Planar Sensor Array Research Articles

Optimization of an electric field calibration chamber for high-precision measurements for imaging applications

The DEVCOM Army Research Laboratory (ARL) electric field “cage” generates a uniform E-field over a large working volume, along the lines of the IEEE-Std 1308–1994. The end plates are spaced farther apart than the IEEE standard field source, and the fringing fields are controlled by the addition of “guard tubes.” This chamber was originally constructed to calibrate and characterize electric field sensors, and it has been redesigned to support quasi-static electric field imaging applications. A planar array of sensors forms a grounded end plate of the cage and is used to measure distortions in the uniform field generated by the cage due to objects placed inside. However, the array itself distorts this field and introduces significant errors. Several modifications were made to mitigate the errors, including adding nonfunctional “dummy” elements, a border around the array, and a back plane behind it. The parameter space for these additions is very large, since the number of nonfunctional elements, the width of the border, and the size and placement of the back plane can all be tuned independently. Extensive computer modeling was used to explore this parameter space and test thousands of possible designs. The design chosen yields modeled absolute field errors over a 1.2-m × 0.8-m sensing plane that are less than 0.5 % for a uniform ambient field (empty cage), and less than 1 % for a sphere with a 0.5-m radius in an ambient field.

An object detection system using array planar capacitive sensors

This paper presents a target detection system using array-based planar capacitive sensors, demonstrating excellent detection performance in gesture recognition. The system achieves gesture target classification by collecting the capacitance values of the planar capacitive sensor array and optimizing the BP neural network through a genetic algorithm for model training. Additionally, the system employs visual detection for gesture targets, using transfer learning with the MobileNet V2 network in the Keras framework to achieve gesture target classification. The system utilizes a data fusion mechanism to merge visual recognition and planar capacitive sensor array recognition for decision-making. Experimental results demonstrate that the target detection system exhibits outstanding detection performance in gesture recognition, with an average accuracy of up to 98.92%.

Deep Learning-Based Angular Resolution Improvement in Planar Sensor Array

Deep Learning-Based Angular Resolution Improvement in Planar Sensor Array

Feature-Enhanced Beamforming for Underwater 3-D Acoustic Imaging

A planar array of sensors and beamforming algorithms are required for underwater 3-D acoustic imaging system. However, due to limited aperture and sensor numbers, conventional beamforming usually results in wide mainlobes and high sidelobes, which severely degrade the image quality. To date, using unconventional beamforming algorithms to improve the imaging quality of underwater 3-D acoustic systems have been rarely investigated. This article proposes a feature-enhanced beamforming (FEBF) algorithm, with the goal of improving the imaging quality by utilizing more appropriate prior knowledge that objects in the angular domain in underwater 3-D imaging scenes are generally sparse but locally dense. The proposed FEBF employs the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$l_{1}$</tex-math></inline-formula> -total variation (L1-TV) mixed norm regularization. The penalized beamforming optimization is reformed into convex programming with linear constraints and solved by alternating direction method of multipliers. The results of simulation and experiment demonstrate that the proposed FEBF has the ability to effectively improve the image quality when compared with the other existing beamforming methods. This study also proposes a 2-D fast Fourier transform based acceleration strategy, which effectively reduces the computational time of the FEBF algorithm by about 4.3 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> times for forming 200 × 200 beams. The accelerated version of the proposed FEBF method is considered to have potential for real-time imaging systems.

Intracranial Hemorrhage Detection by Open MIT Sensor Array

Magnetic induction tomography (MIT) is a promising technology in medical imaging due to its nonradioactive, noninvasive, and noncontact properties. To realize the local detection of intracranial hemorrhage with small volume, an open planar MIT sensor array with gradiometers is proposed. With the 3-D head model, the phase response of the hemorrhages in different volumes under this sensor structure was investigated and compared with the sensor structure with Bx sensors. The evaluation indexes: intensity of hemorrhage signals <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$A_{\mathrm {H}}$ </tex-math></inline-formula> and useful signal to background signal ratio(UBR) were introduced for quantitatively compare the performance of the two sensor arrays in hemorrhage detection. For the 2 mL hemorrhage, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$A_{\mathrm {H}}$ </tex-math></inline-formula> and UBR under the planar array with Bx sensors are only 15.33% and 16.67% of those under the planar array with gradiometers, respectively. The results indicate that the planar array with gradiometers can effectively enhance the hemorrhage signals and reduce the effect of normal head tissues, which will facilitate the accurate reconstruction of hemorrhage. Then, the capability of the open planar sensor array with gradiometers in hemorrhage reconstruction was investigated by the time difference MIT, frequency difference MIT, and multifrequency difference MIT method. In the simulation and experimental results, the spatial resolution of the intracranial hemorrhage imaging could, respectively, reach 2 and 6.4 mL under the designed MIT sensor array. This study provides a portable solution for local detection of intracranial hemorrhage with small volume, which will promote the practical application of MIT.

A 4 × 4 Array of Complementary Split-Ring Resonators for Label-Free Dielectric Spectroscopy

In this study, complementary split-ring resonator (CSRR) metamaterial structures are proposed for label-free dielectric spectroscopy of liquids in microplates. This novel combination of an array of sensors and microplates is readily scalable and thus offers a great potential for non-invasive, rapid, and label-free dielectric spectroscopy of liquids in large microplate arrays. The proposed array of sensors on a printed circuit board consists of a microstrip line coupled to four CSRRs in cascade with resonant frequencies ranging from 7 to 10 GHz, spaced around 1 GHz. The microwells were manufactured and bonded to the CSRR using polydimethylsiloxane, whose resonant frequency is dependent on a complex relative permittivity of the liquid loaded in the microwell. The individual microstrip lines with CSRRs were interconnected to the measurement equipment using two electronically controllable microwave switches, which enables microwave measurements of the 4 × 4 CSRR array using only a two-port measurement system. The 4 × 4 microwell sensor arrays were calibrated and evaluated using water-ethanol mixtures with different ethanol concentrations. The proposed measurement setup offers comparable results to ones obtained using a dielectric probe, confirming the potential of the planar sensor array for large-scale microplate experiments.

Planar Near-Field Electric Field Sensor Array Applications Facilitated by Neural Networks

Electrical capacitance tomography is employed for various process tomography applications, typically with circular imaging regions (e.g., to estimate fluid levels in plastic pipes). Typical state-of-the-art implementations focus on circular or cylindrical sensor arrays. In contrast, this research explores using a planar 2D array of electric-field sensors to image volumes composed of various dielectric materials. The array is designed to be used with very-low-frequency electric fields, which are desirable due to their ability to differentiate between various non-conducting objects. D-dot sensors (i.e., charge induction sensors) are used as the electric-field sensing element. In this research, imaging regions of interest are modeled as a composition of (25 cm) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> voxels of dielectric material with randomized relative permittivities. Neural networks are utilized as the inversion algorithm to map measured E-field distortions to the voxels’ relative permittivities. Three applications are explored in a simulated environment: 1) predicting relative permittivities of the entire (pseudo-3D) imaging region from one measurement of electric-field distortions (modeled in free space), 2) imaging regions arbitrarily large (in two dimensions) using the planar array as an imaging kernel, and 3) repeating application (1) in a model of a practical, real-world imaging scenario both with and without interfering material. Application (3) is performed with a real-world experimental setup using a room-sized “E-field Cage” meant to generate a uniform electric field. This work showcases a new electric-field imaging modality using a planar 2D D-dot sensor array paired with a DNN-based inversion algorithm.

Study of signal reconstruction in a planar sensor array MEG with optically pumped magnetometers

Study of signal reconstruction in a planar sensor array MEG with optically pumped magnetometers

Study of signal reconstruction in a planar sensor array MEG with optically pumped magnetometers

Study of signal reconstruction in a planar sensor array MEG with optically pumped magnetometers

A versatile 4D capacitive imaging array: a touchless skin and an obstacle-avoidance sensor for robotic applications

There are growing interests in the use of robots in collaborative environments with humans or other intelligent machines. Sensing the environment for which the robot is operating can be done in many ways, generally guided by skin-like sensors. Some of the skins are inspired by natural sensing in humans or other species. As humans, we use many of our senses, such as version, hearing, smell, and touch, to move around by avoiding colliding with other humans or objects. Different from humans, many other mammals also use whiskers as an additional sensor to help navigate around. In this paper, we demonstrate a touchless capacitive imaging-based sensor in the situation where the obstacles are in close vicinity to the robot. The proposed imaging system can sense the changes in areas near to the skin-like sensors by measuring the capacitances between the array of electrodes. A 4D sensing approach has been developed with the spatiotemporal Total Variation algorithm. The 4D operational mode gives sensors the time awareness that allows for dynamical responses and hence the better control of the robots. Several experiments are conducted to show the skin-like behaviour of this sensor by simulating various scenarios. The sensor shows the excellent ability to detect an object in its vicinity, where the depth is close to half of the planar sensor array size.

Block-sparse two-dimensional off-grid beamforming with arbitrary planar array geometry.

For a sound field observed on a planar sensor array, compressive sensing (CS) reconstructs the two-dimensional (2D) direction-of-arrival (DOA) of multiple sources using a sparsity constraint. Conventional compressive beamforming methods suffer from grid mismatch, where true DOAs do not fall on the discretized angular search grid. This paper adopts a CS-based model, which can reconstruct block-sparse signals, and the model treats DOAs and the off-grid DOA compensation parts as blocks to deal with the off-grid 2D beamforming. The method is illustrated by numerical simulations and shows high estimation accuracy. Also, the approach does not require a specific array configuration and is suitable for arbitrary planar array geometry, which is practically useful. Since propeller tip vortex cavitation induces noise sources located sparsely near the propeller tip, the high-resolution of the method is demonstrated with experimental data from cavitation tunnel experiments.

Calibration of Room Temperature Magnetic Sensor Array for Biomagnetic Measurement

Biomagnetic field measurement is a promising tool for the investigation of electrical activities in a living body. Room temperature (RT) magnetic sensors with an improved resolution such as magnetoresistance (MR) devices have been recently employed for the detection of weak magnetic fields, which were earlier detected solely using superconducting interference device magnetic sensors. The position, orientation, and sensitivity of each magnetic sensor in a sensor array must be precisely determined for accurate magnetic source analysis. We proposed a calibration method using an array of multiple coils, which is applicable to an RT magnetic sensor array. To demonstrate the validity of the proposed calibration method, we applied it to an MR device-based magnetocardiography (MCG) system equipped with an L-shaped planar sensor array, which was newly developed for the simultaneous observation of both anterior and lateral sides of the body. The deviation of the sensor parameters from the designed values was estimated via calibration. The result of the marker coil localization test indicated that the calibration considerably improved the accuracy of the magnetic source analysis. Finally, we demonstrated a preliminary MCG measurement using the calibrated magnetic sensor array.

Monitoring of Indoor Airflows with a New Two-Dimensional Airflow Sensor

Although airflow is invisible, it has a big influence on the indoor environment. An incorrectly planned HVAC systems can lead to draught and thermal discomfort in occupied zones. Since the commissioning tests required after the installation of HVAC systems are generally performed without occupancy, the tests results do not always accurately represent the airflow that occurs during ordinary usage. The airflow needs to be continuously monitored and controlled by an intelligent HVAC system. The aim of this study is to develop a new two-dimensional airflow sensor for the monitoring of indoor airflow, which can also indicate the flow direction. Several of these sensors can be placed in a planar sensor array, by which a two-dimensional section of the flow field is created. By recording data from several of these arrays simultaneously, an image of the three-dimensional flow could be acquired. The prototype of the sensor, which is made by Hahn-Schickard Society for Applied Research is currently being validated at the Institute for Building Energetics, Thermotechnology and Energy Storage. When the development is completed, it will greatly contribute to the control strategies of HVAC systems.

Gas Leak Location Detection Based on Data Fusion with Time Difference of Arrival and Energy Decay Using an Ultrasonic Sensor Array.

Ultrasonic gas leak location technology is based on the detection of ultrasonic waves generated by the ejection of pressured gas from leak holes in sealed containers or pipes. To obtain more accurate leak location information and determine the locations of leak holes in three-dimensional space, this paper proposes an ultrasonic leak location approach based on multi-algorithm data fusion. With the help of a planar ultrasonic sensor array, the eigenvectors of two individual algorithms, i.e., the arrival distance difference, as determined from the time difference of arrival (TDOA) location algorithm, and the ratio of arrival distances from the energy decay (ED) location algorithm, are extracted and fused to calculate the three-dimensional coordinates of leak holes. The fusion is based on an extended Kalman filter, in which the results of the individual algorithms are seen as observation values. The final system state matrix is composed of distances between the measured leak hole and the sensors. Our experiments show that, under the condition in which the pressure in the measured container is 100 kPa, and the leak hole–sensor distance is 800 mm, the maximum error of the calculated results based on the data fusion location algorithm is less than 20 mm, and the combined accuracy is better than those of the individual location algorithms.

Flexible planar electromagnetic sensor array fabricated with printing electronic technology

Although flexible planar electromagnetic sensor array has many advantages such as good conformability, strong adaptability and high efficiency, there is a conflict between their sensitivity and spatial resolution. The relationship between sensitivity and structural parameters of planar coil are analyzed in this paper, and a novel printing electronic technology (PET) is employed to fabricate the flexible planar electromagnetic sensor array. When the spatial resolution of two planar sensors is the same, experiments indicate that the sensitivity of flexible planar sensor fabricated with PET is 10 times of that fabricated with traditional flexible printed circuit (FPC) technology, which can improve the detection ability to micro defects significantly. The flexible planar electromagnetic sensor array fabricated with this method can be applied to inspect components with irregular surface.

Two-sided residual refocusing for an acoustic lens-based photoacoustic imaging system

In photoacoustic (PA) cameras, an acoustic lens-based system can form a focused image of an object plane. A real-time C-scan PA image can be formed by simply time gating the transducer response. While most of the focusing action is performed by the lens, residual refocusing is needed to image multiple depths with high resolution simultaneously. However, a refocusing algorithm for a PA camera has not been studied so far in the literature. In this work, we reformulate this residual refocusing problem for a PA camera into a two-sided wave propagation from a planar sensor array. One part of the problem deals with forward wave propagation while the other deals with time reversal. We have chosen a fast Fourier transform (FFT) based wave propagation model for the refocusing to maintain the real-time nature of the system. We have conducted point spread function (PSF) measurement experiments at multiple depths and refocused the signal using the proposed method. The full width at half maximum (FWHM), peak value and signal to noise ratio (SNR) of the refocused PSF is analyzed to quantify the effect of refocusing. We believe that using a two-dimensional transducer array combined with the proposed refocusing can lead to real-time volumetric imaging using a PA camera.

Influence of Magnetic Measurement Modeling on the Solution of Magnetostatic Inverse Problems Applied to Current Distribution Reconstruction in Switching Air Arcs

This paper presents a systematic analysis of the influence of magnetic measurement modeling on the regularized solution of magnetostatic inverse problems. The focus is on the application of the inverse problem technique to current distribution reconstruction of arc plasmas inside low-voltage switching devices. The inverse problems modeled with both the ideal sensor assumption and non-ideal sensor modeling are studied, considering the geometry and active area of sensors. The Tikhonov regularization is adopted to address the ill posedness of the inverse problem. Sensor arrays with random variations in sensor directions and positions are compared with arrays using perfectly aligned setup. The numerical results reveal that for mono-axial planar sensor arrays the ideal sensor assumption could be used to simplify the modeling process with serious environmental noises. Better reconstruction can be obtained using the non-ideal sensor model when the sensor variations are large.

Oblique Projection Based Enumeration of Mixed Noncoherent and Coherent Narrowband Signals

In many application scenarios, the signals impinging on the array of sensors comprise the noncoherent (uncorrelated and/or partially correlated) signals and the coherent signals with several groups due to multipath propagation. In this paper, we consider the problem of estimating the number of noncoherent narrowband signals and that of coherent narrowband signals with multiple groups impinging on a planar sensor array composed of two parallel uniform linear arrays (ULAs), and an oblique projection based enumerator for the mixed signals (OPEMS) is proposed by utilizing the QR decomposition based ratio criterion (QRRC) for rank determination of a matrix. In the OPEMS, the number of noncoherent signals and that of coherent signals in each group are estimated separately, where only the elevation angles of noncoherent signals are estimated to isolate the coherent signals from the noncoherent ones, and the computationally intensive and time-consuming eigendecomposition procedure is avoided. The consistency of the proposed OPEMS is analyzed, and its effectiveness is verified through numerical examples.

ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY FOR PALM COOKING OIL DISCRIMINATOR USING PLANAR ELECTROMAGNETIC SENSOR ARRAY

Cooking oil is an important product in the Malaysia food industries. Most of the cooking oil products is based on palm oil. However, there are activities in selling cheaper cooking oil by labelling as high quality in cooking oil product. Traditional methods have been developed to measure the quality of the cooking oil product such as the chromatography technique but the cost for the system setup is expensive and requires a large amount of time to analyse the sample. Thus, a suitable and reliable system with less analysis time is needed for widespread industrial uses. This paper has presented a discriminative technique for palm cooking oil using Electrochemical Impedance Spectroscopy (EIS) with planar electromagnetic sensor array. The sensor consists of a meander sensor and an interdigital sensors which interact with the test samples. Three types of palm cooking oil such as double refined palm oil, refined and deodorized palm oil with peanut and sesame oil, and filtered palm oil were prepared. The results obtained showed that the presented technique was able to differentiate the samples between 20 kHz to 1 Mhz. The results obtained correlate with the theories on EIS technique and planar electromagnetic sensor which are presented in this paper.

Development of planar electromagnetic sensor array for nitrate and sulphate detection in natural water sources

Purpose – The purpose of this study is to determine the contamination level in natural water resources because the tremendous development in the agriculture sector has increased the amount of contamination in natural water sources. Hence, the water is polluted and unsafe to drink. Design/methodology/approach – Three types of sensor arrays were suggested: parallel, star and delta. The simulation of all types of sensor array was carried out to calculate the sensors’ impedance value, capacitance and inductance during their operation to determine the best sensor array. The contamination state was simulated by altering the electrical properties values of the environmental domain of the model to represent water contamination. Findings – The simulation results show that all types of sensor array are sensitive to conductivity, σ, and permittivity, ɛ (i.e. contaminated water). Furthermore, a set of experiments was conducted to determine the relationship between the sensor’s impedance and the water’s nitrate and sulphate contamination. The performance of the system was observed where the sensors were tested, with the addition of distilled water with different concentrations of potassium nitrate and potassium sulphate. The sensitivity of the developed sensors was evaluated and the best sensor was selected. Practical implications – Based on the outcomes of the experiments, the star sensor array has the highest sensitivity and can be used to measure nitrate and sulphate contaminations in water. Originality/value – The star sensor array presented in this paper has the potential to be used as a useful low-cost tool for water source monitoring.