Precise Sensor Research Articles

Analysis of soil cohesion by fluidized bed methodology using integrable differential pressure sensors for a wide range of soil textures

Measuring cohesion (Co) as a simple and reliable factor with the fluidized bed approach to assess the inherent resistance of soils against destructive forces corresponding to the separation of particles from the soil mass is considered a promising research area in place of alternative methods by rainfall–runoff experiments. However, the approach has only been tested for very limited soil types, and there is a need to analyze its suitability for more diverse soil conditions, especially for cohesive soils having higher clay, organic matter, or lime contents. This study aimed to evaluate cohesion for twenty soil types representing nine different texture classes that differed significantly in terms of their intrinsic properties with an “Automated Soil Cohesion Measurement Apparatus”. This device was equipped with modern electronic sensor technologies designed to function and measure cohesion with the fluidized-bed approach. In the measurements, pressure drops that occur while the water pressure increases gradually as it passes through the soil mass are visually and electronically monitored and continuously recorded during the experiments with the help of precise differential pressure and weight sensors. Effects of the changes in intrinsic soil properties such as particle sizes, organic matter contents, and lime contents in terms of coagulation potentials on cohesive forces were observed with the designed apparatus. Related to that, the analysis of variance and the Fisher’s least significant difference tests indicated that the cohesion (Co) and the flow velocity at fluidization (Vf) values were significantly different by soil type (p < 0.05). Fraction of the fine silt-sized particles (FNSI) was highly correlated with Co and Vf, and explained much of the variance for the cohesive conditions. In addition, the Co values in coarse-textured soil types with low cementing components and soils having greater sand contents were four times lower than those of heavy textured and clay-bound soils. The approach and the designed apparatus successfully simulated changes in internal soil conditions in terms of measured Co and Vf values.

USE OF LV MEASUREMENTS IN ORDER TO FEED A STATE ESTIMATOR AIMING AT EVALUATING THE MV VOLTAGE WITH A 1% PRECISION

With the development of DER across the world and particularly in Medium Voltage networks, more and more Smart Grid functions are deployed within the utilities. To tackle the Voltage management challenge due to DER, Enedis, the French DSO, is currently using real time Advanced Grid Functions, to monitor and control in real time (e.g., primary substation voltage regulation) a growing part of the MV network. In order to foster a broader and faster deployment of these functions, their costs must be contained and their installation imply the less network outage as possible. This paper presents an alternative solution to the fuelling of a MV state estimator with classical MV high precision sensors by using LV measurements instead, still keeping the final estimation under a 1% accuracy. It depicts the theoretical study and a real world test proving the efficiency of this new way of feeding a MV state estimator, at lower cost.

A synchronous demodulation technology based on sample-and-hold for eddy current sensors

This paper proposes a synchronous demodulation technology based on sample-and-hold which shows significant advantages in the application of precision sensors. The traditional synchronous demodulation methods are discussed, and then the working principle of the proposed method is theoretically analyzed in detail. It is found that the proposed method can not only effectively suppress the harmonic components caused by the signal source but is also beneficial to improving the dynamic range of precision sensors. The eddy current sensor is adopted as an example of precision sensors, and a high-precision eddy current displacement sensor prototype was designed and tested. The results show that with the proposed method, the harmonics in the output signal are suppressed more effectively, and the demodulation circuit is relatively simplified. This synchronous demodulation method has an extensive application prospect in precision sensors.

Highly precise measurement of atmospheric N2O and CO using improved White cell and RF current perturbation

A highly precise dual gas sensor for measurement of atmospheric nitrous oxide (N2O) and carbon monoxide (CO) was developed and evaluated. A room temperature interband cascade laser emitting at 4.54 μm was used as a laser source to cover the absorption lines of N2O and CO simultaneously. Sensitivity and precision were enhanced by using an improved White cell with 76 m effective optical path length and radio frequency noise perturbation technique to reduce optical interference noise. A method was proposed to correct the laser frequency by calculating the correlation coefficient between the absorption signal with the reference signal, which effectively reduced the long-term drift of the absorption line center to less than 4 × 10−5 cm−1. By further precisely control the temperature and pressure of the absorption cell, a continuous 24 h measurement precision of 65 ppt N2O and 133 ppt CO at 0.1 Hz was demonstrated, with a daily drift less than 1.5 ppt. Finally, the repeatability and reliability of the sensor system were validated by real atmospheric measurements for two consecutive days.

Influence of Recharging Wells, Sanitary Collectors and Rain Drainage on Increase Temperature in Pumping Wells on the Groundwater Heat Pump System.

The utilization of groundwater is becoming increasingly popular for heating and cooling buildings, as well as to regulate the temperature needs of industrial processes. Groundwater has excellent energy potential from various factors, of which environmental acceptability stands out, as groundwater is considered a source of renewable energy. Due to the water table depth below the surface, atmospheric conditions have a negligible effect on the temperature of groundwater, resulting only in minor annual temperature variations, thus also making groundwater a source of reliable renewable energy. This paper presents some aspects of the groundwater heat pump (GWHP) system’s design and addresses a particular problem on the influence of recharge temperature field as well as local utility lines on the pumping well water temperature. An example is given of a system designed for a production hall in the northern part of Croatia. Geological and hydrogeological conditions at the site are highly favourable regarding the groundwater temperature and aquifer parameters. For the needs of this research, precise electronic sensors with data loggers were installed inside the wells. Probe type GSR 120 NT manufactured by Eltratec, Slovenia, is capable of monitoring level, temperature, and electrical conductivity, including telemetric data transfer to the remote server. Mapping the obtained data revealed significant temperature breakthroughs from the recharge wells, as well as local temperature field deviation near the sanitary and precipitation drainage collectors. Utility installation seepage influence was differentiated by the increase in groundwater electrical conductivity measured at the pumping wells. Results show that not only distance between the wells, as the main parameter that affects the system, but also industrial utility lines can have an influence on thermal field breakthrough.

An Efficient Surface Map Creation and Tracking Using Smartphone Sensors and Crowdsourcing.

Like Smart Home and Smart Devices, Smart Navigation has become necessary to travel through the congestion of the structure of either building or in the wild. The advancement in smartphone technology and incorporation of many different precise sensors have made the smartphone a unique choice for developing practical navigation applications. Many have taken the initiative to address this by developing mobile-based solutions. Here, a cloud-based intelligent traveler assistant is proposed that exploits user-generated position and elevation data collected from ubiquitous smartphone devices equipped with Accelerometer, Gyroscope, Magnetometer, and GPS (Global Positioning System) sensors. The data can be collected by the pedestrians and the drivers, and are then automatically put into topological information. The platform and associated innovative application allow travelers to create a map of a route or an infrastructure with ease and to share the information for others to follow. The cloud-based solution that does not cost travelers anything allows them to create, access, and follow any maps online and offline. The proposed solution consumes little battery power and can be used with lowly configured resources. The ability to create unknown, unreached, or unrecognized rural/urban road maps, building structures, and the wild map with the help of volunteer traveler-generated data and to share these data with the greater community makes the presented solution unique and valuable. The proposed crowdsourcing method of knowing the unknown would be an excellent support for travelers.

82 Application of Precision Sensor Technologies, Real-time Data Analytics, and Dynamic Models on Extensive Western Rangeland Grazing Systems

Abstract Approximately 40% of the land use within the Northern Great Plains is dedicated to livestock production, with much of the 89.9 million head of cattle and calves in the U.S. concentrated in this area. Precision livestock management has ushered in a new era of sensors and technology to monitor individual animal’s health, reproductive, and nutritional status in real-time to improve efficiency. Despite these advances, most of the research has been conducted on dairy operations or within feedlot settings. Incorporation on extensive rangeland production systems remains relatively absent (Brennan et al., 2021). This is primarily due to difficulties in studying animals on rangelands caused by heterogeneity of forage resources, variable environmental conditions, and challenges associated with accessing information across vast distances, often without cellular or internet connection. Advances in communication technology are increasingly connecting remote areas, creating new opportunities to improve livestock production efficiency on extensive rangelands using precision technology. Numerous challenges still exist, including applying and integrating multiple technologies across platforms, effectiveness in a real-world setting, technical skills, and knowledge to utilize real-time data, and achieving economic return for livestock producers. Specifically, we discuss the application of precision technologies and mathematical models for improving ruminant nutrition in rangeland systems (Menendez and Tedeschi, 2020). Opportunities exist to refine or develop the next generation of equations/models that more adequately represent nutrient dynamics such as diet selection, supplementation, movement, behavior, water intake, feed conversion efficiency, heat/cold stress, and gain on an individual animal basis. However, effective adoption and adaptability of new technologies/data analytics merit the consideration of potential intended-and-unintended consequences, such as producer dependency on complex hardware and software systems. Hence, precision capabilities coupled with mathematical models are likely the next step to substantially enhance livestock performance in extensive systems when coupled with feasible and reliable long-term strategies.

Theoretical study of the close-loop atomic magnetometer with a transverse pumping feedback

Atomic magnetometer is a high precision sensor for measuring magnetic fields. We demonstrate a novel way to control the spin polarization of atomic magnetometer in close-loop. The -axis polarization rate is kept to zero by feeding back the circular polarization of a transverse light which is a circularly polarized laser from transverse direction. The electron polarization on -axis responding to the magnetic field is simulated, and the result shows that can be kept to zero in the close-loop mode. Through a modulated magnetic field, the and magnetic field can be demodulated in X-0 and X-1 modes from the transverse light with a pumping rate of .

Experimental use of mobile apps in physics education

Mobile devices have nowadays become familiar instruments of our daily lives. Due to the presence of more and more sophisticated and precise environmental sensors and to the development of more and more user-friendly APPs able to read and analyse data, the interest in the educational context of smartphones, the number of proposals and their quality have rapidly increased in the last years. Our research group in physics education promoted various activities in which students, in the role of “active researchers”, tested some of the available APPs and used them to perform qualitative and quantitative experiments with the aim to improve learning. Here we suggest some significant experimental activity that our partners-student performed with his/her smartphone and low-cost equipment on sound, acceleration, optics and spectroscopy.

In-Situ Compensation on Temperature Coefficient of the Scale Factor for a Single-Axis Nano-g Force-Balance MEMS Accelerometer

The reduction of temperature effect is vitally important for high precision sensors. This paper introduces the theoretical analysis and experimental verification of an in-situ compensation method on the temperature coefficient of the scale factor for a single-axis electromagnetic force-balance feedback MEMS accelerometer. A micro thermistor, fabricated together with the MEMS accelerometer, is integrated to in-situ sense the temperature variation of the accelerometer. The thermistor is connected to the voltage-to-current resistance in series, which compensates the variation of the scale factor of the accelerometer that is influenced by temperature variation. The experimental results reveal that the temperature coefficient of the scale factor of the compensated accelerometer is within 6 ppm/°C for the temperature range from 25°C to 50°C, which is reduced by 68 times compared with the uncompensated accelerometer. Benefiting from the compatible fabrication process and the in-situ compensation, the proposed method is promising to be low-cost and high-efficiency.

Precise Microfluidic Luminescent Sensor Platform with Controlled Injection System.

Efforts have been devoted to screening various prevalent diseases, such as severe acute respiratory syndrome (SARS) and coronavirus disease 2019 (COVID-19). Real-time polymerase chain reaction (RT-PCR), which is currently the most widely used, has high accuracy, but it requires several facilities and takes a relatively long time to check; so, new testing technology is necessary for a higher test efficiency. A chemiluminescence (CL) sensor is a relatively simple device and suitable as an alternative because it can detect very precise specimens. However, in measurements via CL, the quantitative formulation of reagents that cause color development is important. In the case of mixing using micropipettes, precise analysis is possible, but this technique is limited by uncontrollable errors or deviations in detection amounts. In addition, in using a microfluidic chip to increase field applicability, a syringe pump or other quantification injection tools are required, so problems must be overcome for practical use. Therefore, in this study, a microchip was designed and manufactured to supply a sample of a certain volume by simply blowing air and injecting a sample into the chamber. By utilizing the luminescence reaction of luminol, CuSO4 and H2O2 the performance of the prepared chip was confirmed, and the desired amount of the sample could be injected with a simple device with an error rate of 2% or less. For feasible applications, an experiment was performed to quantitatively analyze thrombin, a biomarker of heart disease. Results demonstrated that biomarkers could be more precisely detected using the proposed microchips than using micropipettes.

Highly precise in-plane displacement sensor based on an asymmetric fiber Fabry-Perot interferometer.

An in-plane displacement sensor based on an asymmetric extrinsic fiber Fabry-Perot interferometer (EFPI) is proposed and demonstrated. The asymmetric EFPI composed of a step-shaped external reflector and a cleaved fiber end face can be equivalent to two parallel FPIs with slightly different cavity lengths. By calculating the peak intensity difference of the two FPIs, the in-plane displacement can be demodulated with enhanced sensitivity and suppressed common mode noise. Both theoretical analyses and experimental results show that the sensitivity and the linear range of the in-plane displacement sensor are dependent on the cavity length. A displacement resolution of 5 nm and a linear range of ±7µm under the cavity length of 250 µm are achieved in the experiment. The proposed in-plane displacement sensor with a nanometric resolution and compact size can be widely used in the fields of metrology, accelerometers, and semiconductor manufacture.

Review of 3D-printing technologies for wearable and implantable bio-integrated sensors.

Thin-film microfabrication-based bio-integrated sensors are widely used for a broad range of applications that require continuous measurements of biophysical and biochemical signals from the human body. Typically, they are fabricated using standard photolithography and etching techniques. This traditional method is capable of producing a precise, thin, and flexible bio-integrated sensor system. However, it has several drawbacks, such as the fact that it can only be used to fabricate sensors on a planar surface, it is highly complex requiring specialized high-end facilities and equipment, and it mostly allows only 2D features to be fabricated. Therefore, developing bio-integrated sensors via 3D-printing technology has attracted particular interest. 3D-printing technology offers the possibility to develop sensors on nonplanar substrates, which is beneficial for noninvasive bio-signal sensing, and to directly print on complex 3D nonplanar organ structures. Moreover, this technology introduces a highly flexible and precisely controlled printing process to realize patient-specific sensor systems for ultimate personalized medicine, with the potential of rapid prototyping and mass customization. This review summarizes the latest advancements in 3D-printed bio-integrated systems, including 3D-printing methods and employed printing materials. Furthermore, two widely used 3D-printing techniques are discussed, namely, ex-situ and in-situ fabrication techniques, which can be utilized in different types of applications, including wearable and smart-implantable biosensor systems.

Cutting force analysis of oak for the development of a cutting force model

ABSTRACT The cutting process of oak (Quercus robur) was investigated by means of a novel testing approach. A unique testing device, enabling nearly linear stand-alone cuts, was used. The specimens climatized to 6 different moisture content levels were machined within cutting velocities ranging from 5 to 80 m·s−1, at 5 cutting fibre angles from along to across the grain, and at different uncut chip thicknesses of up to 0.5 mm. The precise quartz sensor utilized for observing cutting forces enabled insights into the cutting mechanism involved while wood disintegration. Cutting velocity evolved as a key process parameter strongly influencing cutting force. Evaluation of uncut chip thickness showed a regression that was strongly influenced by particular force components. The friction force generated by “ploughing” the surface was relevant when cutting thin chips. In contrast, the part of force introduced by chip formation affected the process weightily in the case of cutting a thick chip. When cutting parallel to the grain lower forces were observed than cutting perpendicular to grain orientation. Obtained data supported the mathematical force prediction model establishment involving several parameters (e.g. cutting velocity, cutting fibre angle, uncut chip thickness, and moisture content).

Advances in space quantum communications

Concerted efforts are underway to establish an infrastructure for a global quantum Internet to realise a spectrum of quantum technologies. This will enable more precise sensors, secure communications, and faster data processing. Quantum communications are a front-runner with quantum networks already implemented in several metropolitan areas. A number of recent proposals have modelled the use of space segments to overcome range limitations of purely terrestrial networks. Rapid progress in the design of quantum devices have enabled their deployment in space for in-orbit demonstrations. We review developments in this emerging area of space-based quantum technologies and provide a roadmap of key milestones towards a complete, global quantum networked landscape. Small satellites hold increasing promise to provide a cost effective coverage required to realise the quantum Internet. The state of art in small satellite missions is reviewed and the most current in-field demonstrations of quantum cryptography are collated. The important challenges in space quantum technologies that must be overcome and recent efforts to mitigate their effects are summarised. A perspective on future developments that would improve the performance of space quantum communications is included. The authors conclude with a discussion on fundamental physics experiments that could take advantage of a global, space-based quantum network.

Fast error calibration of Flexible Measuring Arm based on an adaptive Genetic Algorithm

With the development of measurement technology, the Flexible Measuring Arm (FMA) is widely used in quality test of automobile processing and industrial production. FMA is a kind of nonlinear system with many parameters. Low cost and efficient calibration method have become the focuses of attention. This article presents a fast calibration method for FMA based on an adaptive Genetic Algorithm (GA) just with several standard balls and a ball plate. It can greatly reduce the calibration cost than common external calibration method which needs high precision instruments and sensors. Firstly, the kinematic model of FMA is established by RPY theory. Secondly, the common GA is optimized and improved, and an adaptive mechanism is added to the algorithms which can realize the automatic adjustment of crossover and mutation operators. A Normalized Genetic Algorithm (NGA) with adaptive mechanism is proposed to complete the optimization calculation. It can improve the numbers of optimal individuals and the convergence speed. So, the search efficiency will be enhanced greatly. Finally, the Least square method (LSM), the General Genetic Algorithm (GGA), and the proposed NGA are respectively used to finish the calibration work. The compensation accuracy and the search efficiency with the above three different algorithms have been systematically analyzed. Experiment indicates that the performance of NGA is much better than LSM and GGA. The data also has proved that the LSM is suitable to complete optimization calculation for linear system. Its convergence stability is much poorer than NGA and GGA because of the ill-condition Jacobin matrix. GGA is easy to fall into local optimization because of the fixed operators. The proposed NGA obviously owns fast convergence speed, high accuracy and better stability than GGA. The position error is reduced from 3.17 to 0.5 mm after compensation with the proposed NGA. Its convergence rate is almost two time of GGA which applies constant genetic factors. The effectiveness and feasibility of proposed method are verified by experiment.

ADESIT

Thanks to the numerous machine learning tools available to us nowadays, it is easier than ever to derive a model from a dataset in the frame of a supervised learning problem. However, when this model behaves poorly compared with an expected performance, the underlying question of the existence of such a model is often underlooked and one might just be tempted to try different parameters or just choose another model architecture. This is why the quality of the learning examples should be considered as early as possible as it acts as a go/no go signal for the following potentially costly learning process. With ADESIT, we provide a way to evaluate the ability of a dataset to perform well for a given supervised learning problem through statistics and visual exploration. Notably, we base our work on recent studies proposing the use of functional dependencies and specifically counterexample analysis to provide dataset cleanliness statistics but also a theoretical upper bound on the prediction accuracy directly linked to the problem settings (measurement uncertainty, expected generalization...). In brief, ADESIT is intended to be part of an iterative data refinement process right after data selection and right before the machine learning process itself. With further analysis for a given problem, the user can characterize, clean and export dynamically selected subsets, allowing to better understand what regions of the data could be refined and where the data precision must be improved by using, for example, new or more precise sensors.

ANALYSIS OF GEOMETRIC AND ORTHOGONAL CORRECTION ACCURACY FOR CAS-500 SATELLITE IMAGES

Abstract. This paper reports on geolocation accuracy of image products generated from Precision Image Processing (PIP) system developed for CAS-500 Satellite images. CAS-500, launched on 22 March, 2021, will be used mainly for land monitoring and 1:5000 scale mapping over the Korean Peninsula. For this purpose, ground control points (GCPs) and a Digital Terrain Model (DTM) have been collected over the Peninsula and integrated into the PIP for the generation of precision image product in an automated manner. The goal of this paper is to analyze the geolocation accuracy of image products generated from the PIP. Target geolocation accuracy of the PIP was set as 2 pixel RMSE using the internal GCP DB and DTM. Since CAS-500 images were not distributed yet, the analysis was performed using 13 KOMPSAT-3A satellite images, having similar specifications to CAS-500. The result showed that the accuracy of precise sensor models were about 1.797 pixels in South Korea and 1.907 pixels in North Korea. The accuracy of orthoimages were about 1.24 meters in South Korea and 1.59 meters in North Korea. Overall, the geolocation over North Korea was not as good as that over South Korea. It was judged that the quality of GCPs and DTM over North Korea affected the geolocation accuracy and, however, the accuracy gap was not too severe. The PIP system should produce image products within the targeted geolocation accuracy when CAS-500 delivers high resolution images over the Korean Peninsula.

Signal Expansion Method in Indoor FMCW Radar Systems for Improving Range Resolution.

As various unmanned autonomous driving technologies such as autonomous vehicles and autonomous driving drones are being developed, research on FMCW radar, a sensor related to these technologies, is actively being conducted. The range resolution, which is a parameter for accurately detecting an object in the FMCW radar system, depends on the modulation bandwidth. Expensive radars have a large modulation bandwidth, use the band above 77 GHz, and are mainly used as in-vehicle radar sensors. However, these high-performance radars have the disadvantage of being expensive and burdensome for use in areas that require precise sensors, such as indoor environment motion detection and autonomous drones. In this paper, the range resolution is improved beyond the limited modulation bandwidth by extending the beat frequency signal in the time domain through the proposed Adaptive Mirror Padding and Phase Correction Padding. The proposed algorithm has similar performance in the existing Zero Padding, Mirror Padding, and Range RMSE, but improved results were confirmed through the indicating the size of the side lobe compared to the main lobe and the accurate detection rate of the OS CFAR. In the case of , it was confirmed that with single targets, Adaptive Mirror Padding was improved by about 3 times and Phase Correct Padding was improved by about 6 times compared to the existing algorithm. The results of the OS CFAR were divided into single targets and multiple targets to confirm the performance. In single targets, Adaptive Mirror Padding improved by about 10% and Phase Correct Padding by about 20% compared to the existing algorithm. In multiple targets, Phase Correct Padding improved by about 20% compared to the existing algorithm. The proposed algorithm was verified through the MATLAB Tool and the actual FMCW radar. As the results were similar in the two experimental environments, it was verified that the algorithm works in real radar as well.

Antennas as Precise Sensors for GNSS Reference Stations and High-Performance PNT Applications on Earth and in Space.

Satellite navigation is more and more important in a plethora of very different application fields, ranging from bank transactions to shipping, from autonomous driving to aerial applications, such as commercial avionics as well as unmanned aerial vehicles (UAVs). In very precise positioning, navigation, and timing (PNT) applications, such as in reference stations and precise timing stations, it is important to characterize all errors present in the system in order to account possibly for them or calibrate them out. Antennas play an important role in this respect: they are indeed the “sensor” that capture the signal in space from global navigation satellite systems (GNSS) and thereby strongly contribute to the overall achievable performance. This paper reviews the currently available antenna technologies, targeting specifically reference stations as well as precise GNSS antennas for space applications, and, after introducing performance indicators, summarizes the currently achievable performance. Finally, open research issues are identified, and possible approaches to solve them are discussed.