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The integration of nanocomposite thin films with combined multifunctionalities on flexible substrates is desired for flexible device design and applications. For example, combined plasmonic and magnetic properties could lead to unique optical switchable magnetic devices and sensors. In this work, a multiphase TiN-Au-Ni nanocomposite system with core–shell-like Au-Ni nanopillars embedded in a TiN matrix has been demonstrated on flexible mica substrates. The three-phase nanocomposite film has been compared with its single metal nanocomposite counterparts, i.e., TiN-Au and TiN-Ni. Magnetic measurement results suggest that both TiN-Au-Ni/mica and TiN-Ni/mica present room-temperature ferromagnetic property. Tunable plasmonic property has been achieved by varying the metallic component of the nanocomposite films. The cyclic bending test was performed to verify the property reliability of the flexible nanocomposite thin films upon bending. This work opens a new path for integrating complex nitride-based nanocomposite designs on mica towards multifunctional flexible nanodevice applications. [ABSTRACT FROM AUTHOR]

Knowledge of modern state-of-the-practice traffic flow sensors provides traffic managers, researchers, and students an understanding of the operation, strengths, and limitations of current sensor technologies and enables them to make an informed decision as to which is appropriate for a particular application. Accordingly, this article describes the intrusive and nonintrusive traffic flow sensor technologies in use today, their applications and selection criteria, and typical output data. Furthermore, it provides examples of representative sensor models. The technologies discussed are mature with respect to current traffic management applications, although some may not provide the data or accuracy required for a specific application or may not perform as needed under the operational conditions anticipated at the installation site. Sensors selected for a first-time application should be field tested under conditions that will be encountered in day-to-day operation before large-scale purchases of the devices are made. As alternative traffic data and information sources, such as commercial data vendors, Wi-Fi and Bluetooth sensing of smartphone locations, and connected and automated vehicle data, become increasingly available, they are progressively finding their way into modern traffic management systems as a complement to conventional roadside sensors. [ABSTRACT FROM AUTHOR]

In a smart city, sensors are essential elements—the source of up-to-date traffic information. This article deals with magnetic sensors connected to wireless sensor networks (WSNs). They have a low investment cost, a long lifetime, and easy installation. However, it is still necessary to disturb the road surface locally during their installation. All road lanes to and from the city center of Žilina have sensors that send data at five-minute intervals. They send up-to-date information about the traffic flow's intensity, speed, and composition. The LoRa network ensures the data transmission, but in the event of failure, the 4G/LTE modem realizes the backup transmission. The disadvantage of this application of sensors is their accuracy. The research task was to compare the outputs from the WSN with a traffic survey. The appropriate method for the traffic survey on the selected road profile is a video recording and speed measurement using the Sierzega radar. The results show distorted values, mainly for short intervals. The most accurate output from magnetic sensors is the number of vehicles. On the other hand, traffic flow composition and speed measurement are relatively inaccurate because it is not easy to identify vehicles based on dynamic length. Another problem with sensors is frequent communication outages, which cause an accumulation of values after the outage ends. The secondary objective of the paper is to describe the traffic sensor network and its publicly accessible database. In the end, there are several proposals for data usage. [ABSTRACT FROM AUTHOR]

A novel noncontact three-degree-of-freedom radial/axial eddy-current position sensor for applications in active magnetic bearings (AMBs) is developed. The sensor meets the most demanding industrial requirements, including ability to work in dusty environments and in many working fluids, low sensitivity to temperature changes, as well as external electrical and magnetic fields, excellent linearity over a large displacement range, large intrinsic gain, easy integration into a machine, robustness to variations in parameters of the external wiring, simplicity of the signal processing electronics, and large frequency bandwidth. The sensor is inexpensive in volume and well suited for high-volume production. It has been successfully integrated into a commercial 175-kW air compressor, which was spun to the full operation speed of 50 kRPM. Operation with a 4-m twisted-pair sensor cable has been demonstrated and using much longer (tens of meters) cables would be possible with design modifications. Even though the sensor was developed for AMBs, it can find other uses in rotating machinery and beyond. [ABSTRACT FROM AUTHOR]

In this work, an optimized tunnel magnetoresistive (TMR) accelerometer with a closed-loop control system was developed and evaluated. The device first introduces a silicon spring–mass sensing structure lower than 50 Hz into TMR-based accelerometry for enhancing the mechanical sensitivity and subsequent readout sensitivity. Simultaneously, in order to realize the in-plane electrostatic feedback control, the comb structure is designed along with the sensing mechanism, owning combined benefits of integrated processing and large feedback force. The whole sensing structure is a silicon-glass chip, fabricated by the standard micro-electromechanical system (MEMS) process—deep dry silicon on glass (DDSOG) process. A permanent rubber magnet is assembled on the proof mass for conversion from the displacement to variation of the magnetic field intensity, which is further detected by a pair of symmetrically arranged TMR sensors. The voltage signals output from TMR sensors are then sent into an analog circuit via an interface module for force-feedback control. The simulation analysis indicates that the proposed MEMS sensing structure has a low natural frequency of 44.55 Hz, corresponding to a compliant mechanical sensitivity of 125.5 $\mu \text{m}$ /g. Meanwhile, a maximum magnetic sensitivity of about 0.1 mT/mm is available in a height of 6 mm above the $3\times 3\times0.3$ mm magnet. Finally, the experiments on the assembled prototype demonstrated that a scale factor of 1.79 V/g and a bias stability of 228 $\mu \text{g}$ have been achieved in the closed-loop modality, which verifies the effectiveness of the proposed TMR MEMS accelerometer. [ABSTRACT FROM AUTHOR]

A kind of magnetic field sensor is proposed, which is based on symmetrically side-polished photonic crystal fiber (PCF) with regular hexagonal air holes. Magnetic fluid (MF) is used as the magnetic field-sensitive material. The polished surfaces are coated with an indium tin oxide (ITO) film to generate lossy mode resonance (LMR) for magnetic field sensing. The obtained magnetic field sensitivity is 466.81 pm/Oe, which can be further adjusted by changing the thickness of the ITO film. The comprehensive sensing performance is evaluated by defining the figure of merit (FOM). The proposed structure is simple and has the capability of mass production, which has great development space in the future. [ABSTRACT FROM AUTHOR]

Indoor localization problems are difficult due to that the information, such as WLAN and GPS, cannot achieve enough precision for indoor issues. This paper presents a novel indoor localization algorithm, GeoLoc, with uncertainty eliminate based on fusion of acceleration, angular rate, and magnetic field sensor data. The algorithm can be deployed in edge devices to overcome the problems of insufficient computing resources and long delay caused by high complexity of location calculation. Firstly, the magnetic map is built and magnetic values are matched. Secondly, orientation updating and position selection are iteratively executed using the fusion data, which gradually reduce uncertainty of orientation. Then, we filter the trajectory from a path set. By gradually reducing uncertainty, GeoLoc can bring a high positioning precision and a smooth trajectory. In addition, this method has an advantage in that it does not rely on any infrastructure such as base stations and beacons. It solves the common problems regarding the non-uniqueness of the geomagnetic fingerprint and the deviation of the sensor measurement. The experimental results show that our algorithm achieves an accuracy of less than 2.5 m in indoor environment, and the positioning results are relatively stable. It meets the basic requirements of indoor location-based services (LBSs). [ABSTRACT FROM AUTHOR]

Permanent magnet eddy current couplings (PMECCs) are widely used in industry to transmit torque through their interior magnetic field. It is important to measure the interior magnetic field of a PMECC, which helps ensure its excellent performance and prevent possible accidents. However, the distribution of magnetic fields is difficult to reconstruct in situ by traditional measuring or modeling approaches. This article proposes a method to continuously reconstruct the distribution of interior magnetic fields and estimate the relative parameters in a short time with a limited number of Hall sensors. A model of field-associated reconstruction (FAR) is proposed to reconstruct the distribution of interior magnetic fields using historical data and sensor positions as constraints. The slip and output torque can be estimated based on the FAR without the need to use additional speed–torque sensors. The experimental results verify the performance of the proposed method. The results show that the model performed well in the reconstruction of axial and tangential components and relatively well near the geometric boundary in the reconstruction of radial components. The relative errors in the speed and torque estimations are approximately 4% and 6%, respectively. The limitations and corresponding reasons are also discussed. [ABSTRACT FROM AUTHOR]

Magnetic biomarker detection and monitoring at low concentrations are critical for the early diagnosis of many diseases and for accurately identifying specific biomolecules. Previously reported highly sensitive detection methods rely on magnetic sensors to detect the stray fields of magnetic labels (usually magnetic beads). The random noise generated by the Brownian motion of magnetic beads in solution makes it difficult to reduce further the limit of detection (LOD) of this measurement. Therefore, we propose a low-concentration magnetic beads sensor and a dynamic magnetic excitation detection method. The intensity of magnetization motion under the ac excitation magnetic field detected by the quartz crystal microbalance (QCM) realizes the measurement of the magnetic bead concentration in the solution. The experimental results show that the LOD of the proposed sensor in $2.8~\mu \text{m}$ magnetic bead solution is 10 ng/mL and displays an approximate linear detection characteristic in the range of 20–100 ng/mL. The intensity of magnetization detected by QCM has an approximately linear relationship with the magnetic bead concentration. Given the wide application of magnetic-labeled biomolecule detection and its huge application prospects in early disease detection and precision medicine, this method provides an inexpensive, fast, and flexible detection technology for the general labeling analysis of magnetic labels in biomolecule detection. [ABSTRACT FROM AUTHOR]

In this article, we present a CMOS hybrid magnetic field sensor for real-time motor speed monitoring for smart energy-efficient autonomous systems. The sensor system consists of a micro Hall effect sensor ($\mu $ HES) and a micro search coil magnetometer ($\mu $ SCM) using Taiwan Semiconductor Manufacturing Company (TSMC) 0.18- $\mu \text{m}$ 1P6M CMOS process with a die size of $1.5\times2$ mm. The hybrid sensor is realized completely by the CMOS process without postprocessing. A wide range of rotation speeds can be measured by the presented passive $\mu $ SCM without signal amplification (>600 r/min) and the combination of the $\mu $ SCM and $\mu $ HES on the same chip allows the low rotation speed range measurement (< 600 r/min). Furthermore, the $\mu $ SCM has zero offset and very low-temperature dependency. The magnetic field of a permanent magnet on the rotating shaft of the motor is measured by the $\mu $ SCM and $\mu $ HES to determine the rotation speed. The sensitivity of the $\mu $ HES (at 5-V bias voltage) and the $\mu $ SCM inside a uniform magnetic field are 113.6 and $11.3 \mu \text{V}$ /mT at 1 Hz without amplification, respectively. The noise equivalent magnetic induction (NEMI) of the $\mu $ SCM was calculated and verified experimentally by utilizing a zero-drift instrumentation amplifier. Furthermore, a simplified equivalent circuit model for the $\mu $ SCM is presented and verified experimentally. According to the equivalent circuit model, the linear frequency response region of the $\mu $ SCM is up to 20 kHz, which suits the controlling motors in smart autonomous systems and other low-frequency applications. [ABSTRACT FROM AUTHOR]

In the field of multimodal human–computer interaction (HCI), hand (and finger) motion tracking remains a critical challenge because it is the input means of visual reproduction and provides the necessary parameters for real-time modeling of the haptic model. Among motion tracking methods including optical tracking methods, inertial tracking methods, and magnetic motion tracking (MMT) methods, the MMT method has a great development prospect as a marker-based method because of its advantages of no line-of-sight problem, being natural-oriented, and high accuracy. In this article, we first discuss the performance and application scenarios under different configurations of electromagnet-based MMT (EMMT) and permanent-magnet-based MMT (PMMT) systems. And then, the MMT algorithms are reviewed, which can be divided into two broad categories: The model-based algorithms include linear algorithm, nonlinear optimization algorithm, and recursive Bayesian algorithm, and the offline-data-based algorithms include neural network algorithm and lookup table (LUT) algorithm. In addition, a state-of-the-art comparison of MMT algorithms is given. In the end, we have an insightful discussion and give the expected future outlook of MMT. [ABSTRACT FROM AUTHOR]

Many methods used for precise fault detection in salient pole synchronous generators (SPSGs) often require a priori knowledge of the healthy case, but this requirement impedes application of the methods since an accurate analysis of different machine quantity waveforms is not usually carried out during commissioning. The inspection and maintenance processes in SPSGs are also costly and time consuming; therefore, reliable methods that can detect and discriminate between different faults without comparison with the healthy condition are highly desirable. This article proposes a precise method for detection and discrimination between different fault types in the SPSG. The method does not require healthy machine data and is applied to diagnose both interturn short circuits (ITSCs) in the field winding and dynamic eccentricities (DEs). The proposed nonintrusive detection algorithm is based on advanced signal analysis of stray magnetic field data and can be applied during SPSG operation. The method is highly precise for monitoring the condition of the rotor field winding and yields a unique pattern for diagnosing possible ITSC faults. Moreover, a distinctive pattern for the DE fault enables the discrimination between both considered failures, even if they are present at the same time. The proposed method is validated through finite-element modeling and experimentally on 100-kVA and 22-MVA SPSGs to demonstrate its applicability in real power plants. [ABSTRACT FROM AUTHOR]

The low-cost, simple, and fast quantitative assay of magnetic nanoparticles (MNPs) is important for the development of magnetic-based immunoassay applications. However, the bulky sensing element and instruments of the recent iron oxide-based MNPs assays are still concerns that should be resolved. This article reports the new platform of an iron oxide-based MNPs label assay using the commercial giant magnetoresistance (GMR) chip AAL024, manufactured by Nonvolatile Electronics (NVE) Corporation, complemented with a basic differential amplifier circuit and Arduino microcontroller (AM) to acquire the digital output voltage. The as-prepared Fe3O4@Ag label possessed (15 ± 2.6) nm of average size and behaved as soft ferromagnetic with 52.1 emu/g of saturation magnetization, and 0.15 kOe of coercive field. Sensor performance for magnetic field detection, as well as Fe3O4@Ag nanoparticles label assay, was evaluated. The results show the implementation of a basic differential amplifier op-amp circuit succeed to magnify the sensor’s response to the magnetic field up to 23 times with the output voltage in the order of volt. The employment of the AM as a voltage supply of the GMR chip, an analog-to-digital converter, and a voltage gauge simplifies the data acquisition without the additional measuring instrument. Meanwhile, for the purpose of the Fe3O4@Ag nanoparticles label assay, the sensor revealed promising performance due to the high signal linearity and the rapid detection which is only 30 s with acceptable signal stabilities. [ABSTRACT FROM AUTHOR]

A novel miniature magnetic-fluid (MF)-infiltrated eccentric fiber Bragg grating (EFBG) vectorial magnetic field sensor was proposed and experimentally demonstrated. An EFBG with a length of 10 mm and an eccentric distance of $2~\mu \text{m}$ was written in a standard single-mode fiber by a point-to-point femtosecond laser (FSL) writing process, which was then sealed in an MF-infiltrated glass capillary (GC) to form the magnetic-field-sensitive structure. Through the refractive index and absorption modulation of the MF under the influence of external magnetic fields, the transmission intensities at the resonant wavelengths of cladding modes are accordingly changed. Transmission at these resonant wavelengths can be used as the magnetic field sensing quantity. Experiments show that the sensor can sensitively respond to both strength and direction of the magnetic field. A sensitivity of about 0.042 dB/Oe in a magnetic field strength range of 0–120 Oe was found. [ABSTRACT FROM AUTHOR]

In this article, a compact fiber-optic current sensor (FOCS) based on an in-fiber Fabry–Pérot interferometer (FPI) and a magnetostrictive transducer is presented. The in-fiber FPI sensor employed in the proposed FOCS was fabricated with a 273- $\mu \text{m}$ Section of a capillary fiber spliced between two pieces of a standard single-mode fiber (SMF). The in-fiber FPI sensor and a commercial fiber Bragg grating (FBG), which was used as a reference sensor for sensitivity comparison, were bonded to a small magnetostrictive actuator (Terfenol-D) and assembled in the proposed FOCS for electric current monitoring up to $800 {A}_{\text {rms}}$ using a commercial FBG interrogator. The in-fiber FPI sensor presented a sensitivity 84.4% higher than that of the FBG sensor. An alternative interrogation system based on an edge-filter technique with temperature compensation was also developed and employed for the characterization of the proposed FOCS under the same range of electric current. Using the edge-filter interrogation system developed, the in-fiber FPI sensor presented a sensitivity 169.8% higher than that shown by the FBG sensor. The results show that the proposed FOCS using an in-fiber FPI sensor presented high sensitivity to electric current sensing and, therefore, is a potential candidate for current monitoring in complement to conventional current transformers (CTs) as well as to conventional optical CTs (OCTs). [ABSTRACT FROM AUTHOR]

This article presents a novel displacement detection method with sensing coils weakly coupled with a conventional eight-pole active magnetic bearing. To improve integration, the sensing coils are completely wound on the magnetic poles of the active magnetic bearing. The proposed method is different from others since each sensing coil is wound around two teeth of an active magnetic bearing, reducing the mutual inductance coefficient between sensing and excitation coils. Thus, the influence of excitation coils on displacement detection can be reduced. A core multiplexing and frequency discrimination method is proposed to detect displacements along ${x}$ - and ${y}$ -directions, simultaneously. Experiment results show that sensitivity along the ${x}$ - and ${y}$ -axes are 8.98 and 5.61 mV/ $\mu \text{m}$ , respectively, showing the feasibility of displacement detection without being affected by displacement variation of the orthogonal axis. Finally, the displacement detected by sensing coils is used for close loop control in an active magnetic bearing system at 2500 rpm, validating the feasibility of sensing coils in active magnetic bearing control. [ABSTRACT FROM AUTHOR]

In this study, a novel design of multiperiod bipolar inductive absolute angle sensor is proposed. The sensor structure is composed of stator and rotor. An inner and outer fan-shaped bipolar pattern is designed and fabricated on the rotor. The receiving coils and signal processing circuits are on the stator. When alternating current is applied to the excitation coil, the eddy current is generated in the rotor. The induced voltage of two adjacent receiving coils is in the form of cosine, when the rotor rotates above the receiving coil. There are two groups of receiving coils in the sensor. One group is composed of eight loops, corresponding to the 45° fan-shaped pattern at the outer edge, and the other group is composed of two loops, corresponding to the 180° fan-shaped (semicircular) pattern at the center. The coil with more loops provides high measurement accuracy and the coil with a small number of loops provides the identification of the number of cycles. The results show that the measurement error is 0.04° and the resolution is better than 0.005° in the range of 0°–360°. Through the multiperiod bipolar pattern proposed in this article, a high accuracy absolute position measurement can be realized. [ABSTRACT FROM AUTHOR]

Simultaneous magnetic actuation and localization is a promising technology to realize active wireless capsule endoscopy. In this article, an adaptive approach is proposed to efficiently propel and precisely locate a magnetically actuated capsule in unknown complex tubular environments. In order to track the capsule in real time in a large workspace, we improve upon our previous external sensor-based magnetic localization strategies by proposing an adaptive method to automatically activate an optimal subset of sensors during the capsule movement and developing a simplified multiple objects tracking algorithm to estimate the six-dimensional pose of the capsule in real time. Moreover, based on a study of capsule locomotion in tubular environments with different shapes, we propose to dynamically adjust the pose of the actuator to achieve efficient and robust propulsion of the capsule in an unknown tubular environment. The effectiveness of our proposed system is validated in extensive experiments on phantoms and ex vivo animal organs. Compared with the state-of-the-art, our method can realize the closed-loop control of a magnetic capsule without requiring sensing modules to be placed inside the capsule, which can reduce the space constraints and energy consumption of the capsule. Moreover, the system and algorithms for adaptive actuation and localization can provide an improved propulsion speed, workspace range, and localization update frequency as well as a comparable localization accuracy. [ABSTRACT FROM AUTHOR]

The surging applications of low-power sensors and portable electronic devices require a safe, convenient and low-cost charging method which draws interests of the wireless power transfer research field. Conventional WPT techniques using resonant coupling structures are limited by complexity, safety concerns and hardware costs. Electromechanical wireless power transfer (EWPT) techniques provide a low-cost, easy-to-control and safe wireless charging method via moving magnets; but transmission failures may occur due to the position and orientation misalignments of loads from optimum conditions. This article proposes an EWPT system that is able to charge loads at different tilt angles via a low-frequency rotating magnetic field and a permanent magnet rotor. The magnetic field has a uniform distribution in a space volume over 125 000 mm3. A custom permanent magnet rotor embedded with six identical cylindrical magnets and an induction coil is employed to capture transmitted power. Theoretical analyses and experimental results are presented to prove the feasibility and output capability of the proposed system. The peak output power achieves 130 mW under a magnetic field strength around 1 mT and the system output maintains stable for loads at different tilt angles. Such EWPT method can be applied as a stable power supply for free-positioned and free-oriented sensors or other low-power devices in an enclosed or semienclosed area. [ABSTRACT FROM AUTHOR]

Multi-functional magnetic sensors with tunable measure range can help cover different requirements from detecting weak field to sensing strong field. However, additional control system is often required to realize the tunability, which increases the complexity of device. In this work, we found the current controlled sensitivity and linear range in the NiCo2O4 thin film based anomalous hall sensor. The device owns not only simple structure but also interesting anomalous hall signal whose linearity range and sensitivity can be controlled by current. Ultrahigh sensitivity of 4900 V/(AT) in the range of ±0.2 mT and competitive sensitivity of 20 V/(AT) in the range of ±23 mT are simultaneously realized by tunning the work current. In addition, a memory switching characteristic controlled by magnetic field is further found in the device. These results show that the anomalous hall device has the potential for multifunctional compact device. [ABSTRACT FROM AUTHOR]

In a wide range of electrical applications, the requirement for noncontact measurement of weak direct currents is continuously increasing. Among all types of dc current sensors, the magnetic modulator (fluxgate) is more suitable for measuring weak dc currents due to its low noise and high stability. As the most common type, the open-loop magnetic modulator has made possible a current down to 1 mA to be measured, while the further development could be hardly made due to the zero offset. In this article, it is revealed that the difference in two-cores’ magnetic characteristics is the main root cause for the zero offset. With the subtraction loop used to describe this difference, keeping this loop symmetric could greatly weaken the zero offset. On this basis, a controlled-greed pairing strategy is proposed to control the zero offset at a rather low level by screening out two cores with similar magnetic offsets to form one magnetic modulator. Furthermore, the pairing experiment of 10 magnetic cores and the application case of 30 magnetic modulators are conducted. The results show that the pairing scheme obtained with the proposed strategy is better than the random pairing scheme in 98.863% of cases, and the average of zero offset decreases from 131.27 to $19.50 ~\mu \text{A}$ in mass production. [ABSTRACT FROM AUTHOR]

Magnetic tracking is useful in many motion tracking applications and free from the line-of-sight (occlusion) limitations that is the drawback of many popular optical tracking systems. Previously, multiaxis magnetic markers relied on time multiplex or frequency multiplex methods to separately sense inductor–capacitor (LC) coils in different axes, which introduce bandwidth or speed limitations. In this article, we propose a novel data-driven magnetic tracking approach whose markers are based on multiple LC coils in the same resonance frequency. Our approach utilizes deep learning to determine the complex flux distribution of monofrequency multiaxis magnetic markers where simulation results are the training data. Classic numerical methods struggle to achieve the same process. With this approach, we build a new magnetic tracking system that pursues multiaxis passive markers and overcomes the original tracking principle’s dead-angle limitation. With the flexibility of deep learning, we can design markers with more than three axes. Our experimental result also shows that compared to classic three-axis markers, more LC coils in different axes actually improve the tracking accuracy. Our approach not only helps build a new tracking system based on a wireless magnetic tracking principle, but can also be applied in any multiaxis magnetic tracking system. [ABSTRACT FROM AUTHOR]

Position sensing is one of the crucial parts of the active magnetic bearing (AMB) system. The printed circuit board (PCB) eddy current position sensor is a new type of position sensor for the AMB system, which makes a compact structure, high sensing quality, and is low cost. In this article, an improved driver circuit is proposed for this new sensor. The driver circuit includes an excitation circuit and signal conditioning circuits. A crystal oscillator circuit with a power stage is used to provide the excitation coil with a stable excitation source of high stability and good precision of frequency. The analog demodulation circuit is designed for signal conditioning circuits to extract the rotor displacement information from the sensing coil outputs. Compared with the state-of-art driver schemes, the proposed method reduces the circuit complexity and cost. Accordingly, the experimental results show that the designed sensor has good linearity and sensitivity, and it can ensure AMB stable operation at the rated speed. [ABSTRACT FROM AUTHOR]

Kinematic analysis of human movement is paramount for medical and working scenarios, such as rehabilitation or ergonomic evaluation of workers. Recent studies in the state-of-the-art highlight the importance of assessing the performance of M-IMUs as tools for objective kinematic analysis before exploiting them in any context. This work aims at proposing a method grounded on the use of an anthropomorphic robot, to characterize the behavior of M-IMUs for specific frequency and amplitude ranges, typical of human upper limb movements. The use of a robot allows generating controlled and repeatable angular trajectories, thus providing a gold standard to evaluate the capability of the sensors to accurately track target angular trajectories. The Root Mean Square Error is adopted as a performance indicator. An experimental validation of the proposed method is carried out on two different sets of M-IMUs. The 87.96% and 71.30% of the performed trials exhibit errors lower than 0.087 rad for the WISE and Xsens sensors, respectively. The proposed workflow can be exploited to characterize the sensor behavior for different applications as well as the sensor fusion algorithms implemented into the measurement unit. [ABSTRACT FROM AUTHOR]

Broadband transient current measurement is a basic research method in many engineering fields. Optical integrated current sensor has the advantages of small size, anti electromagnetic interference and high precision, which has become a major trend of current monitoring. However, the existing optical current sensing methods have great challenges in broadband, wide amplitude and volume miniaturization. In this paper, a new high-performance magneto-optical energy coupling sensing method based on silicon photons and magneto-optical materials is studied, and an integrated optical waveguide current sensor based on a magneto-optical thin film and a double-ring assisted Mach–Zehnder interferometer is proposed. The energy coupling between the micro-ring resonator and the magneto-optical thin film is achieved through the magneto-optical nonreciprocity effect, and the current information is obtained by modulating the output light intensity with the Mach–Zehnder interferometer. The experimental results show that the sensor has a good linearity and a large dynamic measurement range. The measurement frequency range is from10 Hz to 13.56 MHz, and the sensitivity is 2.183 mV/A. This work seeks to promote the development of optical broadband current sensors on chips. [ABSTRACT FROM AUTHOR]

This article presents a duty-cycled integrated-fluxgate (IFG) magnetic-to-digital converter for contactless current sensing. While previous works have proven high linearity, low noise, and low offset capabilities of fluxgate sensing, this work focuses on low energy operation. The mixed-signal front-end design enables energy-efficient duty cycling with a 13-bit digital integrator to retain the last converged output during sleep mode and resume searching in its vicinity upon wake up. The system achieves a ±2.4 mT measured range of magnetic fields for indirect current measurement. The hierarchical search modes achieve $10\times $ faster convergence than analog implementations. The faster readout with a peak sampling rate of 770 kS/s translates to lower compensation energy per sample. The 3-dB bandwidth of 125 kHz is 67% higher than prior IFG art, with competitive 500-nT rms noise. The test chip fabricated in 250-nm CMOS technology consumes the lowest power of known IFG works. It can be duty-cycled to save energy in low-bandwidth applications or run at peak bandwidth for low latency. [ABSTRACT FROM AUTHOR]

Rogowski current sensors play an important role in detecting the condition of electrical power substation equipment. An electromagnetic field shielding shell is necessary for some of these sensors to operate correctly, especially those with large diameters and small heights. These are used for frequency-response analysis in power transformers. In this study, the magnetic-shielding effectiveness of a normal C-type metal shell was tested and simulated. The distribution and direction of the magnetic field were analyzed using finite-element simulation calculations to reveal the reasons for its poor shielding effectiveness. It was found that the magnetic field induced by an interference current crosses the shell and enters its cavity through the gap in its inner wall. Shells with larger inner-diameter-to-height ratios have worse magnetic-shielding effectiveness. Therefore, a novel shell structure with a spiral gap is proposed here. The magnetic-shielding effectiveness of this new type of shell was analyzed by further simulations and verified in experimental tests. The results showed that a shell with a spiral gap has better shielding effectiveness when it has a long gap. In addition, the spiral gap was found not to inhibit the current-measurement function of the sensor. This provides a new approach to the design of electromagnetic shielding shells for Rogowski sensors. [ABSTRACT FROM AUTHOR]

Optical flow cytometry is used as the gold standard in single cell function diagnostics with the drawback of involving high complexity and operator costs. Magnetic flow cytometers try to overcome this problem by replacing optical labeling with magnetic nanoparticles to assign each cell a magnetic fingerprint. This allows operators to obtain rich cell information from a biological sample with minimal sample preparation at near in-vivo conditions in a decentralized environment. A central task in flow cytometry is the determination of cell concentrations and cell parameters, e.g. hydrodynamic diameter. For the acquisition of this information, signal processing is an essential component. Previous approaches mainly focus on the processing of one-cell signals, leaving out superimposed signals originating from cells passing the magnetic sensors in close proximity. In this work, we present a framework for joint cell/particle detection and analysis, which is capable of processing one-cell as well as multi-cell signals. We employ deep learning and compressive sensing in this approach, which involves the minimization of an adaptive norm. We evaluate our method on simulated and experimental signals, the latter being obtained with polymer microparticles. Our results show that the framework is capable of counting cells with a relative error smaller than 2%. Inference of cell parameters works reliably at both low and high noise levels. [ABSTRACT FROM AUTHOR]

Information encoding in barcodes using magnetic-based technology is a unique strategy to read data buried underneath non-transparent surfaces since a direct line-of-sight between the code and the reader is not required. This technology is of particular interest in secure labeling and recyclable packaging applications. However, current magnetic reading heads, such as those employed for magnetic ink character recognition (MICR), need to be placed in contact with the magnetic structures, limiting the depths at which the information can be read. This article describes a strategy to overcome that limitation by replacing the traditional inductive heads with tunnel magnetoresistive (TMR) sensors. Soft-magnetic codes can be printed using conventional LaserJet toners and, by having their magnetization set with a permanent magnet (PM) included in the device, the resulting magnetic field can be read using a TMR sensor. We demonstrate that such a device can read barcodes at depths of at least 1 mm. It can also resolve individual structures as thin as $200 ~\mu \text{m}$ when used in contact. [ABSTRACT FROM AUTHOR]

Fluxgate magnetometers have been widely applied in many fields, such as magnetic anomaly detection, e-compass, etc. In this work, a micro-fluxgate magnetometer based on the implementation of the MEMS technology is proposed. The core of the fluxgate was fabricated by using an amorphous Co-based magnetic material, which shows a good degree of linearity below 0.5 Oe. Moreover, a mixed-signal lock-in circuit was designed to drive and capture signals. Magnetic noise density of such a device was limited to the value of 500 pT/ $\surd $ Hz at 1 Hz, while the capability of sensing a DC magnetic field of 6 nT was demonstrated, which presents a good development prospect in the weak signal detection domain. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm to localize a magnetic dipole using a limited number of noisy measurements from magnetic field sensors. The algorithm is based on the theory of compressed sensing, and exploits the sparseness of the magnetic dipole in space. Beforehand, a basis consisting of magnetic dipole fields belonging to individual dipoles in an evenly spaced 3D grid within a specified search domain is constructed. In the algorithm, a number of sensors is chosen which measure all three magnetic field components. The sensors are chosen optimally using QR pivoting. Using the pre-constructed basis and the obtained field measurements, a sparse representation in the location domain is computed using $\ell _{{1}}$ optimization. Based on the resulting sparse representation, the location and magnetic moment of the magnetic dipole are estimated. An extension to an iterative method is implemented, where the basis and chosen sensors improve after every location estimate. Numerical simulations have been performed to verify the algorithm, and experiments have been done for validation. The proposed algorithm is shown to be effective in localizing magnetic dipoles. [ABSTRACT FROM AUTHOR]

In this work, an optical fiber magnetic field sensor is proposed and demonstrated based on silk fibroin hydrogel (SFH). The primary function of SFH is the carrier of material (Streptavidin magnetic nanoparticles, SMN) that is susceptible to the magnetic field. The multimode interference spectrum is obtained by configuring a single-mode -multimode -single-mode (SMS) structure. The SMS structure is consisted by sequentially connecting a single-mode fiber (SMF), a no-core fiber (NCF), and a SMF. In addition, the SMN responds to a magnetic field, and SMN will modify the effective refractive index (RI) of SFH. Hence, magnetic field sensing can be performed by coating a mixture of SMN and SFH on the SMS structure. Our experimental results show that the maximum sensitivity of the proposed sensor reaches 673.53pm/Oe, and the average sensitivity of 263pm/Oe in the magnetic field strength range from 0 to 115Oe. The proposed optical fiber sensor of the magnetic field, featuring the benefits of environmental friendliness, low cost, easy manufacturing, and simplicity of structure, can find potential application prospects in various areas such as the industry, environment, and military. [ABSTRACT FROM AUTHOR]

The shearer drum height measurement plays a crucial role in the fully mechanized mining face. This paper proposes a measurement method of drum height, taking the ranging arm swing-angle and fuselage attitude angle into consideration; therefore, compared with the existing drum height measurement methods, our approach adheres more to the actual operating conditions of the shearer. Based on our approach, we further developed a shearer drum height sensor. Firstly, TLE5012B (MEMS magnetic angle chip) and MPU6050 (MEMS inertial navigation chip) are selected as the sensing elements of swing-angle and attitude angle, respectively. Secondly, a “rocker-rotating shaft” is designed to convert the swing-angle into the rotation of TLE5012B’s external magnetic field. Thirdly, an intelligent drum height sensor based on DSP-TMS320F28335 is developed, including hardware circuits and software that measure and process the angle data, calculate the drum height, store and display the data, and transmit the data by CAN or WIFI. Fourthly, the magnetic field distribution and vibration source of the shearer are simulated and analyzed, and the magnetic shielding shell and anti-vibration device are designed to reduce the influence of external factors on the sensor. Furthermore, a sensor prototype was developed and experimentally tested. The maximum absolute errors of sensor swing-angle, pitch angle, roll angle, and drum height were 0.16°, 0.07°, 0.06°, and 6.7mm, respectively. Finally, we establish a measurement error model of shearer drum height and calculate the maximum measurement error is 2.24cm. The results show that our approach and sensor meet the requirements of shearer drum height measurement. [ABSTRACT FROM AUTHOR]

This paper proposes an eddy current testing (ECT) probe with high-resolution tunneling magnetoresistance (TMR) array sensors for vector magnetic field measurement. The probe consists of two printed circuit boards (PCBs), which are placed perpendicular to each other. Three arrays of TMR sensors are wire bonded on the two PCBs to measure the three components of the magnetic field. Each array contains 32 sensors and the distance between the centers of two adjacent sensors in an array is 0.5 mm. The 32 output signals of each array are multiplexed, amplified and filtered by using a circuit on the PCB. An experimental system is set up and aluminum samples with machined defects are imaged by the probe. It is seen that the patterns of the images along the x-, y- and z-axis are different, meaning the information in the three images can compensate each other to a certain extent. The images change their orientations if the defects are oriented along different angles. An image processing algorithm including image segmentation, normalization, edge detection and K-means classification is developed to class the defects. It is seen that the defects can be classified accurately with the algorithm. Then, the orientations of the defects are calculated from the images with a linear regression of the angles of the three axis images. It is found that the mean error of the orientation quantification is only 4.14°, which is much smaller than the mean error calculated from each axis image separately. [ABSTRACT FROM AUTHOR]

The online error compensation of the three-axis magnetic sensor is the key to a high accuracy geomagnetic assisted navigation. Traditionally, the least squares or its improved methods are used for error compensation, which are offline and need to assume that measurement errors are Gaussian. In this paper, the geomagnetic measurement error is modeled based on the error source analysis, and then the compensation parameters are converted through the ellipsoid hypothesis. To eliminate the negative effect of abnormal values, iterative least squares is designed to calculate static compensation parameters and corresponding residuals, then different weights are assigned to each geomagnetic measurement data through robust estimation. Also, to avoid data saturation phenomenon and finally complete online error compensation, a forgetting factor is introduced into the iterative least squares, and the dynamic coefficients are constructed by weights of measurement data to derive the online updated compensation parameters. Simulation and experiment results both show that the online combined compensation method possesses higher adaptability, which can eliminate the influence of abnormal data effectively. And its accuracy and stability of error compensation are better than other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

We demonstrate the fabrication of a high-sensitivity magnetic field sensor based on the packaged long-period fiber grating (LPFG) with magnetic fluid. The transmission spectra and the surrounding refractive index (SRI) characteristics of the LPFGs near the dispersion turning point (DTP) were investigated theoretically and experimentally. We have studied the influence of mode order and wavelength separation at DTP on the SRI sensitivity of the DTP-LPFG. The experimental results are consistent with the simulation. The LP0,10 mode has the highest SRI sensitivity of 1956.4 nm/RIU in the range of 1.333-1.435 when the wavelength separation at DTP is 89.1 nm. The sensor achieves a magnetic field sensitivity of 1.9 nm/mT in the magnetic field intensity range of 0-20.5 mT, which indicates that the sensor can be used as a high-sensitivity magnetic field sensor. [ABSTRACT FROM AUTHOR]

The tactile sensing capabilities of human hands are essential in daily activities. Simultaneously perceiving normal and shear forces via the mechanoreceptors integrated into the hands allow us humans to achieve daily tasks like grasping delicate objects. In this paper, we design and fabricate a biomimetic tactile sensor with skin-like heterogeneity that perceives normal and shear contact forces simultaneously. It mimics the multilayered structure of mechanoreceptors in human skin by combining an extrinsic layer (piezoresistive sensors) and an intrinsic layer (a Hall sensor) so that it can perform estimation of contact force directions, locations, and joint-level torque. By integrating our sensors, a robotic gripper can obtain contact force feedback at the fingertips; accordingly, robots can perform challenging tasks, such as using tweezers and grasping eggs. This insightful sensor design can be customized and applied in different areas of robotics and provide them with heterogeneous force sensing, potentially supporting robotics in acquiring skin-like tactile feedback. [ABSTRACT FROM AUTHOR]

This article presents an accurate method to determine the mandatory rotor position to control a permanent magnet synchronous machine from misplaced Hall-effect switch sensors. The main feature of this technique is the estimated speed from two consecutive edge transitions in the same phase to dodge the inaccurate information. Besides, when a new electrical cycle starts, a gradual compensation algorithm corrects the initial speed estimation to cancel the electrical angle error in order to prevent current distortions. Furthermore, a first-order Taylor series approximation estimates the rotor position from the compensated speed calculation, reducing the possible torque ripple and noise due to an inaccurate control strategy. The proposed method has been compared with other state-of-the-art approaches through simulation and experimental results obtained from a low-voltage powertrain, showing more straightforward implementation and delivering the best balance performance during steady-state and transient operation. [ABSTRACT FROM AUTHOR]

The control of very high switching frequency power electronic converter systems featuring latest generation wide bandgap devices requires current measurements with a very high bandwidth (BW) to achieve high closed-loop control dynamics. One example is an ultrahigh BW $\mathbf {4.8}$ MHz parallel-interleaved multilevel GaN inverter ac power source with a target large-signal output BW of $\mathbf {100}$ kHz. This work investigates the combination of commercially available low-frequency (LF) Hall-effect current sensors (BW $\mathbf {\approx 1}$ MHz) with suitable high-frequency (HF) sensors to extend the BW above $\mathbf {10}$ MHz, i.e., enough to measure the HF inductor current. Based on a conventional PCB-integrated Rogowski coil, for the HF sensor, three improved pickup coil (PUC) geometries based on proposals in the literature are investigated. The LF and HF sensor signals are combined with a precision fully differential combiner circuit. Design guidelines for the HF sensors as well as the combiner circuit are presented and thereby the influence of mismatches and tolerances is examined. The performance of the proposed HF sensors is experimentally verified and compared with previous solutions based on galvanically isolated inductor voltage sensing and a current transformer. The PUCs reach a BW $\mathbf {>50}$ MHz, which is an improvement by more than a factor of $\mathbf {50}$ compared to the fastest available Hall sensor. Furthermore, it is proven that all investigated sensors are capable to accurately measure the triangular inductor current ripple in a hardware prototype of the aforementioned ac power source. In a final step, the influence of common-mode (CM) disturbances originating from fast $\mathbf {{d}v/{d}t}$ switching transients on the sensor performance is analyzed. The presented current sensors achieve a CM rejection ratio of almost $\mathbf {100}$ dB. [ABSTRACT FROM AUTHOR]

This article investigates and assesses neutron radiation effects on attitude estimation (AE) processing, typically embedded in inertial navigation systems (INSs) and upcoming autonomous things. Findings highlight the importance of radiation-induced critical failures that can upset the on-board AE processing and consequently the inertial navigation. Radiation tests and analyses were conducted by considering as on-board AE processing the execution of classical AE algorithm on multi-core computer hardware exposed to 14-MeV neutron and thermal neutron radiation. Three computing strategies and different case-study scenarios were tested and compared. Results suggest that the contribution of radiation-induced soft errors to be mitigated on the embedded AE processing is essentially related to single-event functional interrupts (SEFIs) that can lead the inertial navigation to critical failures. [ABSTRACT FROM AUTHOR]

Oil condition monitoring is an important way to achieve mechanical equipment health assessment, condition early warning, fault diagnosis, and intelligent maintenance. A microsensor integrated with inductance-resistance and capacitance sensing units is presented, which can comprehensively detect metal debris, air bubbles, and moisture in oil based on impedance analysis. The inductance-resistance sensing unit not only detects traditional inductance parameter, but also proposes a resistance detection method based on coil to further improve the detection sensitivity for nonferromagnetic metal debris. The capacitance sensing unit can detect air bubbles, and a new moisture measurement method is also proposed. Based on the signal characteristics of inductance, resistance and capacitance detection results, the microsensor can effectively distinguish 16–500 μm iron debris, 60–500 μm copper debris, >170 μm air bubbles and moisture in oil. The ultrasensitive microsensor can obtain more oil status information, which has important value and wide engineering application prospect for modern fault diagnosis and prediction theory based on information fusion. [ABSTRACT FROM AUTHOR]

Traditional current monitoring devices (e.g. current transformers) for transmission and distribution (T&D) networks are mostly installed at substations, so real-time and accurate information on current is almost unavailable for on-site load current monitoring, imbalance assessment, and equipment maintenance. This increases the fault risk in T&D networks and degrades the reliability and quality of the power supply. To address such a situation, this study proposes an intelligent and contactless current measurement method. The proposed method uses only a small number of magnetic-field sensors and the conductor geometry specification of an overhead line obtained from utilities. The simulation results show that the proposed method can accurately calculate each phase current using only three magnetic field sensors. In addition, a scaled-down overhead line measurement system was built to test the proposed method. The experimental results verify the feasibility of the proposed contactless method for overhead-line current measurement with less than 10% maximum measurement error. [ABSTRACT FROM AUTHOR]

A parallel three-coil wear particle sensor is innovatively proposed with the detachable substrate and magnetic rings. The magnetic rings are designed and fabricated using polydimethylsiloxane (PDMS) and iron-based amorphous soft magnetic material (IASM). The excitation coils surround the magnetic rings, leaving only a 1mm air gap on the inner side (near the flow channel). The magnetic rings are magnetized under the action of the high-frequency alternating magnetic field, which forms an enhanced magnetic field with a high gradient distribution in the detection area. Through numerical simulation and experimental verification, the influence of IASM concentration, radial position and size of wear particles on the sensor output signal are studied. With the increase of IASM concentration, the sensor detection sensitivity rises dramatically. The sensor with 75% IASM magnetic rings can effectively detect 60 $\mu \text{m}$ iron particles and 160 $\mu \text{m}$ copper particles in a 10mm flow channel; the detection error rate is less than 15% in the actual lubrication circuit, which fully meets the needs of early abnormal wear fault diagnosis of mechanical equipment. Therefore, this method is a promising candidate for developing the large-flow electromagnetic wear particle sensor sensitivity. [ABSTRACT FROM AUTHOR]

A magnetostrictive tactile sensor unit with a large force measurement range and high sensitivity is designed using L-shaped Galfenol wires, tunnel magnetoresistive elements, and cylindrical permanent magnets. The output voltage model of the sensor unit is established based on the inverse magnetostrictive effect, tunnel magnetoresistance, and elastodynamic theory. Structures of the sensor unit and array are optimized using COMSOL. The static, dynamic, and temperature characteristics are tested. The interaction between the output voltages of each unit in a $3\times $ 3 tactile sensor array is described. The experimental results show that the sensitivity of the sensor unit is 85.5 mV/N at 0-10 N and 28.4 mV/N at 10-16 N under a biased magnetic field of 1.671 kA/m. The dynamic force sensitivity of the sensor unit does not vary by more than 1.4%. The magnetic field lateral coupling and longitudinal coupling of the sensor array do not exceed a maximum of 2.3%. The array can accurately distinguish the force distribution when multiple contacts are subjected to force at the same time. The sensitivity does not vary by more than 3.9% over the ambient temperature range of 23- $59~^{\circ }\text{C}$. The tactile sensor array is mounted on the mechanical fingertips to grasp bar-shaped objects with different tilt angles. The output voltage of the sensor array obtained from the robotic grasping experiments is analyzed using Probabilistic Neural Network, which can determine the tilt angle of the grasped objects, and the accuracy rate of object tilt recognition is 96.74%. [ABSTRACT FROM AUTHOR]

This work proposes an experimental configuration for a magnetic field and electric current sensor using an optical fiber in a single-mode-multimode (SM-MM) structure. The method applied is based on multimodal interference effects, where the MM fiber was coated with carbon steel. A continuous-wave laser with a 1550 nm wavelength was used to feed the sensor. The signal at the MM fiber output is captured by a photodiode in order to measure the signal in terms of voltage using a digital multimeter. The alternating magnetic field causes the carbon steel coated optical fiber to oscillate, changing its light propagation characteristics and therefore the output of the transmitted light. An increase in the signal was observed at the sensor output with increases in the magnetic field. The sensitivity of the sensor was tested by placing the coil at 2 cm and 4 cm from the fiber, reaching values of 78.13 mV/mT and 79.80 mV/mT, respectively. The relationship between the optical transmission variation and the magnetic field intensity reached a linearity of 98.297%. Notably, the method proposed in this experiment is less complex than most state-of-the-art methods. Furthermore, it presents excellent characteristics of cost, compactness and structure, with potential applications for the measurement of alternating magnetic fields and electric currents. [ABSTRACT FROM AUTHOR]

This paper proposes the rotor speed estimation of a squirrel cage induction motor fed by a sinusoidal power supply or an inverter based on the use of a Hall effect sensor installed between two stator slots of the machine. As well known in literature, inverter-fed induction motors usually contains a series of current harmonics and in case of rotor faults, such as broken bars, this operational condition becomes even more severe. The speed estimation has been extensively investigated for its use in control schemes, to compute output power or machine efficiency and particularly for fault diagnosis using motor current signature analysis. In this method, it is necessary an accurate speed estimation to prevent false positives and false negative indications. Therefore, the present research has been carried out by applying the Fast Fourier Transform and Hilbert Transform in the airgap signal measured by the Hall sensor, in order to estimate the rotational speed of the induction motor in a healthy condition and with broken rotor bars. This approach has been compared to the same signal processing techniques using the stator current phase, usually used for speed estimation in the state of the art solutions. The efficiency of this approach was evaluated from simulation and experimental tests, for motor running at distinct load torques, at very low slip conditions and considering a damaged rotor cage. The simulation and experimental results have shown a better accuracy with the measured or simulated speeds, using the airgap estimations when compared to those obtained from stator current processing. [ABSTRACT FROM AUTHOR]

When the optical fiber submarine seismometer is applied to the seabed, the direction of vibration should be compensated by heading angle. In order to meet the stringent requirements of small size and low power consumption, geomagnetic sensors are used to measure the heading angle. Due to the complexity of magnetic field interference in the seismometer, the heading angle calculated by electronic compass based on the geomagnetic sensors is not accurate. In order to improve the accuracy of heading angle, we propose a geomagnetic compensation method based on unscented Kalman algorithm, which can solve the problems of difficult calibration operation and long-term accuracy in existing magnetic compensation methods. Meanwhile, according to the environmental conditions of underwater applications, we further optimize the method to reduce the calculation amount and avoid the non-positive definite problem of some Cholesky decomposition. The experiment is carried out to validate the effectiveness of the proposed method. The results show that the heading angle errors compensated by proposed method are all within 0.5°, which meets the application requirements of fiber optic submarine seismometer. In addition, the experimental operation is simple when using the proposed method. [ABSTRACT FROM AUTHOR]

The use of helium recycling systems for magnetoencephalography (MEG) has rapidly expanded in recent years. Placing the cryocooler close to the MEG cryostat is expected to aid in achieving a high helium-recycling efficiency. However, the cryocooler typically introduces a large amount of magnetic interference in the MEG system owing to mechanical vibration, and electric and magnetic noise. In this study, we proposed a mobile reference sensor method using fluxgate magnetometers and vibration meters to reduce the noise originating from the cryocooler. We placed the MEG cryostat, which included superconducting quantum interference device (SQUID)-based MEG sensors and reference magnetometers, and a pulse-tube cryocooler inside a magnetically shielded room. We recorded the vibration and magnetic noise during the operation of the cryocooler using the vibration meters and fluxgate magnetometers placed on the cryocooler and reference SQUID magnetometers as the reference noise data. A noise reduction algorithm named time-shift principal component analysis (TSPCA) was applied to the recorded MEG sensor data by employing the reference noise data. A noise reduction ratio of –39 dB was achieved without temporal and spatial distortion of the MEG signal using an MEG phantom. Thus, we conclude that the mobile reference sensor method with the TSPCA algorithm is an effective technique for reducing the magnetic noise originating from the cryocooler. [ABSTRACT FROM AUTHOR]

The automotive industry progresses towards full electrification of cars. Therefore, more and more current sensors will be used in each car. These sensors must consume little electrical energy and be as cheap as possible due to the cost-sensitive automotive market. The latter leads to the use, where possible, of Hall-effect open-loop sensors composed of cheap magnetic materials, such as Fe-Si alloys for the magnetic circuit. Depending on the wide range of current and bandwidth of the different onboard electrical devices, each sensor has a different magnetic circuit that must be designed quickly but still accurately. This paper aims to facilitate the design work of engineers by providing them with a simulation model that can be easily used in a circuit type simulation software such as LTspice. This model can bring high-fidelity results in terms of sensor linearity and frequency bandwidth which allows the optimization of the sensor before proceeding to the prototyping step, reducing the time and costs of the design phase. [ABSTRACT FROM AUTHOR]

Air-core coil sensors are widely used in geophysical electromagnetic exploration because of their ease of production, high sensitivity, and broadband. In order to increase the bandwidth of the air-core coil without reducing the number of turns, a new type of dual-air-core coil sensor was proposed for the shallow exploration in the electromagnetic method. The design principle of the dual-air-core coil sensor was introduced, consisting of a low-bandwidth coil and a high-bandwidth coil. The output voltage of the high-frequency coil is used as a linear reference to obtain the amplitude-frequency response data of the low-frequency coil, and the fitting model is constructed to extract the equivalent inductance and distributed capacitance of the low-frequency coil, so as to realize the correction of the system response. In addition, the crosstalk model between air-core coils was established, and a method to suppress crosstalk was proposed. In order to prove the feasibility of the dual-air-core coil sensor, in-laboratory and field test platforms were set up. The experimental results show that the crosstalk between the coils can be eliminated by adjusting the relative position of the coil. The fitting method can effectively increase the bandwidth of the low-bandwidth coil, so that it exceeds the high-frequency coil used, and it is shown to have better performance. The effective area is 59.5 m2, the amplitude bandwidth of −3 dB is 200 kHz, the phase bandwidth with the error less than ±5° is 220 kHz, and the noise level is 18 fT $\cdot $ Hz $^{-1/2}$ at 1 kHz. [ABSTRACT FROM AUTHOR]