Data Acquisition Circuit Research Articles

Fabrication and Application of ZIF-8 Derived In2O3-ZnO Nanocomposites for Ultra-Sensitive NO2 Sensing under UV Irradiation at Room Temperature

Nitrogen oxide (NO2) is common by-products of industrial production, posing significant health risks to workers. Therefore, real-time monitoring of NO2 is crucial. In this study, innovative In2O3-ZnO nano-materials were prepared by combining In2O3 with ZIF-8 via electrospinning, for detecting trace amounts of NO2 at room temperature (RT). Compared to pure In2O3, the In2O3-ZnO nano-materials (V2) with a 10% weight ratio of ZIF-8 exhibited a significantly higher response (389.99) and a faster response time (16.9s) to NO2 under ultraviolet (UV) irradiation at RT. The superior gas sensing performance of the V2 nano-materials is attributed to the formation of n-n heterojunctions, enhanced optical absorption, increased oxygen vacancy ratio, and excellent dispersion among the nano-materials. The results demonstrate that V2 nano-materials can detect NO2 at parts-per-billion (ppb) levels at RT, making them suitable for monitoring trace amounts of NO2 in open environments. Furthermore, a portable real-time NO2 monitoring device was constructed using V2 as the sensing material, an LM358-based amplifier circuit for data acquisition, an STM32F103C8T6 microcontroller as the main control unit, and a buzzer as an alarm device. Compared to devices using a helical Ni-Cr wire as an indirect heat source, this integrated NO2 detection device offers real-time alarms with lower energy consumption. This application not only enhances worker health and safety in industrial environments but also demonstrates higher energy efficiency in practical application.

Thermoelectric energy harvesting associated with heat pipes for monitoring highways weather conditions

This work aims to develop a prototype for autonomously monitoring highway weather conditions using thermoelectric energy. The prototype utilizes solar thermal energy, heat absorbed by the asphalt and soil heat to generate, convert, manage, and store energy. The study investigates the optimal functioning of the thermoelectric generator, including utilizing the soil as a heat sink and incorporating passive thermal control devices like heat pipes. A commercial ultra-low power converter model LTC3108 was experimentally tested for efficient energy conversion. The monitoring system is designed to acquire readings from sensors measuring relevant climate parameters such as temperature, atmospheric pressure, and humidity, focusing on ultra-low power characteristics. The acquired data is transmitted via LoRa technology to a server for processing and analysis. The prototype generated 286.24 J of energy with a maximum temperature gradient of 4.25 ºC in the thermoelectric generator. The energy cost of transmitting a 40-byte message through the LoRaWAN module was 0.625 J. The proposed climate data acquisition circuit had a theoretical consumption of 17.69 J. Experimental tests with the LTC3108 converter, and a 0.22 F supercapacitor demonstrated successful data transmission. This work provides a solid foundation for future studies utilizing thermoelectric energy in highway applications, resulting in a prototype suitable for real-world road scenarios.

A self-heating gas sensor for online monitoring of endogenous ethylene of post-harvest cut chrysanthemums

The decay of post-harvest cut chrysanthemums (PHCCs) during storage and shipment results in enormous loss, and the accumulated endogenous ethylene is one of the main reasons. However, it is challenging for current technologies to onsite monitoring of endogenous ethylene of PHCCs whose concentration is very low. Here, we propose a ethylene sensor with high performances enabled by self-heating capability. Specifically, laser-induced graphene (LIG) patterns are in-situ fabricated on the upper and lower sides of a polyimide substrate. The upper LIG is coated with chemo-resistive SnO2 for ethylene sensing and the lower LIG serves as heater for self-heating. The working temperature is well tuned by the heater and effectively transferred to SnO2. Owing to the self-heating capability, the sensor displays outstanding ethylene detection performances, such as ultra-low limit of detection (1.654 ppb), wide detection range (0.05–100 ppm), high sensitivity (0.2249 ppm−1), high detection linearity (0.9925), and long-term stability (>14 days). Moreover, the sensor is integrated with a data acquisition circuit and connected to a mobile application, realizing online monitoring of endogenous ethylene of PHCCs. The results demonstrate that the decay of PHCCs is accelerated as the endogenous ethylene accumulates. This work would promote the online monitoring of endogenous ethylene of plants.

Low-cost sensor-based damage localization for large-area monitoring of FRP composites

In recent years, there has been growing interest in self-sensing structural materials across research and industry sectors. Detecting and locating structural damage typically requires numerous sensors wired to a data acquisition (DAQ) circuit, rendering implementation impractical in real structures. This paper proposes an innovative, cost-effective sensor network for damage detection and localization in fiber-reinforced polymer composites. The innovation encompasses three key elements: (1) utilizing carbon fiber tows within the composite as piezoresistive sensors, eliminating the need for additional foreign sensor devices; (2) introducing a novel sensor layout wherein sensor tow branches with varied resistance values are connected in parallel, reducing the number of connections to the DAQ circuit and cutting manufacturing costs significantly; (3) developing a practical sensor terminal fabrication technique to minimize manufacturing expenses. The proposed design methodology for the branch resistance values is first validated using a demonstration panel. Subsequently, the overall strategy is assessed by conducting impact tests on carbon and glass fiber-reinforced composite specimens. Results validate the sensor’s ability to accurately detect and locate structural damage.

Design and Realization of Electromagnetic Instrument Data Acquisition Circuit for Landslide Detection

Design and Realization of Electromagnetic Instrument Data Acquisition Circuit for Landslide Detection

A sample-and-hold-based sine wave phase measurement system

In this paper, a new prototype of a Phase Measurement System (PMS) is presented. The PMS uses a Sample & Hold (S&H) circuit-based architecture, and it is capable of performing phase measurements with very low uncertainty over a wide bandwidth. The prototype covers a frequency range from 100 Hz to 100 MHz, and it consists of three main subsystems: (i) a bank of four S&H circuits, (ii) a pulse train signal generator with coarse and fine delay control, and (iii) a data acquisition circuit followed by digital signal processing.The paper describes the method and system-level architecture of the PMS, as well as its capabilities. Experimental results show that the PMS can provide high-accuracy time measurements from high-accuracy amplitude measurements. For a sinewave frequency of 10 MHz, the maximum standard deviation obtained was 0.019°, while for a frequency of 100 MHz, the maximum standard deviation was 0.73°. These results represent a significant improvement compared to the previous PMS prototype and reference measurement instrumentation.

Origami-inspired highly stretchable and breathable 3D wearable sensors for in-situ and online monitoring of plant growth and microclimate

The emerging wearable plant sensors demonstrate the capability of in-situ measurement of physiological and micro-environmental information of plants. However, the stretchability and breathability of current wearable plant sensors are restricted mainly due to their 2D planar structures, which interfere with plant growth and development. Here, origami-inspired 3D wearable sensors have been developed for plant growth and microclimate monitoring. Unlike 2D counterparts, the 3D sensors demonstrate theoretically infinitely high stretchability and breathability derived from the structure rather than the material. They are adjusted to 100% and 111.55 mg cm−2·h−1 in the optimized design. In addition to stretchability and breathability, the structural parameters are also used to control the strain distribution of the 3D sensors to enhance sensitivity and minimize interference. After integrating with corresponding sensing materials, electrodes, data acquisition and transmission circuits, and a mobile App, a miniaturized sensing system is produced with the capability of in-situ and online monitoring of plant elongation and microclimate. As a demonstration, the 3D sensors are worn on pumpkin leaves, which can accurately monitor the leaf elongation and microclimate with negligible hindrance to plant growth. Finally, the effects of the microclimate on the plant growth is resolved by analyzing the monitored data. This study would significantly promote the development of wearable plant sensors and their applications in the fields of plant phenomics, plant-environment interface, and smart agriculture.

Real-time data acquisition inside high-pressure PEM water electrolyzer

This study used the micro-electro-mechanical systems (MEMS) technology to develop a high-pressure resistant flexible 7-in-1 microsensor (voltage, current, humidity, temperature, pressure, flow, and hydrogen). The microsensor is integrated with a flexible printed circuit (FPC) for real-time data acquisition of local voltage, current, humidity, temperature, pressure, flow, and hydrogen variations in different positions inside a high-pressure proton exchange membrane water electrolyzer (PEMWE). The goal of developing such microsensor is to observe the influence of temperature and pressure on the PEMWE. The operational safety of hydrogen is ensured by using a micro hydrogen sensor.

Dry‐Wet Hybrid Direct Printing of Laser‐Induced Graphene and Zinc Oxide Nanoribbons for Continuous‐Flow Manufacturing of Flexible Wearable Photodetectors

AbstractFlexible wearable electronics enable an in situ and real‐time measurement of human physiology and micro‐environment. Although large‐scale production of flexible wearable electronics is demonstrated using direct printing techniques, the “wet” nature of these techniques requires multiple procedures and chemicals to prepare printable inks, increasing the complexity and cost. Here, a dry‐wet hybrid direct printing is developed for the mass production of flexible wearable photodetectors, in which a “dry” direct laser writing and a “wet” screen printing are employed to fabricate laser‐induced graphene as electrode layer and zinc oxide as photosensitive layer, respectively. The liquid‐free fabrication of LIG significantly reduces the complexity and cost of the production. An automatic conveyor belt is designed to realize continuous‐flow manufacturing. The photodetectors demonstrate good ultraviolet (UV) photodetection performances, such as a photo‐to‐dark current ratio (Iphoto/Idark) of 5.67 × 105, approaching the record of similar devices. The manufacturing system presents a high reproducibility, considering that Iphoto/Idark only fluctuates within 7.10%. The flexible photodetectors are worn as wristbands after being integrated with a data acquisition and transmission circuit. UV intensity is real‐time monitored on a self‐developed mobile application. The continuous‐flow manufacturing based on the developed dry‐wet hybrid direct printing sheds light on the mass production of flexible wearable electronics.

Non-Contact Current Measurement for Three-Phase Rectangular Busbars Using TMR Sensors.

This paper proposes a non-contact current measurement method for three-phase rectangular busbars based on TMR (tunneling magneto-resistance) sensors, due to their advantages of large dynamic range, wide bandwidth, light weight, and easy installation. A non-contact current sensor composed of only three TMR sensors is developed and the TMR sensors are respectively placed at a location with a certain distance from the surface of each rectangular busbar to measure the magnetic fields generated by the busbar currents. To calibrate the developed current sensor, i.e., to establish the relationship between the magnetic fields measured by the TMR sensors and the currents flowing in the three-phase rectangular busbars, we designed a thyristor-controlled resistive load as a calibrator, which is connected to a downstream branch of the distribution cabinet. By switching the resistive load, a calibration current, which can be identified from the background current, is generated in one rectangular busbar and its value is measured at the location of the calibrator, and transmitted wirelessly to the location of the TMR sensors. A new and robust method is proposed to extract the voltage components, corresponding to the calibration current, from the voltage waveforms of the TMR sensors. By calculating the proportional coefficients between the calibration currents and the extracted voltage components, online calibration of the current sensor is achieved. We designed and implemented a current measurement system consisting of a current sensor using TMR sensors, a thyristor-controlled resistive load for current sensor calibration, and a data acquisition circuit based on a multi-channel analog-to-digital converter (ADC). Current measurement experiments were performed in a practical distribution cabinet installed in our laboratory. Compared to the measurement results using a commercial current probe with an accuracy of 1%, the relative error of the measured currents in RMS is less than 2.5% and the phase error is less than 1°, while the nonlinearity error of the current sensor is better than 0.8%.

Assessment of the TEROS 10 and TEROS 12 sensors in soil moisture measurement

This study focuses on investigating the accuracy of the empirical equations proposed by the manufacturing company for the widely used TEROS 10 and TEROS 12 sensors. Specifically, the study examines whether the raw - unprocessed - measurements provided by the two sensors lead to reliable predictions of soil moisture and electrical conductivity values when these particular empirical equations are utilized. For this purpose, a prototype setup was developed, incorporating a lowcost microcontroller along with auxiliary power supply and data acquisition circuits for the sensors. The results highlight the need for specific calibration of the sensors for each soil type and salinity level. Additionally, the behaviour of the sensors operating at low frequency (70 MHz) under increasing salinity conditions is contrary to expectations.

A dual-mode fiber-shaped flexible capacitive strain sensor fabricated by direct ink writing technology for wearable and implantable health monitoring applications

Flexible fiber-shaped strain sensors show tremendous potential in wearable health monitoring and human‒machine interactions due to their compatibility with everyday clothing. However, the conductive and sensitive materials generated by traditional manufacturing methods to fabricate fiber-shaped strain sensors, including sequential coating and solution extrusion, exhibit limited stretchability, resulting in a limited stretch range and potential interface delamination. To address this issue, we fabricate a fiber-shaped flexible capacitive strain sensor (FSFCSS) by direct ink writing technology. Through this technology, we print parallel helical Ag electrodes on the surface of TPU tube fibers and encapsulate them with a high dielectric material BTO@Ecoflex, endowing FSFCSS with excellent dual-mode sensing performance. The FSFCSS can sense dual-model strain, namely, axial tensile strain and radial expansion strain. For axial tensile strain sensing, FSFCSS exhibits a wide detection range of 178%, a significant sensitivity of 0.924, a low detection limit of 0.6%, a low hysteresis coefficient of 1.44%, and outstanding mechanical stability. For radial expansion strain sensing, FSFCSS demonstrates a sensitivity of 0.00086 mmHg−1 and exhibits excellent responsiveness to static and dynamic expansion strain. Furthermore, FSFCSS was combined with a portable data acquisition circuit board for the acquisition of physiological signals and human‒machine interaction in a wearable wireless sensing system. To measure blood pressure and heart rate, FSFCSS was combined with a printed RF coil in series to fabricate a wireless hemodynamic sensor. This work enables simultaneous application in wearable and implantable health monitoring, thereby advancing the development of smart textiles.

On-Line Partial Discharge Monitoring System for Switchgears Based on the Detection of UHF Signals

Aiming at the phenomenon of partial discharge caused by the insulation fault of switchgears, an ultra-high frequency (UHF) partial discharge online monitoring system based on the Internet of Thing (IoT) is designed. The hardware of the system mainly consists of UHF sensors, signal conditioning circuits, and data acquisition circuits to realize the monitoring of the discharge signal. The monitoring data is uploaded to the cloud platform through the 4G DTU module, and the host computer software based on B/S architecture is designed on the server side, which can monitor the operation status of the switchgear anytime and anywhere. The experimental results show that the detection system is stable and reliable and can meet practical needs.

Flexible optical tactile sensor based on a liquid-membrane lens structure.

Based on the liquid lens focus mechanism, a novel, to the best of our knowledge, optical tactile sensor is designed by taking advantage of the structure simplicity, fast response, and environmental immunity. The design of the tactile sensing mechanism used the liquid-membrane lens structure. To integrate the tactile sensing system, we designed a data acquisition circuit unit. A performance test platform was built, and performance testing and two application demonstrations were conducted. The experiment's result showed that the linear fitting degree was greater than 0.988, the load response time was 0.078s, the target mass was accurately measured, the maximum error was less than 0.02N, and the fine adjustment of the LED light intensity was achieved.

The Influence Mechanism and Improvement Strategy of Multiplexer on Measurement Error of the 2-D Resistive Sensor Array Data Acquisition Circuit

The Influence Mechanism and Improvement Strategy of Multiplexer on Measurement Error of the 2-D Resistive Sensor Array Data Acquisition Circuit

Robust and Flexible Sliding Tactile Sensor for Surface Pattern Perception and Recognition

Perceiving surface characteristics through tactile interaction typically requires high‐resolution devices or precise spatial scanning to record and analyze a significant amount of information. However, most available tactile sensors require complicated technological processes, redundant layouts, and data acquisition circuits, which limits their ability to provide a real‐time static perception and feedback for potential applications such as robotic manipulation. Drawing inspiration from the sliding tactile (ST) perception mode of the human fingertip, a robust and flexible ST sensor with a low array density of 2.7 cells cm−2 is reported. This innovative sensor has a soft and cambered configuration that allows it to rapidly and accurately recognize the 3D surface features of objects, including grooves as small as 500 μm. Benefiting from the strong correlation between collected electronic responding and local deformation of sensing cell, the ST sensor can adaptively reconstruct surface patterns with the assistance of deep learning, even on unstructured objects. The pattern recognition system based on the robot is demonstrated by accurately classifying a set of mahjong tiles with nearly 100% accuracy, surpassing human tactile perception capabilities in the same task.

Experimental validation of a wireless monitored solar still for efficient olive pomace drying and distilled water production

This work presents the prototype of a solar still that can be used as a complement to the traditional fossil fuel-based drying process of olive pomace, a thick sludge with a high moisture content that is massively by-produced in the olive oil industry. In addition, the system allows to recover distilled water, which can be used to irrigate the adjacent fields. The feasibility of the system for the target application was experimentally validated by designing a wireless data acquisition circuit for data collection, remote storage, visualization and analysis in real-time, with access possible from multiple devices. The results from a test campaign revealed that the moisture content of the olive pomace was effectively reduced from 67.17% to 39.90% in a 10-day period. A maximum drying efficiency of 16.64% was achieved, with potential for higher values under favorable weather conditions. The simplicity of the design and the low-cost solution can facilitate the future large-scale implementation of a similar system.

Development of a Virtual Environment-Based Electrooculogram Control System for Safe Electric Wheelchair Mobility for Individuals with Severe Physical Disabilities

Conventional wheelchairs are predominantly manual or joystick-operated electric wheelchairs. However, operating these wheelchairs can be difficult or impossible for individuals with severe physical disabilities. Due to losing control of their physical limbs, they depend on an attendant for assistance. As a remedy, bio-signals may be used as a control mechanism since they are readily available and can be acquired from any body part. This research proposes to use EOG signals to vail a control mechanism and test it in a virtual and actual electric wheelchair. The main contribution of the study is an investigation of the use of EOG to control an electric wheelchair in a virtual environment to determine safe control parameters for wheelchair use in complex environments. A customized data acquisition circuit was developed to acquire single-channel EOG signals using wet electrodes. The acquired signal was filtered and processed using feature extraction and classification techniques in MATLAB software. Two customized control environments were developed in Unity 3D, one with equally partitioned sections and the other with sections decreasing in size as the robot wheelchair approaches the target. Twenty-two test subjects (mean age 24.5, std 1.5) participated in the study, controlling the robot wheelchair in real-time with non or least instances of collision and oversteering. The system achieved an accuracy of 96.5% with a response time of 0.7s, translating to an ITR of 70.6 bits/min. Overall, the participants managed to navigate the virtual environment with a completion time of 101.94s ± 19.71 and 109.07s ± 13.25 for the male and female participants, respectively. In the scene with decreasing section sizes, 72% and 54% instances of collision and oversteering were reported, respectively, highlighting the need to consider the complexity of the control environment and the sufficiency of the participants' control skills to ensure safety in operations. The results confirm the usefulness of EOG as a control interface, with little or no need for recalibration. It provides a promising avenue for individuals with severe physical disabilities to operate wheelchairs independently in complex environments, enhancing their quality of life.

Data Glove with Integrated Polyethylene‐Carbon Composite‐Based Strain Sensor for Virtual Reality Applications

AbstractA data glove enables fine motion control in virtual reality (VR). This work presents a cost‐effective data glove made of a commercial nylon‐based glove with integrated polyethylene‐carbon composites (Velostat). The resistance of the Velostat varies when a finger is bent. This piezoresistive behavior was explored by designing the Velostat as the strain sensor. The strain sensor was characterized for its flexure sensing by connecting it to a data acquisition circuit. The circuit is designed to process the output of the joint angles and feed it to the computer. A linear resistance output was measured with a sensitivity/gauge factor of 1.45 % per degree with a response time of 0.0158 seconds when the strain sensor bends from 0° to 30°. To control the 3D virtual hand's movement, the data glove was coupled with two inertial measurement unit sensors at the forearm and upper arm to identify its coordinates. The fabricated data glove successfully performs a proof‐of‐concept by picking‐and‐placing multiple objects in a VR environment.

E-Nose System Based on Fourier Series for Gases Identification and Concentration Estimation From Food Spoilage

This work presents an electronic nose (EN)-based gas identification and concentration estimation method for the detection of food spoilage. The response data of sensors were acquired through a commercial gas sensor array and data acquisition circuit board and transformed into pictures with the form of the Fourier series. A convolutional neural network (CNN) model was used to identify the pictures from the conversion of sensor data, thus achieving the purpose of identifying the gases (C2H5OH, NH3, and H2S). In order to solve the problem of sample imbalance and to improve the generalization performance of classification models, the synthetic minority oversampling technique (SMOTE) and dropout technique were employed. Fivefold cross-validation was used to evaluate the performance of the model, of which the gas identification accuracy rate reached 96.67%. Moreover, a gas concentration regression model with the advantages of simplicity and strong interpretability was further proposed to estimate the concentrations of C2H5OH, NH3, and H2S. The mean absolute errors and coefficients of determination for the concentration estimation of C2H5OH, NH3, and H2S are (3.71 ppm, 0.968), (0.50 ppm, 0.968), and (0.13 ppm, 0.99), respectively. Furthermore, we used our model to evaluate the freshness of kiwifruit, pork, and beef, and it showed satisfactory predictive performance. The method proposed in this work realizes high-precision detection of gases from food spoilage and has a good application prospect in the rapid judgment of food freshness on the EN system.