Sensor System For Detection Research Articles

Near-Infrared Dual-Gas Sensor System for Methane and Ethane Detection Using a Compact Multipass Cell

In this invited paper, a compact dense-pattern multipass cell-based near-infrared sensor system was demonstrated for detection of parts-per-billion in volume (ppbv)-level methane (CH4) and ethane (C2H6). The dimension size of the fabricated gas cell is 18.5 × 8 × 9 cm3 with an absorption path length of 9.39 m. CH4 measurement was realized within a spectral range of 6,046–6,048 cm−1 and an absorption line of 6,046.95 cm−1. The spectral range for C2H6 detection is 5,951–5,953 cm−1 with an absorption line of 5,951.73 cm−1. Allan deviation analysis was used for evaluating the dual-gas sensing performance, and a detection limit of 78 ppbv for CH4 and 190 ppbv for C2H6 were achieved, respectively, with an averaging time of 0.8 s. Furthermore, CH4 measurement in the indoor and outdoor atmosphere was both performed to verify the field sensing capability of the sensor system. Compared with two separate sensor systems for CH4/C2H6 sensing, the proposed dual-gas sensor system using two near-infrared lasers and one multipass cell has the advantages of low-cost, compact-size without decreasing the selectivity and sensitivity.

Integrated solid-state wearable sweat sensor system for sodium and potassium ion concentration detection

PurposeDesign, fabricate and evaluate all-solid-state wearable sensor systems that can monitor ion concentrations in human sweat to provide real time health analysis and disease diagnosis capabilities.Design/methodology/approachA human health monitoring system includes disposable customized flexible electrode array and a compact signal transmission-processing electronic unit.FindingsPatterned rGO (reduced-graphene oxide) layers can replace traditional metal electrodes for the fabrication of free-standing all solid film sensors to provide improved flexibility, sensitivity, selectivity, and stability in ion concentration monitoring. Electrochemical measurements show the open circuit potential of current selective electrodes exhibit near Nernst responses versus Na+ and K+ ion concentration in sweat. These signals show great stability during a typical measurement period of 3 weeks. Sensor performances evaluated through real time measurements on human subjects show strong correlations between subject activity and sweating levels, confirming high degree of robustness, sensitivity, reliability and practicality of current sensor systems.Originality/valueIn improving flexibility, stability and interfacial coherency of chemical sensor arrays, rGO films have been the developed as a high-performance alternative to conventional electrode with significant cost and processing complexity reduction. rGO supported solid state electrode arrays have been found to have linear potential response versus ion concentration, suitable for electrochemical sensing applications. Current sweat sensor system has a high degree of integration, including electrode arrays, signal processing circuits, and data visualization interfaces.

The first application of sensory structures based on photoelectric transducer for the study of enzymatic reactions

Background. The development of highly sensitive sensor equipment with the possibility of registering analytes in real time is a fast growing research area and a promising diagnostic biomedical technology. Currently, the standard laboratory method for determining the activities of ATPses is an indirect spectroscopic study of the concentration of inorganic phosphate formed as a result of ATP hydrolysis by these enzymes. However, there is no commercially available phosphate sensor with satisfactory parameters of sensitivity, selectivity and stability over time. The purpose of our research was the deve­lopment of a photoelectric recombination sensor system for the real-time detection of biochemical markers and its testing on the example of screening ATPase activity of rat erythrocyte plasma membrane suspension preparations. Materials and Methods. Experiments were performed on suspension preparations of plasma membranes of erythrocytes of Wistar rats. Preparations of plasma membrane suspensions obtained by Dodge method from each animal were divided into aliquots and used for the simultaneous study of ATPase activity by the reference method of Rathbun & Betlach, as well as the registration of photocurrents induced during the passage of the ATPase reaction using the photoelectric recombination multisensor system of our own design. Results. The application of silicon sensory structures based on photoelectrical transducer principle for detecting the activity of adenosine triphosphate hydrolases on the example of total Mg2+,Na+,K+-ATPases preparations of plasma membranes of rat erythro­cytes has been experimentally tested. The directly measured analytic parameter is the photocurrent of the deep silicon barrier structure under illumination with high absorption coefficient. The physical features of the device operation have been examined. Detection of such metabolites becomes possible due to reactions intermediates with their own dipole moment (inorganic phosphate, which is one of the products of ATP hydrolysis). The drastic change of photocurrent that characterizes the course of biochemical reaction was observed in real time. The effect is explained by local electrostatic influence on the parameters of recombination centers at the silicon surface that results in surface recombination velocity change. The sensor operation is qualitatively explained in the frame of Stevenson-Keyes’s theory. Conclusions. Our approach can be regarded as a promising way to elaborate technically simple and highly sensitive method for detection of quantitative behavior of enzymatic reactions. Moreover, the local modification of silicon surface allows obtaining time depending scenarios of the adsorption and thus improving the sensitivity of the sensor. These circumstances open up the possibility of elaborating the complex sensory structures with optimized parameters for certain enzymatic reactions.

Near-Infrared Wide-Range Dual-Gas Sensor System for Simultaneous Detection of Methane and Carbon Monoxide in Coal Mine Environment

Near-Infrared Wide-Range Dual-Gas Sensor System for Simultaneous Detection of Methane and Carbon Monoxide in Coal Mine Environment

Mobile Vehicle Measurement of Urban Atmospheric CH4/C2H6 Using a Midinfrared Dual-Gas Sensor System Based on Interband Cascade Laser Absorption Spectroscopy

A vehicle-mounted mobile mid-infrared dual-gas sensor system for simultaneous detection of methane (CH₄) and ethane (C₂H₆) was developed using two interband cascade lasers (ICLs) for targeting the absorption line of CH₄ at 3038.5 cm^-1 and the line of C₂H₆ at 2996.88 cm^-1, respectively. Two multi-pass gas cells (MPGCs) with an absorption path length of 26.4 m were utilized. The detection limit (1σ) of CH₄ using wavelength modulation spectroscopy (WMS) is ~ 4.1 parts-per-billion by volume (ppbv) with a 0.5 s averaging time, and the detection limit (1σ) of C₂H₆ is ~ 2.9 ppbv with a 0.5 s averaging time. Vehicle-mounted mobile measurement ability of the dual-gas sensor was enabled by a remote monitoring system based on an embedded Linux processor and a cloud server. Atmospheric CH₄ and C₂H₆ monitoring was performed for 48 hours on the Jilin University campus to evaluate the performance of the sensor system. Vehicle-mounted mobile campaigns were carried out both on the Jilin University campus and in the Changchun Area for dual-gas concentration mapping. The sensor system shows the merits of remote monitoring and mobile gas sensing ability in field applications.

Mid-Infrared Methane Sensor System for Natural Gas Leakage Detection and Its Application

Mid-Infrared Methane Sensor System for Natural Gas Leakage Detection and Its Application

Design and Construction of a Superconducting Gravimeter Prototype

To promote China’s research on fields related to high-accuracy gravity measurement, the Institute of Electrical Engineering, Chinese Academy of Sciences (IEECAS), is committed to developing superconducting gravimeters. A superconducting gravimeter prototype has been successfully designed, fabricated, and tested through continuous improvement and optimization design. This article describes the main components of the prototype: superconducting gravity sensor, magnetic shield, cryogenic system, and displacement detection and feedback system. The novel work improves the superconducting gravity sensor on the persistent current switch and superconducting joint. Furthermore, the method for testing the levitation stiffness is also introduced, and the result demonstrates that an electromagnetic force method is a feasible approach with fast and good linearity. Finally, experimental test results on the prototype are shown, where solid Earth tide, temperature effect, and parasitic mode are obtained in the prototype signal. Moreover, it is shown that the levitation stiffness obtained by the electromagnetic force method and the tidal observation method are close to each other.

Sewage Flowrate Measurement Based on Array Ultrasonic Sensor and Entropy Analysis

Sewage is the second water resource. The accurate measurement of sewage flowrate is an essential link in the process of sewage resource utilization. In this article, we present a novel sewage flowrate measurement method based on ultrasonic phased array sensor with multi array elements and multi acoustic beams. The flow field information in the ultrasonic scanning plane is obtained by extending the non-contact single point information detection technology to the non-contact multi-point information detection technology, and then combined with the velocity distribution characteristics of the flow field, the entropy analysis method is used to build high-precision sewage flowrate measurement models, which can be developed into a promising sewage flowrate measurement solution. A series of experiments are carried out on the array ultrasonic sensor detection system designed and built in our laboratory. The experimental results, with the combined uncertainty is 0.069 m3/h, show that this method can accurately estimate the sewage flowrate. The circled entropy-boundary layer model has excellent prediction accuracy in 7–14 m3/h range, whose relative error (RE) is less than 2% and the mean absolute percentage error (MAPE) is 0.62%, which has obvious advantages compared with the accuracy of existing flow measurement technologies in the literatures. This study offers new insights on the application of array ultrasonic sensor and entropy analysis signal processing method in sewage flowrate measurement.

Development and field deployment of a mid-infrared CO and CO2 dual-gas sensor system for early fire detection and location

In order to realize early fire detection and location, a mid-infrared carbon monoxide (CO) and carbon dioxide (CO2) dual-gas sensor system was developed, which mainly includes a gas pretreatment module, a CO2 sensor module, a CO sensor module, and a laptop monitoring platform. CO2 and CO absorption lines located at 4.26 μm and 4.66 μm, respectively, were selected to ensure good selectivity of the sensor system. A series of experiments were carried out to evaluate the sensor performance. The 10–90% response time of the CO and CO2 sensor modules was measured to be ∼ 30 s at a flow rate of 1 L/min, and the limits of detection (LoD) of CO2 and CO were assessed to be 5.66 parts per million by volume (ppmv) and 0.94 ppmv, respectively, when the averaging time was 0.25 s. According to the correlation between CO2 and CO concentration in the early fire stage, a method of early fire detection was studied and proposed using the normalized concentration ratio between CO and CO2 (C(CO)/C(CO2)) as the key alarm parameter. Based on gas turbulent diffusion (GTD) model combined with particle swarm optimization (PSO) algorithm, a mobile early fire location method was presented. Correlative experiment results verified that the reported sensor system has a good performance for early fire detection and location.

Characterization Studies of a GC based SAW Sensor System for Potential Detection and Identification of Toxic Environmental Gases/Vapors

The characterization of a custom-designed GC-based SAW e-Nose sensor system is presented here to study the sensing ability of the sensor system to detect and identify low medium and high toxic vapors. A semi-automated multi-vapor generator generates vapors of chemical compounds that are then exposed to the sensing system to examine its performance under various concentrations. Time-domain verses frequency response of GC-SAW Sensor is noted for repeated cycles against different chemical compounds like xylene, 1,2 dibromoethane, dimethyl sulfate, triethyl phosphate, nitrobenzene, phosphorous trichloride being tested. The generated data is examined using a principle component analysis (PCA) technique to detect a unique response for an individual chemical compound. Experimental results are reported.

Adoption of Precision Technologies by Brazilian Dairy Farms: The Farmer's Perception.

Simple SummaryUnderstanding the perception of dairy farmers regarding precision livestock technologies is crucial for creating strategic actions that will increase the rate of adoption and usage of such technologies. A survey study was applied to 378 dairy farms located in Brazil. The farmers were characterized based on technology usage, farmer profile, farm characteristics, and production indexes. The farms were classified into seven clusters: (1) top yield farms; (2) medium–high yield, medium-tech; (3) medium yield and top high-tech; (4) medium yield and medium-tech (5); young medium–low yield and low-tech; (6) elderly medium–low yield and low-tech; and (7) low-tech grazing. Our study helped to elucidate the farmer’s perception about precision technologies and to shed light on challenges that need to be addressed by scientific research and extension programs.The use of precision farming technologies, such as milking robots, automated calf feeders, wearable sensors, and others, has significantly increased in dairy operations over the last few years. The growing interest in farming technologies to reduce labor, maximize productivity, and increase profitability is becoming noticeable in several countries, including Brazil. Information regarding technology adoption, perception, and effectiveness in dairy farms could shed light on challenges that need to be addressed by scientific research and extension programs. The objective of this study was to characterize Brazilian dairy farms based on technology usage. Factors such as willingness to invest in precision technologies, adoption of sensor systems, farmer profile, farm characteristics, and production indexes were investigated in 378 dairy farms located in Brazil. A survey with 22 questions was developed and distributed via Google Forms from July 2018 to July 2020. The farms were then classified into seven clusters: (1) top yield farms; (2) medium–high yield, medium-tech; (3) medium yield and top high-tech; (4) medium yield and medium-tech; (5) young medium–low yield and low-tech; (6) elderly medium–low yield and low-tech; and (7) low-tech grazing. The most frequent technologies adopted by producers were milk meters systems (31.7%), milking parlor smart gate (14.5%), sensor systems to detect mastitis (8.4%), cow activity meter (7.1%), and body temperature (7.9%). Based on a scale containing numerical values (1–5), producers indicated “available technical support” (mean; σ2) (4.55; 0.80) as the most important decision criterion involved in adopting technology, followed by “return on investment—ROI” (4.48; 0.80), “user-friendliness” (4.39; 0.88), “upfront investment cost” (4.36; 0.81), and “compatibility with farm management software” (4.2; 1.02). The most important factors precluding investment in precision dairy technologies were the need for investment in other sectors of the farm (36%), the uncertainty of ROI (24%), and lack of integration with other farm systems and software (11%). Farmers indicated that the most useful technologies were automatic milk meters systems (mean; σ2) (4.05; 1.66), sensor systems for mastitis detection (4.00; 1.57), automatic feeding systems (3.50; 2.05), cow activity meter (3.45; 1.95), and in-line milk analyzers (3.45; 1.95). Overall, the concerns related to data integration, ROI, and user-friendliness of technologies are similar to those of dairy farms located in other countries. Increasing available technical support for sensing technology can have a positive impact on technology adoption.

Compact QEPAS humidity sensor in SF6 buffer gas for high-voltage gas power systems

In SF6 insulated high-voltage gas power systems, H2O is the most problematic impurity which not only decreases insulation performance but also creates an acidic atmosphere that promotes corrosion. Corrosion damages electrical equipment and leads to leaks, which pose serious safety hazards to people and the environment. A QEPAS-based sensor system for the sub-ppm level H2O detection in SF6 buffer gas was developed by use of a near-infrared commercial DFB diode laser. Since the specific physical constants of SF6 are strongly different from that of N2 or air, the resonant frequency and Q-factor of the bare quartz tuning fork (QTF) had changed to 32,763 Hz and 4173, respectively. The optimal vertical detection position was 1.2 mm far from the QTF opening. After the experimental optimization of acoustic micro-resonator (AmR) parameters, gas pressures, and modulation depths, a detection limit of 0.49 ppm was achieved for an averaging time of 1 s, which provided a powerful prevention tool for the safety monitoring in power systems.

The One-Dimensional Liquid Infiltration Characteristics of Ionized Rare Earth Based on Wireless Network Sensor Detection System

The in-situ liquid injection leaching process of ionized rare earth is a typical process of effusion infiltration, and the infiltration efficiency directly determines the mining efficiency. Assuming that the infiltrated (NH <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> ) <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> solution is uniformly distributed in the homogeneous orebody, the relationships between the following groups are derived and studied: (1) The position and time of the infiltration front; (2) The infiltration intensity and the infiltration time; (3) The advancing speed and time of the infiltration front.A wireless network sensor detection system for parameter detection is established based on 4G network,air pressure sensor and water sensor are embedded in the ore body.The sensors are connected to the terminal via the 4G network,the data collection and wireless transmission of water content change and air pressure change of one-imensional fluid infiltration test in the homogeneous ore body with different compaction density were completed by the proposed wireless network sensor detection system. The results show that the influence of residual air pressure can be ignored during the infiltration;the advancing speed of the infiltration front is the fastest at the beginning, and then gradually decreased and stabilized; the change process of infiltration volume corresponds to the process of infiltration front advancing speed; the higher the density, the slower the advancing speed of the infiltration front, the lower the infiltration intensity, and the more difficult the infiltration; the deduced theory can be in good agreement with the actual infiltration situation with high accuracy, which can effectively simulate the infiltration process of ionized rare earth in-situ liquid injection mining.

Application of the Proposed Fiber Optic Time Differential BOCDA Sensor System for Impact Damage Detection of a Composite Cylinder

An optical-fiber-embedded composite cylinder was fabricated using the filament winding process with an interval of 12 mm in the longitudinal direction of the cylinder. The optical fiber was wound 160 turns around the cylinder, and the straight length was about 125 m. After a total of twelve impact events of 5, 10, 15, and 20 J, the residual strain in the cylinder was measured using the proposed time differential BOCDA sensor system. This method makes the traditionally used optical delay unnecessary while increasing the degrees of freedom of using the modulation rate, which determines the spatial resolution of this measurement system. The modulation rates of optical light in the system were applied up to 16 Gbps, which is an eight-fold increase compared to our previous experiments. Damage maps were obtained by mapping the measured residual strain onto the structure of the cylinder, and compared using three spatial resolutions of 20, 10, and 6.25 mm. In the measured damage map, expansion deformation due to impact was measured at all impact points, and the impact location on the map and the actual location on the cylinder were exactly the same. The map measured from the composite showed a clear point-symmetrical shape with an increase in sharpness as the measurement resolution increased. At the highest resolution, material expansion and compression were observed to alternate with respect to the center of impact, like the surface deformation of a liquid caused by a thrown object. Furthermore, considered together with our previous experiments, we confirmed that this phenomenon propagated from the surface of the composite material to the interior, where the optical fiber was embedded. The total amount of residual strain formed around each impact point was linearly proportional to the applied external impact energy.

Intelligent Shopping Trolley (IST) - a social distancing device during pandemic shopping

Intelligent Shopping Trolley (IST) is a device that was built to help in fighting the Covid-19 pandemic. This Intelligent Shopping Trolley is equipped with a RFID and timer system, Indoor Positioning System (IPS) and Microwave Sensor Detection system to determine the distance and to alert customers as they shop in a supermarket. This Intelligent Shopping Trolley will also utilise the Internet of Things (IoT) to manage its functionality. The Intelligent Shopping Trolley will help customers to determine the distance between other customers while implementing social distancing measures that is recommended by the Ministry of Health Malaysia and manage their shopping time as well. Besides that, it helps supermarkets to track their customers after the time limit given to the customers ends. This paper explains the details on this Intelligent Shopping Trolley project. This project helps in making the community aware of the importance of social distancing.

Rapid Extraction and Detection of Biomolecules via a Microneedle Array of Wet‐Crosslinked Methacrylated Hyaluronic Acid

AbstractThe rapid detection of biomolecule levels in the human body is often required to monitor human health. Although swellable microneedle arrays are widely used to extract biomolecules in interstitial fluid in a minimally invasive manner, it takes 3–15 min to carry this out. Herein, we report the development of a microneedle sensor system for the rapid detection of biomolecules. By controlling the crosslinking sequence of methacrylated hyaluronic acid (MeHA) used in the microneedle array, we achieve a swelling ratio of approximately 600% in 30 s in vitro. Furthermore, an electrochemical measurement method is utilized to detect redox reaction of biomolecules extracted with the MeHA microneedle array and screen‐printed electrode. One can measure 1 × 10−6 m of dopamine in 3 s in vitro and with excellent selectivity in a solution of dopamine along with 100 × 10−6 m of L‐ascorbic acid and uric acid. Finally, ex vivo electrochemical analysis is performed on a gelatin phantom and porcine skin containing various concentrations of dopamine and can detect 10 × 10−6 m of dopamine within 30 s. Thus, the swellable hydrogel‐based microneedle array can be applied to biomolecule sensing in interstitial fluid within a few seconds.

Application of a solid-phase microextraction-gas chromatography-mass spectrometry/metal oxide sensor system for detection of antibiotic susceptibility in urinary tract infection-causing Escherichia coli – A proof of principle study

PurposeAntibiotic resistance is widespread throughout the world and represents a serious health concern. There is an urgent need for the development of novel tools for rapidly distinguishing antibiotic resistant bacteria from susceptible strains. Previous work has demonstrated that differences in antimicrobial susceptibility can be reflected in differences in the profile of volatile organic compounds (VOCs) produced by dissimilar strains. The aim of this study was to investigate the effect of the presence of cephalosporin antibiotics on the VOC profile of extended spectrum beta-lactamase (ESBL) and non-ESBL producing strains of Escherichia coli. Material and methodsIn this study, VOCs from strains of Escherichia coli positive and negative for the most commonly encountered ESBL, CTX-M in the presence of cephalosporin antibiotics were assessed using solid-phase microextraction (SPME) coupled with a combined gas chromatography-mass spectrometry/metal oxide sensor (GC-MS/MOS) system. ResultsOur proof-of-concept study allowed for distinguishing CTX-M positive and negative bacteria within 2 ​h after the addition of antibiotics. One MOS signal (RT: 22.6) showed a statistically significant three-way interaction (p ​= ​0.033) in addition to significant two-way interactions for culture and additive (p ​= ​0.046) plus time and additive (p ​= ​0.020). There were also significant effects observed for time (p ​= ​0.009), culture (p ​= ​0.030) and additive (p ​= ​0.028). No effects were observed in the MS data. ConclusionsThe results of our study showed the potential of VOC analysis using SPME combined with a GC-MS/MOS system for the early detection of CTX-M-producing, antibiotic-resistant E. coli, responsible for urinary tract infections (UTIs).

Multi-Feature Fusion Multi-Step State Prediction of Nuclear Power Sensor Based on LSTM

Aiming at the problem in the prediction of nuclear power working condition parameter, this paper uses a large number of time series collected by the nuclear power plant sensor detection system to propose a multi-feature fusion multi-step state prediction model based on long short-term memory network (LSTM). This paper takes the SG1 steam pressure sensor data collected by the real-time parameter system of nuclear power plants as the research object. Firstly, the data is preprocessed for the problems of missing data and inconsistent sampling time scales, and then the structural design and modeling of the multi-feature fusion multi-step state prediction model is completed based on LSTM. Finally, the prediction model proposed in this paper is compared with the multi-step prediction models such as Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Model-S1 layer and univariate LSTM. Experimental results show that the fitting performance and prediction performance of the prediction model proposed in this paper are with overall optimization, and it also verifies the applicability of the deep learning method based on the LSTM model in the field of nuclear power plant operation safety assurance.

Large dynamic-range fiber Bragg grating sensor system for acoustic emission detection.

A distributed feedback (DFB) fiber laser and fiber Bragg gratings (FBGs) are configured to demodulate the wavelength shifts of FBG dynamic strain sensors. The FBG sensors act as sensing units to detect the dynamic strain and the demodulators while the DFB fiber laser only acts as a narrow-linewidth light source. As the reflective spectrum of the FBG sensor changes due to dynamic strains, the output is subsequently converted into a corresponding intensity change and detected directly by a photodetector. The 0.2 nm linewidth FBG sensor can detect the impact signal with a frequency of up to 300 kHz with a maximum of 29.17 µɛ, which is comparable with the detecting result of the piezoelectric transducer sensor. Moreover, the directional response of the FBG sensor is maximized when the direction of acoustic wave propagation is parallel to the optical fiber. The relation between the sensitivity and the FBG spectrum linewidth is presented, and the detectable strain range versus different FBG linewidths is also discussed.

A smart ontology-based IoT framework for remote patient monitoring

The Internet of Things (IoT) is the most promising technology in health technology systems. IoT-based systems ensure continuous monitoring in indoor and outdoor settings. Remote monitoring has revolutionized healthcare by connecting remote and hard-to-reach regions. Specifically, during this COVID-19 pandemic, it is imperative to have a remote monitoring system to assess patients remotely and curb its spread prematurely. This paper proposes a framework that provides the updated information of the Corona Patients in the vicinity and thus provides identifiable data for remote monitoring of locality cohorts. The proposed model is IoT-based remote access and an alarm-enabled bio wearable sensor system for early detection of COVID-19 based on ontology method using sensory 1D Biomedical Signals such as ECG, PPG, temperature, and accelerometer. The proposed ontology-based remote monitoring system analyzes the challenges of encompassing security and privacy issues. The proposed model is also simulated using cooza simulator. During the simulation, it is observed that the proposed model achieves an accuracy of 96.33 %, which establishes the efficacy of the proposed model. The effectiveness of the proposed model is also strengthened by efficient power consumption.