Search Results (211)

Measuring weak magnetic fields proposes significant challenges to the sensing capabilities of magnetic field sensors. The magnetic field detection capacity of tunnel magnetoresistance (TMR) sensors is often insufficient for such applications, necessitating targeted optimization strategies to improve their performance in weak-field measurements. Utilizing magnetic flux concentrators (MFCs) offers an effective approach to enhance TMR sensitivity. In this study, the finite element method was employed to analyze the effects of different MFC geometric structures on the uniformity of the magnetic field in the air gap and the magnetic circuit gain (MCG). It was determined that the MCG of the MFC is not directly related to the absolute values of its parameters but rather to their ratios. Simulation analyses evaluated the impact of these parameter ratios on both the MCG and its spatial distribution uniformity, leading to the formulation of MFC design optimization principles. Building on these simulation-derived principles, several MFCs were fabricated using the 1J85 material, and an experimental platform was established to validate the simulation findings. The fabricated MFCs achieved an MCG of 7.325 times. Based on the previously developed TMR devices, a detection sensitivity of 2.46 nT/$\sqrt{\mathrm{Hz}}$ @1Hz was obtained. By optimizing parameter configurations, this work provides theoretical guidance for further enhancing the performance of TMR sensors in magnetic field measurements. Full article

Magnetocardiography (MCG) provides a non-invasive, contactless technique for evaluating the magnetic fields generated by cardiac electrical activity, offering unique spatial insights into cardiac electrophysiology. However, conventional MCG systems depend on superconducting quantum interference devices that require cryogenic cooling and magnetic shielded environments, posing considerable impediments to widespread clinical adoption. In this study, we present a novel MCG system utilizing a high-sensitivity, wide-dynamic-range magnetoresistive sensor array operating at room temperature. To mitigate environmental interference, identical sensors were deployed as reference channels, enabling adaptive noise cancellation (ANC) without the need for traditional magnetic shielding. MCG recordings were obtained from 40 healthy participants, with signals processed using ANC, R-peak-synchronized averaging, and Bayesian spatial signal separation. This approach enabled the reliable detection of key cardiac components, including P, QRS, and T waves, from the unshielded MCG recordings. Our findings underscore the feasibility of a cost-effective, portable MCG system suitable for clinical settings, presenting new opportunities for noninvasive cardiac diagnostics and monitoring. Full article

Mechanical defects and sensor failures can substantially undermine the reliability of low-cost sensors, especially in applications where measurement inaccuracies or malfunctions may lead to critical outcomes, including system control disruptions, emergency scenarios, or safety hazards. To overcome these challenges, this paper presents a novel Self-X architecture with sensor redundancy, which incorporates dynamic calibration based on multidimensional mapping. By extracting reliable sensor readings from imperfect or defective sensors, the system utilizes Self-X principles to dynamically adapt and optimize performance. The approach is initially validated on synthetic data from tunnel magnetoresistance (TMR) sensors to facilitate method analysis and comparison. Additionally, a physical measurement setup capable of controlled fault injection is described, highlighting practical validation scenarios and ensuring the realism of synthesized fault conditions. The study highlights a wide range of potential TMR sensor failures that compromise long-term system reliability and demonstrates how multidimensional mapping effectively mitigates both static and dynamic errors, including offset, amplitude imbalance, phase shift, mechanical misalignments, and other issues. Initially, four individual TMR sensors exhibited mean absolute error (MAE) of 4.709°, 5.632°, 2.956°, and 1.749°, respectively. To rigorously evaluate various dimensionality reduction (DR) methods, benchmark criteria were introduced, offering insights into the relative improvements in sensor array accuracy. On average, MAE was reduced by more than 80% across sensor combinations. A clear quantitative trend was observed: for instance, the MAE decreases from 4.7°–5.6° for single sensors to 0.111° when the factor analysis method was applied to four sensors. This demonstrates the concrete benefit of sensor redundancy and DR algorithms for creating robust, fault-tolerant measurement systems. Full article

Touch is a crucial sense for advanced organisms, particularly humans, as it provides essential information about the shape, size, and texture of contacting objects. In robotics and automation, the integration of tactile sensors has become increasingly relevant, enabling devices to properly interact with their environment. This study aimed to develop a biomimetic, skin-inspired tactile sensor device capable of sensing applied force, characterizing it in three dimensions, and determining the point of application. The device was designed as a 4 × 4 matrix of tunneling magnetoresistive sensors, which provide a higher sensitivity in comparison to the ones based on the Hall effect, the current standard in tactile sensors. These detect magnetic field changes along a single axis, wire-bonded to a PCB and encapsulated in epoxy. This sensing array detects the magnetic field from an overlayed magnetorheological elastomer composed of Ecoflex and 5 µm neodymium–iron–boron ferromagnetic particles. Structural integrity tests showed that the device could withstand forces above 100 N, with an epoxy coverage of 0.12 mL per sensor chip. A 3D movement stage equipped with an indenting tip and force sensor was used to collect device data, which was then used to train neural network models to predict the contact location and 3D magnitude of the applied force. The magnitude-sensing model was trained on 31,260 data points, being able to accurately characterize force with a mean absolute error ranging between 0.07 and 0.17 N. The spatial sensitivity model was trained on 171,008 points and achieved a mean absolute error of 0.26 mm when predicting the location of applied force within a sensitive area of 25.5 mm × 25.5 mm using sensors spaced 4.5 mm apart. For points outside the testing range, the mean absolute error was 0.63 mm. Full article

Gear condition monitoring is predominantly executed through the utilization of acceleration sensors positioned on the housing. However, recent advancements have identified measuring the instantaneous angular speed as a compelling alternative as it shortens the transmission path and therefore provides high-quality rotational angle information that can be used to increase damage prediction accuracy, particularly under transient operating conditions. Additionally, there are a variety of methodologies for integrating sensors into gears, which underscores the necessity for high-quality condition data. However, it should be noted that a significant amount of effort is required to successfully integrate these sensors into the rotating system. This publication uses a gear wheel sensor that employs the gear itself as a material measure to acquire rotational angle data and to deduce the damage condition. A magnetoresistive sensor is integrated into the gearbox housing radially facing a ferromagnetic gear and measures the rotational angle by the gear teeth. Various artificial tooth flank damages are applied to the pinion. The rotational angle is measured with the gear sensor, and the damage state is classified with a random forest classifier using established evaluations in the time and frequency domains. The tests are conducted under stationary operating conditions at an array of speed and torque levels. Additionally, they are performed under transient operating conditions, employing speed ramps at constant torque. The results of the classification are evaluated by means of classification accuracy and confusion matrices and compared with those obtained via a classic encoder at the pinion shaft and an acceleration sensor at the gearbox housing. Full article

The anisotropic magnetoresistance (AMR) effect is widely used in microscale and nanoscale magnetic sensors. In this study, we investigate the correlation between AMR and the crystal structure, epitaxial relationship, and magnetic properties of Co₅₀Fe₅₀ thin films deposited on rigid MgO and flexible mica substrates. The AMR ratio is approximately 1.6% for CoFe films on mica, lower than the 2.5% observed in epitaxially grown films on MgO substrates. The difference is likely due to the well-defined easy axis in the single domain epitaxial thin films on MgO, which enhances the AMR ratio. Microscopic strain induced by lattice mismatch and bending on flexible substrates were determined using grazing incidence X-ray diffraction and extended X-ray absorption fine structure techniques. These results showed that neither microscopic nor macroscopic strain (below 0.5%) affects the AMR ratio on mica, suggesting its suitability for magnetic sensors in flexible and wearable devices. Additionally, investigating M-H loops under various growth temperatures, lattice mismatch conditions, and bending strains could further benefit the fabrication and integration of the micro-scale magnetic sensors in the microelectronic industry. Full article

This study presents a novel dual phase-locked loop two-dimensional synchronized motion modulation (TDSMM-DPLL) system designed to enhance the low-frequency detection capability of magnetoresistive (MR) sensors by effectively mitigating 1/f noise. The TDSMM-DPLL system integrates a comb-driven resonator and a piezoelectric cantilever beam resonator, achieving synchronized magnetic field modulation through a DPLL circuit that adjusts the resonant frequency of the comb-driven resonator to twice that of the cantilever beam resonator. Theoretical analysis and finite element simulations demonstrate a modulation efficiency of 38.98%, which is significantly higher than that of traditional one-dimensional modulation methods. Experimental validation confirms the system’s effectiveness, showing a 3.13-fold reduction in frequency Allan variance, decreasing from 217.32 ppb to 69.46 ppb, indicating substantial noise suppression. These results highlight the TDSMM-DPLL system’s potential to improve the performance of MR sensors in low-frequency applications, making it a promising solution for high-precision magnetic field detection. Full article

In response to the accurate positioning issue for high-speed moving lens groups in rapid zoom optical lenses with voice coil motors (VCMs), we demonstrate a positioning system design based on tunnel magnetoresistance sensors. The equivalent magnetic charge method and finite element method (FEM) simulations were utilized to compute the magnetic field distribution of the magnetic grating encoder. Based on analytical computation, the optimal air gap δ_S between the sensor and magnetic grating is determined to be δ_S = 0.15 mm, which balances magnetic flux density amplitude and total harmonic distortion. In addition, a simplified fitting model is proposed to reduce computational complexity. We quantify the magnetic interference of VCM through three-dimensional flux leakage mapping by FEM analysis, deriving an optimal sensor position O_S, with a 24 mm y-offset and 20 mm z-offset relative to the VCM’s origin O_V. The position error caused by interference remains below 5 μm with maximum deviations at trajectory endpoints of the moving group. The original signal output is processed and corrected, and eventually, the measured displacement exhibits a linear relationship with actual displacement. Our study provides a comprehensive framework for the design and optimization of magnetic positioning systems in optical applications with electromagnetic motors. Full article

Accurate measurement of magnetic fields holds immense significance across various disciplines, such as IC circuit measurement, geological exploration, and aerospace. The sensitivity and noise parameters of magnetic field sensors play a vital role in detecting minute fluctuations in magnetic fields. However, the current detection capability of tunneling magnetoresistance (TMR) is insufficient to meet the requirements for weak magnetic field measurement. This study investigates the impact of structural and fabrication parameters on the performance of TMR sensors. We fabricated series-connected TMR sensors with varying long-axis lengths of the elliptical cross-section and adjusted their performance by modifying annealing magnetic fields and magnetic field bias along the easy axis. The results demonstrate that TMR sensitivity decreases with increasing long-axis length, increases initially and then decreases with an annealing magnetic field, and decreases with a higher bias magnetic field along the easy axis. The voltage noise level of TMR sensors decreases as the long-axis length increases. Notably, the detection capability of TMR sensors exhibits a non-monotonic dependence on long-axis length. Moreover, we optimized the hysteresis of TMR sensors by applying a magnetic field bias along the easy axis. When the bias along the easy axis reached 16 Oe or −40 Oe, the hysteresis level was reduced to below 0.5 Oe. After encapsulating the TMR devices into a full Wheatstone bridge structure, we achieved a detection capability of 17 nT/$\sqrt{\mathrm{Hz}}$@1Hz. This study highlights that the detection capability of TMR devices is jointly influenced by fabrication parameters. By optimizing parameter configuration, this work provides theoretical guidance for further enhancing the performance of TMR devices in magnetic field measurements. Full article

This study presents a system for precisely measuring pulsed magnetic fields with high amplitude and microsecond duration with minimal interference. The system comprises a probe with an advanced magnetic field sensor and a measurement unit for signal conversion, analysis, and digitization. The sensor uses a thin nanostructured manganite La-Sr-Mn-O film exhibiting colossal magnetoresistance, which enables precise magnetic field measurement independent of its orientation. Films with different compositions were optimized and tested in pulsed magnetic fields. The measurement unit includes a pulsed voltage generator, an ADC, a microcontroller, and an amplifier unit. Two versions of the measurement unit were developed: one with a separate amplifier unit configured for the sensor positioned more than 1 m away from the measurement unit, and the other with an integrated amplifier for the sensor positioned at a distance of less than 0.5 m. A bipolar pulsed voltage supplying the sensor minimized the parasitic effects of the electromotive force induced in the probe circuit. The data were transmitted via a fiber optic cable to a PC equipped with a special software for processing and recording. Tests with 20–30 μs pulses up to 15 T confirmed the effectiveness of the system for measuring high pulsed magnetic fields. Full article

With the rapid development of current sensor technology, tunnel magnetoresistance (TMR) current sensors have been widely adopted in industrial detection due to their high sensitivity, excellent linearity, and broad measurement range. This study focuses on closed-loop TMR current sensors, utilizing COMSOL Multiphysics 6.2 software and the finite element method to conduct an in-depth analysis of structural parameters affecting sensor sensitivity. A novel magnetic shielding package architecture is proposed and designed. Simulation results demonstrate that the shielding efficiency of this structure improves by 44.3% compared to a single magnetic ring under a stray magnetic field of 0.1 mT along the sensing axis. At the same time, the measurement accuracy is 2.1 times higher than that of traditional structures. Current detection experiments conducted in a strong magnetic field environment further validate that the shielding package effectively suppresses external electromagnetic interference, significantly enhancing sensor stability and measurement accuracy. This research provides important theoretical and practical insights for applying high-precision TMR current sensors in complex electromagnetic environments. Full article

Planar Hall magnetoresistance (PHMR) sensors are widely utilized due to their high sensitivity, simple structure, and cost-effectiveness. However, their performance is influenced by both the driving mode and the thickness of the ferromagnetic layer, yet the combined effects of these factors remain insufficiently explored. This study systematically investigates the impact of Ni₈₀Fe₂₀ thickness (5–35 nm) on PHMR sensor performance under constant current (CC) and constant voltage (CV) modes, with a focus on optimizing the peak-to-peak voltage (V_p-p). In CC mode, electron surface scattering at 5–10 nm increases resistance, leading to a sharp rise in V_p-p, followed by a decline as the thickness increases. In contrast, CV mode minimizes resistance-related effects, with sensor signals predominantly governed by magnetization-dependent resistivity. Experimentally, the optimal V_p-p was observed at 25 nm in CV mode. However, for thicknesses beyond this point, the reduction in sensor resistance suggests that voltage distribution across both the sensor and external load resistance significantly influences performance. These findings provide practical insights into optimizing PHMR sensors by elucidating the interplay between driving modes and material properties. The results contribute to the advancement of high-performance PHMR sensors with enhanced signal stability and sensitivity for industrial and scientific applications. Full article

The moving-magnet linear motor has received considerable attention in the development of logistic and factory automation in recent years. A reliable position detection system is the key to achieving the precise position and control of the motor. At present, the magnetic grid-scale and grating-scale are the most widely used traditional detection methods. However, these are not suitable for position detection with moving-magnet linear motors. They have the disadvantages of being easy to disturb, having a high cost, and exhibiting a limited measurement range. In this work, a moving-magnet linear motor position detection system based on an array of magnetoresistive sensors is used. The array is configured by arranging the magnetoresistive sensors at equal intervals along a line parallel to the trajectory of the armature. Then, the permanent magnet is fixed on the rotor and detected by sensors. When the rotor crosses the sensors in a parallel line, the changes in the magnetic field cause the magnetoresistive sensors to output two voltage signals directly proportional to the corresponding position changes. The signals are collected by the AD7606 and transmitted to the FPGA and STM32 controller for data processing, and the actual position of the rotor is calculated. This method has no length limitation and can be used for long-distance position detection. The experimental results show that the position detection system has a higher linear correlation coefficient compared with the magnetic grid ruler, in addition to a capability of ±9 μm accuracy, which verifies the validity of the position detection method for the moving-magnet linear motor. Full article

This study introduces an innovative, non-contact method for classifying the hardness of austenitic stainless steels (grade AISI 304) based on their intrinsic magnetic fields. Utilizing a 3 × 3 matrix sensor system, this research captures weak magnetic fields to produce precise 2D magnetic field maps of the samples. A key advancement is the application of a modified GoogleNet convolutional neural network, optimized with the stochastic gradient descent with momentum algorithm, which achieves exceptional classification accuracy, ranging from 95% to 100%, and median accuracies of 97.5% to 99%. This method stands out by revealing a novel correlation between annealing temperature and magnetic field strength, particularly a pronounced decline in magnetic properties at temperatures near 1000 °C. This observation underscores the sensitivity of magnetic profiles to heat treatments, offering a groundbreaking approach to material characterization. By enabling reliable, efficient, and fully automated hardness evaluation based on magnetic signatures, this work has the potential to transform materials engineering and manufacturing, setting a new benchmark for non-destructive material analysis techniques. Full article

We developed a measurement system capable of detecting magnetic responses in various material samples. The system utilizes an excitation coil to apply an alternating magnetic field within the frequency range of 1–10 kHz. The magnetic field generated in the samples was detected using a highly sensitive magnetoresistive sensor. The system demonstrated a detection lower limit in the sub-pT range for magnetic fields arising from magnetic responses such as eddy currents and magnetization changes. The frequency dependence of the detected signal intensities correlated well with the physical mechanisms underlying the magnetic responses. Notably, the distance between the excitation coil and the magnetic sensor was maintained at 300 mm. These results, which demonstrate the detection of a sub-pT magnetic field using a highly sensitive magnetic sensor, have not been previously reported and provide valuable insights for advancing practical applications in non-destructive testing and clinical diagnostic imaging. Full article