Search Results (2,405)

In this article, the authors developed a novel method for the moisture mapping of the soil surface of agrophytocenosis using a neural network based on synchronized radar and multispectral optoelectronic data from Sentinel-1,2. The significance of this research lies in its potential to enhance precision farming practices, which are increasingly vital in addressing global agricultural challenges such as water scarcity and the need for sustainable resource management. To verify the developed method, data from two experimental plots were utilized. These plots were located on irrigated soybean crops, with the first plot situated on the right bank (plot No. 1) and the second on the left bank (plot No. 2) of the lower Volga River. Two experimental soil moisture geodatasets were created through measurements and geo-referencing points using the gravimetric method (for plot No. 1) and the proximal sensing method (for plot No. 2) employing the Soil Moisture Sensor ML3-KIT (THETAKIT, Delta). The soil moisture retrieval algorithm was based on the use of a neural network to predict the reflection coefficient of an electro-magnetic wave from the soil surface, followed by inversion into soil moisture using a dielectric model that takes into account the soil texture. The input parameter of the neural network was the ratio of the microwave radar vegetation index (calculated based on Sentinel-1 data) to the index (calculated based on the data of multispectral optoelectronic channels 8 and 11 of Sentinel-2). The retrieved soil moisture values were compared with in situ measurements, showing a determination coefficient of 0.44–0.65 and a standard deviation of 2.4–4.2% for plot No. 1 and similar metrics for plot No. 2. The conducted research laid the groundwork for developing a new technology for remote sensing of soil moisture content in agrophytocenosis, serving as a crucial component of precision farming systems and agroecology. The integration of this technology promotes sustainable agricultural practices by minimizing water consumption while maximizing crop productivity. This aligns with broader environmental goals of conserving natural resources and reducing agricultural runoff. On a larger scale, data derived from such studies can inform policy decisions related to water resource management, guiding regulations that promote efficient water use in agriculture. Full article

In the past few decades, there has been a notable technological advancement in geophysical sensors. In the case of magnetometry, several sensors were used, having the common feature of being miniaturized and lightweight, thus idoneous to be carried by UAVs in drone-borne magnetometric surveys. A common feature is that their sensitivity ranges from 0.1 to about 200 nT, thus not comparable to that of optically pumped, standard fluxgate or even proton magnetometers. However, their low cost, volume and weight remain very interesting features of these sensors. In fact, such sensors have the common feature of being very inexpensive, so new ways of making surveys using many of these sensors could be devised, in addition to the possibility, even with limited resources, of creating gradiometers by combining two or more of them. In this paper, we explore the range of applicability of small tri-axial magnetometers commonly used for attitude determination in several devices. We compare the results of surveys performed with standard professional geophysical instruments with those obtained using these sensors and find that in the presence of strongly magnetized sources, they succeeded in identifying the main anomalies. Full article

The optimization of a contact-less magnetoelastic sensing setup designed to detect substances/agents accumulating in its environment is presented. The setup is intended as a custom-built, low-cost yet effective magnetoelastic sensor for pest/bug detection in constrained places (small museums, labs, etc.). It involves a short, thin, and flexible polymer slab in a cantilever arrangement, with a short Metglas^® 2826 MB magnetoelastic ribbon attached on part of its surface. A mobile phone both supports and supplies low-amplitude vibration to the slab’s free end. When vibrating, the magnetoelastic ribbon generates variable magnetic flux, thus inducing voltage in a contact-less manner into a pick-up coil suspended above the ribbon. This voltage carries specific characteristic frequencies of the slab’s vibration. If substances/agents accumulate on parts of the (suitably coated) slab surface, its mass distribution and, hence, characteristic frequencies change. Then, simply monitoring shifts of such frequencies in the recorded voltage enables the detection of accumulating substances/agents. The current work uses extensive testing via various vibration profiles and load positions on the slab, for statistically evaluating the sensitivity of the mass detection of the setup. It is shown that, although this custom-built substance/agent detector involves limited (low-cost) hardware and a simplified design, it achieves promising results with respect to its cost. Full article

Torque measurement is a key task in several mechanical and structural engineering applications. Most commercial torquemeters require the shaft to be interrupted to place the sensors between the two portions of the shaft where a torque has to be measured. Contactless torquemeters based on the inverse magnetostrictive effect represent an effective alternative to conventional ones. Most known ferromagnetic materials have an inverse magnetostrictive behavior: applied stresses induce variations in their magnetic properties. This paper investigates the possibility of measuring torsional loads applied to a shaft made of ferromagnetic steel S235 through an inverse magnetostrictive torquemeter. It consists of an excitation coil that produces a time-varying electromagnetic field inside the shaft and an array of sensing coils suitably arranged around it, in which voltages are induced. First, the system is analyzed both in unloaded and loaded conditions by a Finite Element Method, investigating the influence of relative positions between the sensor and the shaft. Then, the numerical results are compared with the experimental measurements, confirming a linear characteristic of the sensor (sensitivity about 0.013 mV/Nm for the adopted experimental setup) and revealing the consistency of the model used. Since the system exploits the physical behavior of a large class of structural steel and does not require the introduction of special materials, this torquemeter may represent a reliable, economical, and easy-to-install device. Full article

Motion analysis is of great interest to a variety of applications, such as virtual and augmented reality and medical diagnostics. Hand movement tracking systems, in particular, are used as a human–machine interface. In most cases, these systems are based on optical or acceleration/angular speed sensors. These technologies are already well researched and used in commercial systems. In special applications, it can be advantageous to use magnetic sensors to supplement an existing system or even replace the existing sensors. The core of a motion tracking system is a localization unit. The relatively complex localization algorithms present a problem in magnetic systems, leading to a relatively large computational complexity. In this paper, a new approach for pose estimation of a kinematic chain is presented. The new algorithm is based on spatially rotating magnetic dipole sources. A spatial feature is extracted from the sensor signal, the dipole direction in which the maximum magnitude value is detected at the sensor. This is introduced as the “maximum vector”. A relationship between this feature, the location vector (pointing from the magnetic source to the sensor position) and the sensor orientation is derived and subsequently exploited. By modelling the hand as a kinematic chain, the posture of the chain can be described in two ways: the knowledge about the magnetic correlations and the structure of the kinematic chain. Both are bundled in an iterative algorithm with very low complexity. The algorithm was implemented in a real-time framework and evaluated in a simulation and first laboratory tests. In tests without movement, it could be shown that there was no significant deviation between the simulated and estimated poses. In tests with periodic movements, an error in the range of 1° was found. Of particular interest here is the required computing power. This was evaluated in terms of the required computing operations and the required computing time. Initial analyses have shown that a computing time of 3 $\mathsf{\mu }$s per joint is required on a personal computer. Lastly, the first laboratory tests basically prove the functionality of the proposed methodology. Full article

This study introduces a novel method for the simultaneous detection of microwave sensor power and temperature, leveraging nitrogen-vacancy (NV) centers as a robust quantum system. Through precise measurement of the optical detection magnetic resonance contrast in NV centers, the microwave power is accurately determined. Furthermore, the temperature of the sensor is obtained by monitoring the variations in zero-field splitting and thorough spectral analysis. This method enables the efficient real-time acquisition of synchronized data on both microwave power and temperature from the sensor, facilitating concurrent monitoring without the necessity of additional sensing devices. Finally, we verified that the magnetic sensitivity of the system is approximately 1.2 nT/Hz^1/2, and the temperature sensitivity is around 0.38 mK/Hz^1/2. The minimum resolution of microwave power is about 20 nW. The experimental results demonstrate that this quantum measurement technique provides stable and accurate data across a wide range of microwave power and temperature conditions. These findings indicate substantial potential for this technique in advanced applications such as aerospace, medical diagnostics, and high-frequency communications. Future studies will aim to extend the industrial applicability of this method by refining quantum control techniques within NV center systems. Full article

During the in-orbit operation of spacecraft, permanent magnet synchronous motors are commonly used as power sources in the drive mechanisms of solar panel arrays and the high-precision servo control systems based on satellites. Apart from the performance of the motors themselves and the software control algorithms, the accuracy of the entire control system is also influenced by angle sensors used to detect the rotor position of the motors. As a high-precision angular measuring instrument, the inductosyn possesses excellent environmental adaptability and long service life. Effectively utilizing the inductosyn can greatly enhance the performance of servo control systems. To address the complexity of the decoding process for dual-channel round inductosyn-to-digital converters, this paper proposes a design of the decoding circuit for dual-channel round inductosyn based on the parallel-synchronization decoding method of two AD2S1210 Resolver-to-Digital Converter (RDC) decoding chips. The decoding circuit amplifies the excitation signal outputted by the AD2S1210 for driving the round inductosyn, and processes the sine and cosine induction signals outputted by the round inductosyn through filtering, amplification, and other methods; by using analog circuitry, the output signals of the dual-channel round inductosyn are processed to meet the input requirements of the AD2S1210. Finally, through both the Multisim (circuit simulation software Version 14.1) simulation and physical experiments, it was verified that the decoding circuit designed in this paper could process the input/output signals of the dual-channel round inductosyn and AD2S1210, and successfully decoded the analog induction signal of the round inductosyn. This greatly simplifies the signal decoding process for the dual-channel round inductosyn. Full article

Small piezoelectric wind-induced vibration energy harvesting systems have been widely studied to provide long-term sustainable green energy for a large number of wireless sensor network nodes. Piezoelectric materials are commonly utilized as transducers because of their ability to produce high output power density and their simple structure, but they are prone to material fracture under large deformation conditions. This paper proposes a magnetic boundary modulated stepped beam wind energy harvesting system. On the one hand, the design incorporates a composite stepped beam with both high- and low-stiffness components, allowing for efficient vibration and electrical energy output at low wind speeds. On the other hand, a magnetic boundary constraint mechanism is constructed to prevent the piezoelectric sheet from breaking due to excessive deformation. Experiments have confirmed that the effective operational wind speed range of the harvester with magnetic boundary constraints is doubled compared to that of the harvester without magnetic boundary constraints. Furthermore, by adjusting the magnetic pole spacing of the boundary, the harvesting system can generate sufficiently high output power under high-wind-speed conditions without damaging the piezoelectric sheet. Full article

In order to ensure the safety of steel wire rope in various application scenarios, it is particularly important to quantitatively detect the defects of wire rope. Complex detection conditions affect the detection efficiency of wire rope. Therefore, based on the magnetic flux leakage method, this study proposes a method to identify the damage width of steel wire rope for multi-channel fusion of a Hall sensor array. Firstly, the Hall sensor array is used to capture the magnetic flux leakage data of steel wire rope; then, continuous wavelet transform is used to decompose the original data, and moving average filtering is used to denoise each component; the denoised components are merged and converted into a time spectrum, and the time spectrum is classified by ResNet50 image classification model to realize the detection of wire rope damage width. According to the dataset used in this study, the results show that the proposed method performs best in the mainstream noise reduction model; detection accuracy for the width of damage in steel wire ropes is 97%, which proves that the proposed method is effective and feasible. Full article

Magnetic encoders are composed of a magnetic sensor, a hard magnetic recording medium and a signal processing circuit. Electrodeposited micro-magnet arrays produced by micro-fabrication are promising recording media for enhancing encoder performance. However, two major engineering issues have yet to be resolved. One issue is an unknown relationship between the feature sizes of micro-magnet arrays and their stray field shapes, and another issue is the formation of micro-cracks due to the built-up residual stresses of thick films. In this study, we investigated the effect of feature sizes on the emanating stray field shape at various observation heights. Feature sizes include two height (i.e., film thickness) values of 78 μm and 176 μm, and both width and spacing with three values of 360 μm, 520 μm and 680 μm. Ultrasound-assisted agitation was adopted for investigating the effects of electrodepositing current densities on the film crystalline microstructures and magnetic properties. Narrowing the width of micro-magnets helps the stray field to become a sinusoidal profile. Thinner film, i.e., thickness 78 μm in this study, supports the stray field taking on a sinusoidal profile. Moreover, the spacing between the micro-magnets plays a key factor in determining the shape of the stray field. Under 37 kHz/156 W ultrasound agitation, the optimal hard magnetic properties of electrodeposited CoMnP films are residual magnetization 2329 G and coercivity 968 Oe by a current density of 10.0 mA/cm². Ultrasound-assisted electrodeposition, along with duly designed feature size, facilitates the micro-magnet arrays having a sinusoidal stray field shape using high quality films. Furthermore, for the first time, a systematic understanding of feature-size-dependent stray field evolution and improved polarities quality has been realized for the recording media of sinusoidal magnetic encoders. Full article

The sensitivity of Tunnel Magnetoresistance (TMR) sensors is characterized by significant temperature drift and poor sensitivity drift repeatability, which severely impairs measurement accuracy. Conventional temperature compensation techniques are often hindered by low compensation precision, inadequate real-time performance, and an inability to effectively address the issue of poor repeatability in temperature drift characteristics. To overcome these challenges, this paper introduces a novel method for suppressing temperature drift in TMR sensors. In this method, an alternating reference magnetic field is applied to TMR sensors, and the output amplitude at the frequency of the reference magnetic field is calculated to compensate the sensitivity temperature drift in real time. Temperature characteristic tests were conducted in a non-magnetic temperature test chamber, and the results revealed that the proposed method significantly reduced the TMR sensitivity drift coefficient from 985.39 ppm/°C to 59.08 ppm/°C. Additionally, the repeatability of sensitivity temperature characteristic curves was enhanced, with a reduction in root mean square error from 0.84 to 0.21. This approach effectively mitigates temperature-induced sensitivity drift without necessitating the use of a temperature sensor, and has the advantages of real-time performance and repeatability, providing a new approach for the high-precision temperature drift suppression of TMR. Full article

A dominant event determining the course of heart failure (HF) includes the disruption of the delicate sodium (Na⁺) and water balance leading to (Na⁺) and water retention and edema formation. Although incomplete decongestion adversely affects outcomes, it is unknown whether interventions directly targeting (Na⁺), such as strict dietary (Na⁺) restriction, intravenous hypertonic saline, and diuretics, reverse this effect. As a result, it is imperative to implement (Na⁺)-targeting interventions in selected HF patients with established congestion on top of quadruple therapy with angiotensin receptor neprilysin inhibitor, β-adrenergic receptor blocker, mineralocorticoid receptor antagonist, and sodium glucose cotransporter 2 inhibitor, which dramatically improves outcomes. The limited effectiveness of (Na⁺)-targeting treatments may be partly due to the fact that the current metrics of HF severity have a limited capacity of foreseeing and averting episodes of congestion and guiding (Na⁺)-targeting treatments, which often leads to dysnatremias, adversely affecting outcomes. Recent evidence suggests that spot urinary sodium measurements may be used as a guide to monitor (Na⁺)-targeting interventions both in chronic and acute HF. Further, the classical (2)-compartment model of (Na⁺) storage has been displaced by the (3)-compartment model emphasizing the non-osmotic accumulation of (Na⁺), chiefly in the skin. 23(Na⁺) magnetic resonance imaging (MRI) enables the accurate and reliable quantification of tissue (Na⁺). Another promising approach enabling tissue (Na⁺) monitoring is based on wearable devices employing ion-selective electrodes for electrolyte detection, including (Na⁺) and (Cl^–). Undoubtably, further studies using 23(Na⁺)-MRI technology and wearable sensors are required to learn more about the clinical significance of tissue (Na⁺) storage and (Na⁺)-related mechanisms of morbidity and mortality in HF. Full article

Hall sensors are commonly used to detect rotor position information in permanent magnet synchronous motors (PMSM). However, due to the low resolution of Hall sensors, the speed signal directly collected by the motor during rotation contains significant random errors and noise. Using this signal directly may increase the error and jitter in the rotor position estimation, thereby affecting the control performance of the system. This paper proposes a novel position estimation method that combines the Kalman filter and phase-locked loop (PLL) to precisely obtain the rotor position. In the proposed method, to suppress the noise and errors of the speed signal, the state and observation equations are established using the Kalman filter algorithm. Additionally, to enhance the precision of the rotor position estimation, the position obtained by integrating the speed from the Kalman filter is processed using the PLL algorithm, and the PLL algorithm parameters are dynamically corrected. To verify the feasibility and accuracy of the proposed speed and position estimation method, simulations and experiments are performed, respectively. By adopting the proposed method, the speed error is reduced by 30% to 50%, and the current harmonic component is reduced by about 48.7%, which effectively improves the accuracy of the rotor position estimation. Full article

This paper reports the successful application of a self-developed, miniaturized, low-power nano-star tracker for precise attitude measurement of a 5-m-long satellite extension boom. Such extension booms are widely used in space science missions to extend and support payloads like magnetometers. The nano-star tracker, based on a CMOS image sensor, weighs 150 g (including the baffle), has a total power consumption of approximately 0.85 W, and achieves a pointing accuracy of about 5 arcseconds. It is paired with a low-cost, commercial lens and utilizes automated calibration techniques for measurement correction of the collected data. This system has been successfully applied to the precise attitude measurement of the 5-m magnetometer boom on the Chinese Advanced Space Technology Demonstration Satellite (SATech-01). Analysis of the in-orbit measurement data shows that within shadowed regions, the extension boom remains stable relative to the satellite, with a standard deviation of 30′′ (1σ). The average Euler angles for the “X-Y-Z” rotation sequence from the extension boom to the satellite are [−89.49°, 0.08°, 90.11°]. In the transition zone from shadow to sunlight, influenced by vibrations and thermal factors during satellite attitude adjustments, the maximum angular fluctuation of the extension boom relative to the satellite is approximately ±2°. These data and the accuracy of the measurements can effectively correct magnetic field vector measurements. Full article

The measurement of hydrogen concentration in fuel cell systems is an important prerequisite for the development of a control strategy to enhance system performance, reduce purge losses and minimize fuel cell aging effects. In this perspective paper, the working principles of hydrogen sensors are analyzed and their requirements for hydrogen control in fuel cell systems are critically discussed. The wide measurement range, absence of oxygen, high humidity and limited space turn out to be most limiting. A perspective on the development of hydrogen sensors based on palladium as a gas-sensitive metal and based on the organic magnetic field effect in organic light-emitting devices is presented. The design of a test chamber, where the sensor response can easily be analyzed under fuel cell-like conditions is proposed. This allows the generation of practical knowledge for further sensor development. The presented sensors could be integrated into the end plate to measure the hydrogen concentration at the anode in- and outlet. Further miniaturization is necessary to integrate them into the flow field of the fuel cell to avoid fuel starvation in each single cell. Compressed sensing methods are used for more efficient data analysis. By using a dynamical sensor model, control algorithms are applied with high frequency to control the hydrogen concentration, the purge process, and the recirculation pump. Full article