Sensor Components Research Articles

A Resonant Cavity Based on Capacitively Loaded Coaxial Structure for Overhauser Magnetic Sensors

The RF excitation coil is an important component of the Overhauser magnetic sensor, which determines whether the dynamic nucleation polarization of the free radical solution can be carried out smoothly. A capacitance-loaded resonant cavity structure is proposed as the RF excitation of the Overhauser magnetic sensor. The structure and equivalent circuit of the capacitance-loaded coaxial resonant cavity are analyzed and improved on the conventional structure, and the resonant frequency is verified to be consistent with the excitation frequency of the free radical solution by modeling and simulation using COMSOL software. The resonant cavity solid was fabricated, and the cavity was tested by using a vector network analyzer. The results show that the initial resonance point of the homemade resonant cavity is 60.55MHz, and the frequency point can be adjusted to 60.7MHz by adjusting the loading capacitor and tuning capacitor; the resonant cavity return loss S11 is about -19dB, and the quality factor Q value is about 506.

Development of STEAM-Based Rain Alarm Prototype

The sudden changes in weather and unpredictable rain have an impact on human life. The objective of this research is to analyze the effectiveness and sensitivity of a rain alarm prototype and its relationship with STEAM. This study employs the ADDIE model (Analysis, Design, Development or Production, Implementation or Delivery, and Evaluations). Then, the benefits will be applied in student learning by teachers through global warming education with an environmental awareness theme. From this research, the following findings were discovered: 1) The rain alarm prototype has a high effectiveness, where each component used was successfully processed and utilized; 2) the sensitivity level revealed that the water, temperature, and humidity sensors have high sensitivity; 3) the relationship between the prototype and STEAM lies in the science aspect, as measured parameters were approached scientifically, the technology aspect through the utilization of the ThingSpeak application, engineering aspect through the collaboration of three different sensors (water, temperature, humidity), and analyzing their contributions in the field of classroom learning. In terms of art, the sensor components are neatly packaged and a housing is also created as an example of installation. Mathematics is found in the coding within the Arduino application. However, a limitation of the research is the inability to utilize an automatic roof system, which means that it cannot automatically lift snacks/clothes during rainfall. Therefore, future research can further develop this prototype by incorporating an automatic roof system.

Micro-force sensing techniques and traceable reference forces: a review

Micro-force measurement with high resolution, accuracy, and reliability is of interest in a broad range of applications including gravitational-wave detection, intelligent healthcare, bionic robotics, and micromanipulation. Herein, the researchand development in recent years of micro-force sensors based on various principles is reviewed thoroughly, presenting their characteristics and applications, as well as summarizing their advantages and limitations. The most indispensable component of force sensors, elastic sensitive elements, is underlined. Next, four kinds of not widely used but promising sensors are also introduced briefly. Finally, the traceable reference forces are analyzed, concluding with a future perspective into the corresponding challenges and opportunities of micro-force sensors for future research. This review aims at providing references for developing micro-force sensors and improving their performance.

CoFe2O4 embedded bacterial cellulose for flexible, biodegradable, and self-powered electromagnetic sensor

Self-powered flexible electromagnetic sensors based on flexible magnets are promising to be applied in wearable field. As the core component of motion sensors, flexible magnets are getting growing attentions. However, most reported flexible magnets were fabricated with non-degradable substrate materials via complicated processes. Here, a novel flexible, biodegradable and self-powered electromagnetic sensor was prepared based on CoFe2O4-embedded magnetic bacterial cellulose, which is prepared by a facile and economical in-situ co-precipitation paired with a post-process of hot-pressing and magnetizing. Magnetic CoFe2O4 nanoparticles were synthesized in network structure of degradable bacterial cellulose for flexible composited magnetic films. Degradation experiment demonstrated that the flexible magnetic films degraded completely within 56 h, and the left magnetic materials of CoFe2O4 nanoparticles could be recycled. The flexible electromagnetic sensors based on composited films were tested in a customized testing platform, manifesting excellent sensing properties and stability. To deeply verify the application potential of the flexible electromagnetic sensors, an intelligent jacket, which was sewn with flexible magnetic film and copper coils was designed. It is capable of monitoring motion signals and distinguishing the motion state, proving that the biodegradable flexible electromagnetic sensor is promising to be utilized in wearable field as a kind of eco-friendly flexible sensor.

A convenient, low-cost graphene UV-cured additive manufacturing electronic process to achieve flexible sensors

The reductions in manufacturing cost and process complexity of flexible sensors are of great significance in popularizing their applications. In present work, a Graphene UV-Cured Direct Electronic (GUDE) process based on photo-curing additive manufacturing technology is proposed and used to fabricate flexible electrode components of wearable respiratory sensors with excellent electrical responses. The method enables one to directly print the conductive structures without the need for cumbersome preparation and complex equipment. Compared with screen printing and microfabrication process that involve the mask preparation, the GUDE process can rapidly produce electrode patterns of any shape, thereby shortening the molding process and time cost of flexible electrodes. Moreover, GUDE process is additive manufacturing process, which saves the cost of raw materials. To verify the feasibility and application of the GUDE technology, a flexible humidity-sensing electronic device is fabricated. The humidity-sensing electronic device has a rapid response and recovery time of 0.27 s and 0.34 s, respectively, and a linear range in relative humidity variation between 39.3 % and 88.3 %. It can be perfectly attached to skin/surface where humidity needs to be monitored, and then be used in scenarios such as detection of body signals like respiration, disease diagnosis, monitoring of exercise status and industrial humidity/air flow, etc. In addition, excellent humidity responsiveness is attributed to enhanced adsorption capability of GUDE-printed surface microstructures due to large specific surface area and hydrophobic properties of graphene. In conclusion, the GUDE process, as a fast, direct electronic printing technology, offers broad prospects in the fabrication of flexible, high-performance electrical sensors, and has great potential for manufacturing advanced electronic devices.

A New Electro-Optical-Thermal Modelling for Non-Dispersive IR Sensing Technique of Gas Concentration

In this research, a new electro-optical-thermal modeling is proposed and built by simulation program with integrated circuit emphasis (SPICE). In particular, it is constructed for use in the non-dispersive infrared (NDIR) sensing technique of gas concentration. This model, based on the theory of circuitry and the Beer-Lambert law, includes various equivalent elements for the optics, sensor, and circuits. To build and investigate the validity of the proposed model, an NDIR for measurement of CO2 is built with the hybrid combination of a thermopile sensor with a specific wavelength filter, an infrared micro electro mechanical systems (MEMS) heater, an optical tube, amplification circuits with a chopper amplifier, advanced RISC machine (ARM)-based micro processing unit and discrete electronic devices. The thermal properties of the light source with periodic modulation have been studied from the output signal of a thermopile within the limit of modulation frequency. Based on the thorough measurements of output signals and transient responses, the thermal and optical parameters of the sensor and optical components for this model are extracted. The comparison of the simulation and experimental data of the NDIR measurement for different CO2 concentrations shows a great agreement with a maximum error of 0.27% at 3500 ppm. This approach allows for the development of a high-level sensor and circuit integrated simulation based on the most fundamental principles and multiple variables.

On Data-Driven Self-Calibration for IoT-Based Gas Concentration Monitoring Systems

In this article, data-driven self-calibration algorithms for the Internet of Things-based gas concentration monitoring systems embedded with low-cost gas sensors are designed. The measurement errors are assumed to be caused by imperfect compensation for the variation of sensor component behavior. Specifically, the calibration procedure for the nondispersive infrared <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$CO_{2}$ </tex-math></inline-formula> sensors is developed, for which the temperature dependency is the most dominant drift source. For a single sensor, the hidden Markov model is used to characterize the statistical relationship between different quantities introduced by the physical model that builds on the Beer–Lambert law. For the calibration in the Internet of Things-based system, sensors first transmit their belief functions of the true gas concentration level to the cloud. Then, the cloud fusion center computes a fused belief function according to certain rules. This belief function is then used as reference for calibrating the sensors. To deal with the case where belief functions highly conflict with each other, a Wasserstein distance-based weighted average belief function fusion approach is first proposed as a networked calibration algorithm. To achieve more long-term stable calibration results, the networked calibration problem is further formulated as a partially observed Markov decision process (MDP) problem, and the calibration strategies are derived in a sequential manner. Correspondingly, the deep <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -network approach is applied as a computationally efficient method to solve the proposed MDP problem. The performance of practical designs of the proposed self-calibration algorithms is finally illustrated in numerical experiments utilizing real data.

The prototype of IOT-Based weight scale and calorie tracking application

This research designs the prototype of Internet of Things based scale with calorie tracking application in purpose to help optimize the application of healthy lifestyle. This research is done through numerous steps including analysis of needs, designing the devices and system, software programming, device integration, device testing, and maintenance. This research developed Internet of Things based scale with sensor load cell and HX711 module as weight sensor component, Node MCU as microcontroller component, battery as voltage source, and firebase as database to store the result of body weight measurement. Android application developed with Android Studio, visual studio code, and java programming language. Internet of Things based scale is functioned to measure body weight in real-time which connected to android application to display body weight, calculate Body Mass Index (BMI), calculate daily calories needs including Basal Metabolic Rate (BMR) and Total Energy Expenditure (TEE), provide information of food calories and exercise and total calories recording to monitor daily intake and output.

Establishing an Intelligent Emotion Analysis System for Long-Term Care Application Based on LabVIEW

In this study, the authors implemented an intelligent long-term care system based on deep learning techniques, using an AI model that can be integrated with the Lab’s Virtual Instrumentation Engineering Workbench (LabVIEW) application for sentiment analysis. The input data collected is a database of numerous facial features and environmental variables that have been processed and analyzed; the output decisions are the corresponding controls for sentiment analysis and prediction. Convolutional neural network (CNN) is used to deal with the complex process of deep learning. After the convolutional layer simplifies the processing of the image matrix, the results are computed by the fully connected layer. Furthermore, the Multilayer Perceptron (MLP) model embedded in LabVIEW is constructed for numerical transformation, analysis, and predictive control; it predicts the corresponding control of emotional and environmental variables. Moreover, LabVIEW is used to design sensor components, data displays, and control interfaces. Remote sensing and control is achieved by using LabVIEW’s built-in web publishing tools.

Mechanical dissipation by substrate–mode coupling in SiN resonators

State-of-the-art nanomechanical resonators are heralded as a central component for next-generation clocks, filters, resonant sensors, and quantum technologies. To practically build these technologies will require monolithic integration of microchips, resonators, and readout systems. While it is widely seen that mounting microchip substrates into a system can greatly impact the performance of high-Q resonators, a systematic study has remained elusive, owing to the variety of physical processes and factors that influence the dissipation. Here, we analytically analyze a mechanism by which substrates couple to resonators manufactured on them and experimentally demonstrate that this coupling can increase the mechanical dissipation of nanomechanical resonators when resonance frequencies of resonator and substrate coincide. More generally, we then show that a similar coupling mechanism can exist between two adjacent resonators. Since the substrate–mode coupling mechanism strongly depends on both the resonator position on the substrate and the mounting of the substrate, this work provides key design guidelines for high-precision nanomechanical technologies.

Piezoionic strain sensors enabled by force-voltage coupling from ionogels

Flexible piezoionic strain sensors with high sensitivity are critical to artificial intelligence. Solid-state ion conductors are basic components in piezoionic sensors, and have great effects on the sensing properties. Here, we have put forward an ionogel composed of polyvinyl alcohol and ionic liquid, which presents high ionic conductivity and superior flexibility. The ionogel fabrication is simple and shows potential for large-scale production. The force-voltage coupling effect makes ionogels as promising candidates for sensor application. Further, piezoionic sensors based on ionogels display good sensing properties with high working stability, and have been applied for detection of subtle pulse signals.

Optimized electric heater configuration design with magnetic-field self-suppression using genetic algorithm

Atomic vapor cells are core components in various atomic sensors, and usually heated by an electric heater which would generate an additional magnetic field. To sufficiently suppress this magnetic-field interference, an optimized electric heater configuration method with magnetic-field self-suppression using a genetic algorithm is proposed. The resistance tracks in the electric heater configuration are decomposed into several heating coils; the size and current direction of each coil are optimized by the genetic algorithm to minimize the magnetic field in the heated space. The effectiveness of the proposed method is verified through the finite element simulation and an experimental test. The results show that for the optimal electric heater configuration, the average magnetic flux density introduced is approximately 2–4 times less than and dozens of times less than, respectively, the average magnetic flux density introduced in previously proposed 2 N multipole and common spiral configurations. This study is significative for electric heating with lower magnetic field and contributes to further improving the performance of atomic sensors.

Nonlinear Behavior during the Electrochemical Oxidation of Thiols

The electrochemical behavior of sulfur-containing compounds is of great importance in fields ranging from diagnostics to energy-storage and materials chemistry. For example, thiols (R-SH) are important components of many electrochemical sensors and are routinely used in materials applications as they are known to form well-ordered and reproducible monolayers (self-assembled monolayers, SAMs) on various metal surfaces. Sulfur compounds are also interesting from the viewpoint of nonlinear dynamics owing to the presence of multiple oxidation states, which has been exploited to study complex dynamic behavior in both chemical and electrochemical systems. In this work we explore the oscillatory behavior of 2-(dimethylamino)ethanethiol (DMAET), a known hydrolysis product of V-type nerve agents, on platinum electrodes. Interestingly, the electrochemical oxidation of DMAET leads to two distinct regions of oscillatory behavior. Probing the system with electrochemical impedance spectroscopy (EIS), resulted in the classification of the DMAET system as an HN-NDR type oscillator. These results are compared to structurally similar thiol containing compounds towards the goal of elucidating general features which permit the evolution of dynamic behavior in thiol-based electrochemical systems.

Low-Pb High-Piezoelectric Ceramic System (1-x)Ba(Zr0.18Ti0.82)O3-x(Ba0.78Pb0.22)TiO3.

Piezoelectric materials, especially Pb-based piezoelectric materials, are widely used in the key components of sensors, actuators, and transducers. Due to the rising concern of the toxicity of Pb, global legislation has been adopted to restrict the use of Pb. Given that the available Pb-free piezoelectric materials cannot replace the Pb-based ones for various reasons, we designed and fabricated a low-Pb piezoelectric solid-solution ceramic system, (1–x)Ba(Zr0.18Ti0.82)O3–x(Ba0.78Pb0.22)TiO3 (denoted as BZ0.18T–xBP0.22T herein). The crystal structure, ferroelectric, dielectric, and piezoelectric properties of the BZ0.18T–xBP0.22T system were systematically studied. With the increase in BP0.22T content, the structure of the samples changed from a rhombohedral phase to a tetragonal phase; the intermediate composition x = 0.5 was located at the morphotropic phase boundary of the system and corresponded to the state with the coexistence of the rhombohedral and tetragonal phases. Moreover, x = 0.5 exhibited the optimum comprehensive properties among all the samples, with a piezoelectric coefficient d33 of 240 pC/N, a maximum dielectric temperature Tm of 121.1°C, and a maximum polarization Pm of 15 μC/cm2. Our work verifies the validity of the route to design low-Pb high-piezoelectric materials and may stimulate the interests for exploring new low-Pb high-performance ferroelectric and piezoelectric materials.

Application Research on Sensors and Detection Technology in Mechatronics System

Sensors and detection technology play a very important role in the industrial control industry. Sensors play a pivotal role in various intelligent equipment. Sensors are divided into a variety of sensors. Reasonable sensor components can be used according to the actual situation of the application. However, the application of sensors and detection technology in mechatronics systems is very common, so this research work aims to focus on the analysis of sensors and detection technology, and to study the application of this technology in mechatronics control systems. In the final phase of this research, a future analysis of the application status of sensors and detection technologies is carried out. It aims to provide the necessary theoretical basis for the improvement and innovation of modern sensors and detection technology.

Colour Detecting and Sorting Robot

Abstract: In this digital world, color processing in numerous industries gives us more leverage to unravel the consistency problem of continuous manual sorting. This document are a replacement approach to continuously detect and classify objects and keep them in a very specific place. Color processing attracts plenty of attention since the assistance of contemporary technology results in the likelihood of expanding the scope of its application in various areas. The Arduino Nano microcontroller, TCS3200 colour sensor, servo motor, and other electronic components are wont to study, develop, and build a color sorter. This work involves sensors that detect the colour of the item and send the signal to the Arduino. The microcontroller sends a proof to the circuitry that drives the varied motors to activate the thing and place it within the specified location. supported the detection, everything moves to the required position releases the thing, and returns to the first position. The system is in a position to quickly classify the article supported its color at the respective color station. Sorting objects is an essentially mechanical process that needs difficult work. The chronically manual layout ends up in consistency problems. Above all, machines can do boring tasks that humans are superior to. Worker burnout in sequential production structures can result in reduced execution and purpose issues in maintaining the article. Recognize the colour of the article but in no way a machine. during this article, a compact registration near the arrangement of things supported color was implemented using the TCS3200 color sensor with servo motors in conjunction with Arduino Nano.

Investigation and optimization of PDMS/PES membrane on morphology and performance for methane-water separation

Methane detection is important for exploring combustible ice in energy field. As the core component of the methane sensor, gas-liquid separation membranes play a crucial role in separating methane from water, which can effectively enhance the timeliness and stability of methane detection. Moreover, the correlative permeability and mechanical properties of are contradictory requirements for achieving optimum performance of membranes. Herein, a methane-water separation membrane was developed and optimized by adjusting the PEG as porogen based on PDMS and PES as functional and support layers, respectively. PDMS/PES composite membrane performed an excellent methane permeability and tensile strength. Particularly, the PEG was studied as porogen to affect the morphology and adjust pore structure of the PES layer. Considering the trade-off of methane permeability and mechanical properties, the results indicate the appropriate content of porogen is 4 wt% PEG. This work optimizes a new approach to prepare methane-water separation membrane and give a significant insight to develop methane detection for exploring new energy in seabed.

A Review of IoT-Enabled Mobile Healthcare: Technologies, Challenges, and Future Trends

The Internet of Things (IoT) has grown over decades to encompass many forms of sensing modalities, and continues to improve in terms of sophistication and lower costs. The trend of hardware miniaturization and emphasis on user convenience has inspired numerous studies to integrate more varied devices within the IoT into modernizing healthcare systems, facilitating applications, such as activity recognition, fitness assistance, vital signs monitoring, daily dietary tracking, and sleep monitoring. These applications are vital for prevention, detection, and treatment of ailments and can be realized using both dedicated health sensors as well as general-purpose sensors not originally designed for health monitoring. This article surveys such studies, detailing smart health monitoring systems, and the types of sensor components utilized within the IoT. We categorize and analyze these works based on their leverage of device-based techniques (i.e., use of sensors worn or carried by the person) and device-free techniques (i.e., wireless sensing without need to carry hardware), as well as signal processing and classification techniques utilized. In particular, we discuss how different combinations of these techniques can be creatively applied to support professional and commercial health-monitoring IoT networks. We also identify limitations and potential directions that future research may explore.

Characterization of a novel microhotplate for application in a silicon-based nanofilm gas sensor

The micro-hotplate is the core component of the silicon-based nano-film gas sensor and directly affects the overall performance. This paper first analyzes the heat dissipation of the micro-hotplate and establishes a heat transfer calculation model. Multiphysics coupling is used to optimize the arrangement of the heating and test electrodes to obtain the best design of the micro-hotplate. Next, silicon-based micro-electro-mechanical system (MEMS) performs micro-hotplate processing and electrical connections according to the parameters optimized by the finite element. Lastly, the temperature coefficient of resistance measurement and infrared microscopic imaging were used to complete the characterization of the hotplate and the verification of the theoretical simulation was completed. The size of the micro-hotplate unit is 500 μm × 500 μm, and the area of the heating film area is 160 μm × 160 μm. The micro-hotplate designed in this paper has low power consumption and may be operated up to 357.5 °C with a power of 28.6 mw. Below the working temperature of 357.5 °C, the resistance of the micro-hotplate has an excellent linear relationship with temperature without warping or fracture. The micro-hotplate is small in size and may allow large-scale sensor array integration.

Highly Stretchable and Transparent Conductive Electrodes for Resistive Strain Sensors

AbstractConductive organic materials are a crucial component of resistive strain sensors because phase separation limits the concentration of inorganic materials in polymer matrices, leading to poor electrical conductivity. However, traditional conductive polymers are not good candidates for use in flexible electric devices due to their low or ultralow sensitivity and stretchability. In this paper, the development of transparent, highly stretchable polymer electrodes by a one‐step solution process is reported. The polymer electrodes tolerate extreme strains exceeding 150% and feature an ionic conductivity of 1.4 × 10−4 S cm−1. These metal‐free electrodes also exhibit a high optical transparency of 60%, suggesting that they have great potential for optoelectronic applications. Strain sensors are fabricated by covering the conductive polymer electrodes with polyimide film in a simple, low‐cost, and scalable process. The as‐assembled strain sensors can be used for both stretching and compressing with high sensitivity (a maximum gauge factor of 1049.9), an ultralow limit of detection (0.5% strain), and excellent reliability and stability (&gt;5000 stretching cycles).