its soft field characteristics and the inhomogeneous distribution of its sensitive field. What's more, the EIT reconstruction algorithm requires further improvements in robustness, clarity, etc. The image-reconstruction algorithm and image quality are among the key challenges in the application of EIT technology; thus, more research is urgently needed to improve the performance of EIT technology and use it to solve a larger variety of clinical problems. In this paper, we pay special attention to the latest advances in the study of EIT image-reconstruction algorithms to provide a convenient reference for EIT beginners and researchers who are newly involved in research on EIT image reconstruction. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Particle drying in fluidized beds is a common and important process in food and pharmaceutical industry. However, the fluidization characteristic is complex due to the moisture content change in the process and it is a challenge to monitor the flow characteristics by conventional measurement approach, likes pressure and thermal probes. In this research, process tomography including capacitance and microwave tomographic systems are used to investigate the flow characteristics in a fluidized bed dryer with high-moisture content particles. Static tests were firstly carried out to investigate the image characteristics based on microwave tomography (MWT) and electrical capacitance tomography (ECT). The imaging ability was compared between MWT and ECT. In the dynamic tests, the drying process for particles with high-moisture content was monitored on-line by MWT and ECT separately. The static test results show that the high calibration for ECT is critical and particles with low moisture content should be used for high calibration of an ECT system to achieve high quality images for the dynamic tests. For the high calibration of ECT, there is an upper limit for the moisture content. With a fixed calibration background, the moisture content of particles should not exceed this upper limit value. MWT basically has no limitation on the moisture content both for high calibration and measurement. Dynamic test results illustrate that MWT is a good option to monitor high-moisture content particles drying in a fluidized bed and it is possible to combine ECT together to identify the gas–solids flow regime transit and to determine the moisture content by MWT in a fluidized bed drying process. [ABSTRACT FROM AUTHOR]

In industrial environments, having instrumentation able to attain fast, accurate, and autonomous measurements is pivotal to understanding the dynamics of liquid and particles during transport. Ideally, these instruments, consisting of either probes or sensors, should be robust, fast, and unintrusive, i.e., not cause interference on the very flows being monitored, and require minimal maintenance. Beyond monitoring, the process knowledge gained through real time inspection allows teams to make informed technical decisions based on particle behavior, i.e., settling of particles causing pipe wear and clustering or blockages that can damage the unit or cause shutdowns, both of which with economical drawbacks. The purpose of this review is to examine experimental measurement techniques used to characterize physical properties and operational parameters of solid-liquid slurry flows, focusing on non-ionizing radiation methods. With this text the intent is not to provide an exhaustive examination of each individual technique but rather an overview on the most pertinent types of instrumentation, which will be presented, in addition to application examples from the literature, while directing the reader for pertinent seminal and review papers for a more in-depth analysis. [ABSTRACT FROM AUTHOR]

Electrical capacitance tomography (ECT) provides an effective way for solving the problem of two-phase flow measurement. However, there is a problem of underdetermination, which leads to the low accuracy of ECT image reconstruction. In this article, a new ECT image reconstruction method based on multi-exponential feature extraction is proposed to improve the accuracy of ECT image reconstruction. First, it can be observed that the grayscale of two-dimensional images is a typical Dirac pulse sequence, and the grayscale vector can be modeled as a discrete finite rate of innovation (FRI) signal. Then, the FRI sampling system is used to extract the feature information after filtering by exponential reproducing kernel. Finally, by means of zero filling and random recombination, a comprehensive observation equation can be constructed by using feature information. The original image signal is recovered by solving a L0 norm optimization problem. Simulation results have shown that the images reconstructed by the method in this article outperform those reconstructed by existing algorithms. [ABSTRACT FROM AUTHOR]

The impedance flow sensors have usually been considered as the competitive components in the multi-flow measurement, primarily due to their advantages of fast response, high dynamic range and sensitivity, non-invasive and/or non-intrusive measurements. In this review, the impedance sensors have been categorized into two categories, i.e., the probes for local/average parameter measurement and sensor arrays for distributed parameter measurement. Maxwell’s equations and boundary conditions have been referred as a starting point to understand the measuring principle of impedance sensors, from which the sensitivity distribution can be attained. The sensitivity distribution can be utilized to characterize the sensor and employed as an objective function in optimizing the sensor geometry. The EMA models usually offer a way to relate the impedance measurements to individual phase fraction, which have been critically reviewed. In addition, the application range, spatial and temporal resolutions, advantages and disadvantages of the sensor arrays, i.e., the wire mesh sensor, field focusing sensor, electrical resistance and capacitance tomography sensors have also been provided. Finally, the future trends of impedance sensor development have been briefly discussed. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polymers (CFRPs) are composite materials in which carbon provides strength and stiffness, whereas polymers provide cohesiveness and toughness. The electrical impedance of CFRP laminates is changed due to different kinds of damages. Electrical impedance tomography (EIT) has significant advantages such as non-intrusion, portability, low cost, and quick response and has widely been used as a nondestructive testing method. Therefore, EIT has great potential in structural health monitoring of CFRPs. Regularization can solve the ill-posed inverse problem of EIT. However, conventional regularization algorithms have their own limitations, such as over-smoothness of reconstructed edges and unstable solution caused by measurement noise. In addition, the anisotropic property of CFRPs also affects the image quality based on traditional methods. In this paper, the sorted L1-norm regularization is proposed. It promotes grouping highly correlated variables while encouraging sparsity by using more effective penalty terms. The sharp edges between different materials can be obtained, and the obtained solution is more stable. The image quality of different objects, especially the image quality of multi-targets, can be significantly improved with this new method. In addition, the sorted L1 norm can generate adaptive regularization parameters without empirical selection. The new regularization problem is solved by the alternating direction method of multipliers. Both experimental and simulation results demonstrate that the sorted L1 norm improves the quality of reconstructed images under various noise levels. The proposed method is comprehensively evaluated with three image quality criteria by numerical simulation quantitatively. [ABSTRACT FROM AUTHOR]

Electrical impedance tomography (EIT) is a nondestructive imaging technique for estimating the electrical impedance distribution within a conductive process. EIT is employed in many fields, including medical, geology, and industrial. The pressure sensor design is one of the most recent applications of this method. In this application, a thin and flexible conductor uses as the pressure sensor to apply physical pressure on a specific region and cause local variations in the electrical impedance of that region. We present the principles of designing and implementing a multifrequency EIT system for pressure sensing and imaging. Considering this, the theoretical topics and the hardware components of an EIT system are described. Subsequently, with the aim of examining the designed system, the conductive fabric was employed as the pressure sensor. In numerous experiments, the reconstructed electrical impedance images of the applied pressure demonstrated that there is a relatively linear relation between the pressure and the impedance variations at each frequency. The experimental results reveal that the designed system successfully detects the pressure area and determines its magnitude in the applied pressure region. [ABSTRACT FROM AUTHOR]