Tunnel Magnetoresistance Sensors Research Articles

Current Measurement for Curved Conductor based on 3-D Coreless TMR Sensor Array

Magnetic sensor arrays have been widely used in current measurement due to their advantages of small size, low power consumption, high sensitivity, wide bandwidth, and large dynamic range. However, researches in recent years all assume that the conductor is long-straight, while in actual engineering the conductor is usually curved. And the error introduced by curvature has not been searched until now. In this paper, a correction method based on circular 3D magnetic sensors array is proposed. The simulation results show theoretically that the method can greatly reduce the error. 3-D tunnel magnetoresistance (TMR) chip is selected as the magnetic sensors of the circular array in laboratory experiment, and the experiment errors can be reduced to around 1%. The simulation and experiment results verify that the correction method can improve the accuracy of the current measurement.

Non-contact measurement of traveling wave of overhead transmission line

This study proposes a non-contact measurement technique for traveling waves in overhead high-voltage transmission lines. To provide an accurate, efficient, and reliable measurement of the overhead transmission lines, the proposed method utilizes tunnel magnetoresistance sensor arrays that do not require information about the line parameters to evaluate and measure the traveling waves of the overhead transmission line. Further, it diagnoses the operation status of the overhead transmission line by enhancing the system reliability. An experiment is performed to test the feasibility and reliability of the proposed method compared with conventional current transformers. The simulation results demonstrate that the proposed method performs satisfactorily with respect to providing a reliable, cost-effective, and accurate measurement of the traveling waves of overhead transmission lines.

Tunneling Magnetoresistance DC Current Transformer for Ion Beam Diagnostics.

In this paper, open loop and closed loop Tunneling Magnetoresistance (TMR) DC Current Transformers (DCCTs) for ion beam diagnostics are presented. The DCCTs employ MR sensors to measure the DC component of the accelerator’s ion beam. A comparative study between Giant Magnetoresistance (GMR) and TMR sensors is presented to illustrate the sensor selection criterion for the DCCT application. The two proposed DCCTs are studied in open and closed loop configurations. A closed loop feedback electronic system is designed to generate a feedback current equivalent to the ion beam current such that the sensor operates at zero flux. Furthermore, theoretical and experimental results for the TMR-based DCCT including noise analysis are presented for both open loop and closed loop configurations. Both configurations’ minimum detectable currents are in the range of microampere. The proposed closed loop hardware prototype has a settling time of less than 15 μs. The measured minimum detectable currents for the open and closed loop TMR-based DCCTs are 128.2 μA/ and 10.14 μA/ at 1 Hz, respectively.

Tuning the linear field range of tunnel magnetoresistive sensor with MgO capping in perpendicular pinned double-interface CoFeB/MgO structure

A double-interface CoFeB/MgO perpendicular tunnel magnetoresistance (p-TMR) structure has been proposed as a solution to improve the thermal stability of perpendicular magnetic tunnel junction (MTJ)-based devices. In this paper, we have investigated the performance of TMR film stacks by varying the thickness of the MgO cap layer. The resistance area (RA) product and TMR ratio are characterized using a current-in-plane tunneling system. Structural and physical analyses are performed using transmission electron microscopy and a superconducting quantum interference device. It is found that the sensing layer is able to exhibit a linear output and sensitivity up to 0.25% MR/Oe as the thickness of the MgO cap layer is lowered to 0.7 nm. The RA product increases as the thickness of the MgO cap layer decreases under 0.8 nm, which is attributed to oxidization of the CoFeB layer. This research provides a valuable direction to the optimization of double-interface CoFeB/MgO p-TMR and the sensor design in terms of linear magnetic field range and sensor RA product target for sensor applications.

Harmonic Detection System and Identification Algorithm for Steel Pipeline Defects

Aiming at the problem of defects detection of steel pipeline, a harmonic detection system was developed based on electromagnetic principle, and the target signal identification algorithm was studied. The Advanced RISC Machine (ARM) Cortex-M3 was adopted to design digital adjustable harmonic excitation source, and its effective output power can up to 70 W. The Field Programmable Gate Arrays (FPGA) and ARM Cortex-M4 were introduced to design 15 channels high speed data collector, which parallel local-storage rate of each channel can reach 4.7 kHz. The electromagnetic focusing excitation array and Tunnel Magneto Resistance (TMR) sensors array were constructed to improve the spatial resolution of the detection system. Meanwhile, the system also integrated GPS positioning and LCD real-time display functions. Furthermore, the algorithm combining Empirical Mode Decomposition (EMD) and variable-scale Stochastic Resonance (SR) was proposed to process signal and enhance the targets. The effectiveness of the instrument and algorithm are well verified in both simulation and experiment. The results show that this method has higher integration and better detection effect, which provides a novel method for non-contact detection of metal material defects and is suitable for engineering applications.

Magnetoresistive sensor detectivity: A comparative analysis

We report on the noise performance characteristics of magnetic sensors using both magnetic tunnel junction (MTJ) and giant magnetoresistance (GMR) elements. Each sensor studied has a notably different noise and detectivity. Of the sensors we measured, those based on GMR multilayers have the lowest noise and detectivity. However, the GMR sensor also has a significantly smaller linear range. To make a direct comparison between sensors, we scale the linear operating ranges of each sensor to be the same. This is the phenomenological equivalent of modifying the flux concentration. Upon scaling, the low frequency detectivity of the tunneling magnetoresistance (TMR) sensors becomes essentially equal to that of the GMR sensor. Using the scaling approach, we are able to place the detectivity in the context of other key parameters, namely, size and power consumption. Finally, we use this technique to examine the upper limit for magnetoresistive sensor performance based on a notional MTJ sensor using present record setting TMR values.

A performance improved ACFM-TMR detection system with tradeoff denoising algorithm

This paper presents a novel alternating current field measurement (ACFM) system, which is realized by tunneling magnetoresistive (TMR) sensors and a tradeoff (TO) wavelet denoising algorithm. The TMR sensor is characterized with a high sensitivity of 30 mV/V/Oe and a self-noise of less than 9pT/√Hz at driving frequency f = 3 kHz. TO algorithm is proposed to select the optimum combination of mother wavelet family and decomposition level. The combinations of wavelet Db5 with decomposition level 8 and Sym7 with decomposition level 8 are determined as the most suitable ones for x- and z-axis signal denoising respectively, which have been demonstrated to be better than the traditional low-pass filtering method. Finally, the efficiency of the proposed system is proved by an experiment under more pressing test conditions, for example, with increased lift-off distance of 10 mm. In particular, it leads to increased SNR (signal-to-noise ratio) by 25.5 dB and 16.5 dB for x- and z-axis ACFM signal, respectively.

A Smart Primary Pad With Integrated TMR Sensors for Wirelessly Charged EVs

In this article, a simple and efficient sensing mechanism, using tunneling magnetoresistance (TMR) sensors and a measurement scheme is presented to enable the primary pad to automatically detect and identify the secondary pad in an electric vehicle (EV). In wirelessly charged EVs, a primary pad that can interoperate with different types of secondary pads is highly beneficial. A bipolar pad (BPP) primary can be configured to transfer power to a circular pad (CP) or a double-D pad (DDP) secondary. In the proposed system, during the sensing phase, the primary pad is excited at a very low current ( $k$ ) is clearly observed. This reduces the primary current considerably. In addition, the magnitude of the primary magnetic field is modulated/changed due to the magnetic field of the secondary. When a DDP secondary is present above the primary, a slight yet repeatable change is seen in the primary magnetic field due to the modulation, while the frequency bifurcation is not seen as the $k$ is very low. The simulation and experimental studies show that these features can be used to reliably detect and identify the type of secondary pad. In the prototype developed, TMR sensors are integrated at the optimal locations on the primary pad to sense the change in the magnetic flux density. In addition, the prototype pad and sensor system developed distinguishes between the metallic body and the secondary pad so that an accidental turning on of the primary pad can be avoided. The results, from the laboratory prototype built and tested in detail, validate the functionality and usefulness of the proposed scheme.

Real-time magnetocardiographic measurement using tunnel magneto-resistive sensors

Real-time magnetocardiographic measurement using tunnel magneto-resistive sensors

An Ill-Conditioned Optimization Method and Relaxation Strategy of Landweber for EMT System Based on TMR

The sensitivity distribution of the electromagnetic tomography (EMT) system based on tunneling magnetoresistance (TMR) is quite different from the traditional coil measurement EMT system due to the change of detection sensor. The sensitivity of the TMRs-EMT system is higher only near the TMR sensors but lower at other locations in the region of interest, which results in a more serious ill-conditioned problem of image reconstruction. Focusing on the ill-conditioned problem, the Landweber algorithm is optimized by using an appropriate weight and an appropriate relaxation strategy in this article. By verifying the consistency of variation of the spectral radius of the iterative matrix and variation of condition number for the Landweber method, a new weight matrix is introduced for the general Landweber method to reduce the condition number. On this basis, an optimal relaxation factor is determined based on the principle of minimizing the spectral radius of the newly derived iterative matrix. By comparing the imaging results of the new method with the Landweber with a relaxation factor of 1, it can be seen that the average correlation coefficient with the new approach for the five models used in this article is 0.8466, which is much higher than 0.7633 of the Landweber with a relaxation factor of 1. Meanwhile, the proposed method has a faster imaging speed. The convergence analysis of the two methods shows that the new relaxation factor determination strategy can overcome the semiconvergence problem of Landweber.

Close-Range Electromagnetic Tracking of Pulse Induction Search Coils for Subsurface Sensing

In this article, we investigate a specific search coil tracking problem arising from the use of electromagnetic induction (EMI) sensors to classify buried low metal objects. In the proposed approach, a moving search coil is used as a magnetic field beacon, two triaxial tunnel magnetoresistance (TMR) sensors are used as anchors, and the extended Kalman filter (EKF) is used to estimate five degrees of freedom information on coil’s relative pose. A specific feature of the analyzed application is the pulsed beacon field and the coil’s size comparable to the tracking distance. To address the resulting near-field effects and improve the tracking accuracy, we include a rigorous analytical multiloop model of the search coil into the EKF estimation algorithm and introduce a novel sensor calibration scheme. The system is experimentally validated in realistic dynamic conditions using a handheld pulse induction metal detector as a beacon, and a laboratory-grade optical tracking system with declared sub-millimeter accuracy as a source of ground truth data. For a near-horizontal zigzag scan pattern within a volume of $\sim \,\,40\times 50\times 5$ cm, our system yields mean absolute errors x- and $y$ -coordinates, $z$ -coordinates, and <0.5° for the pitch and roll angles, making it a viable solution for pose-referenced EMI sensing.

Simulation and Design of DC Sensor Based on Tunnel Magnetoresistance

In order to measure the DC current measurement, a method of current measurement and interference error elimination based on tunnel magnetoresistance (TMR) DC sensor is established. Firstly, the basic principle of TMR sensor is described, and its open-loop transfer function is derived, and the parameter variables related to its open-loop gain are analyzed; an adaptive filtering algorithm based on least mean squares (LMS) is proposed to detect the magnetic induction intensity. Taking three magnetic sensors as an example, the magnetic field estimation value under this condition is calculated. Finally, the correctness and effectiveness of the design method are verified by simulation.

Magnetic Imaging of Sludge Outside Steam Generator Tube With Array Magnetoresistance Sensors

The water impurities and corrosion products of the nuclear power plant structure form sludge outside the steam generator tube (SGT), which decreases the energy exchange efficiency resulting in tremendous economic loss and may lead to serious defects posing a threat to the safe operation. Thus, it is critical to efficiently inspect the deposition of sludge outside SGT. This work reveals that the sludge sample of a nuclear power plant has little conductivity and relative permeability about 2.88. Based on the electromagnetic properties of the sludge, we proposed a novel probe with array tunnel magnetoresistance (TMR) sensors for inspection of magnetic field disturbed by the presence of sludge outside the SGT. The principle of the method and the parameters of the probe were studied using a 3D finite element method (FEM) model. It is seen that the signal amplitude of the offset sensor configuration is stronger than that of the probe with non-offset sensor setup and the offset design avoids the disadvantage of non-sensitive to symmetry sludge. Further, it is observed that the sludge inspection performance is better at a lower excitation frequency, i.e. 1 kHz. The TMR sensors provide superior image quality at the low excitation frequency. A prototype probe is manufactured and tested. Sludge samples prepared according to the realistic fouling scenarios in steam generator were tested by the probe. The experimental results validate the feasibility of the probe and demonstrate the advantage of enhancing signal to noise ratio (SNR) of imaging by suppressing the background signal of tube support plate structure under the low excitation frequency.

Magnetic, magnetoresistive and low-frequency noise properties of tunnel magnetoresistance sensor devices with amorphous CoFeBTa soft magnetic layers

Magnetic field sensors using the tunnel magnetoresistance (TMR) effect require linear resistance–magnetic field (R–H) response curves with small hysteresis, for which the soft magnetic property of the free layer (FL) is critical. In this work, we investigated amorphous CoFeBTa (CFBT) as a soft magnetic layer of the FL of CoFeB/MgO/CoFeB-based magnetic tunnel junctions in view of magnetic, TMR, and low-frequency noise properties. A two-step annealing process enabled an orthogonal magnetization configuration between the FL and the reference layer, by which linear R–H curves with small hysteresis were realized. The change in the shape of the R–H curve depending on annealing temperature is explained by the Stoner–Wohlfarth model. The highest TMR ratio of ∼160% and sensitivity of ∼70%/mT were obtained with a CFBT (20 nm)/Ta (0.3 nm)/CoFeB (3 nm) FL. The noise of the TMR devices are dominated by 1/f noise below ∼10 kHz in frequency, which limits the detectivity (D) of the magnetic field of the sensor. The sensor devices patterned to 50 µm diameter circular shapes showed a minimum D of ∼2 nT/ at 10 Hz, which is superior to the previously reported values for the TMR sensors with NiFe soft magnetic layers.

Spintronic Sensors Based on Magnetic Tunnel Junctions for Wireless Eye Movement Gesture Control.

The tracking of eye gesture movements using wearable technologies can undoubtedly improve quality of life for people with mobility and physical impairments by using spintronic sensors based on the tunnel magnetoresistance (TMR) effect in a human-machine interface. Our design involves integrating three TMR sensors on an eyeglass frame for detecting relative movement between the sensor and tiny magnets embedded in an in-house fabricated contact lens. Using TMR sensors with the sensitivity of 11mV/V/Oe and ten <1 mm3 embedded magnets within a lens, an eye gesture system was implemented with a sampling frequency of up to 28 Hz. Three discrete eye movements were successfully classified when a participant looked up, right or left using a threshold-based classifier. Moreover, our proof-of-concept real-time interaction system was tested on 13 participants, who played a simplified Tetris game using their eye movements. Our results show that all participants were successful in completing the game with an average accuracy of 90.8%.

The Broken Wires Identification of Wire Rope Based on Multilevel Filtering Method Using EEMD and Wavelet Analysis

In view of the shortcomings of current wire rope magnetic flux leakage (MFL) detection devices such as large size and low sensitivity, as well as the poor noise reduction effect of MFL data and the low recognition rate of defects, this paper designs a wire rope three-dimensional MFL detection device based on unsaturated magnetic excitation (UME) and proposes a multilevel filtering algorithm. Six types of small gap broken wire defects can be effectively detected by the three-dimensional tunnel magnetoresistive sensor array. The multilevel filtering method based on EEMD and optimal wavelet is applied to three-dimensional UME signal processing, effectively suppressing noise interference. And color processing technology is applied to enhance the characterization of the defect images. A support vector machine recognition network based on the color moment feature vector as input is designed to classify broken wire defects, and the quantitative recognition rate of 98.572% is achieved when the limit error is 0.901%. The experimental results show that the detection device has the advantages of high sensitivity and simple structure and can collect MFL information in three directions, and the filtering algorithm effectively improves the signal-to-noise ratio and can realize the preliminary quantification of broken wire defects.

Imaging of Magnetic Nanoparticles Using Small TMR Sensor With an Excitation-Compensation Scheme

Magnetic nanoparticle imaging (MPI) is an emerging non-invasive technique with potential applications in bio-medical diagnostic and material science. In this paper, we propose a new method for MPI using tunnel magnetoresistance (TMR) sensor with an area of dimensions 0.45 mm*0.45 mm. The small size of the sensor promotes high level of integration and fine spatial resolution for magnetic field measurements. A solenoid excitation coil carrying alternating current is used to magnetize the magnetic nanoparticles (MNPs). We used commercial MNPs solution named synomag ®-D with iron concentration 10 mg/ml as sample. The response of the MNPs is measured by the TMR sensor during a 2D raster scan resulting in a magnetic image. In order to eliminate the negative effect of the strong background field from the excitation coil, a compensation coil which is located close to the TMR sensor is utilized to subtract the background signal in situ during measurements. Comparing the experimental results with and without the compensation scheme shows that the setup with the compensation coil cancels 95% of the background signal and increases the signal to noise ratio (SNR) from 7 dB to 10 dB. Mainly considering the tradeoff of 1/${f}$ noise and the MNPs response to the excitation frequency, the operating frequencies of 135 Hz, 235 Hz and 335 Hz were investigated in this study. Experimental results show that the system is capable of imaging $5~\mu \text{L}$ MNPs solution with a 5 mm lift-off from the sensor to the top surface of the MNPs sample. Furthermore, an `L' shape formed by 6 holes with $1~\mu \text{L}$ MNPs solution in each is imaged by the system. In comparison, it is very challenging for conventional MPI with coils as pickup sensors to image $10~\mu \text{g}$ irons in $1~\mu \text{L}$ MNPs solution at the low operating frequency. This is because TMR sensor has much better sensitivity than coils in the low frequency range. This work demonstrates the feasibility of using small TMR sensor with an excitation-compensation scheme for MPI. The advantages of high sensitivity, fine spatial resolution and low cost of the probe make it a promising alternative for future bio-medical research to measure the 3-D location and concentration of magnetic nanoparticles.

Equivalent Magnetic Noise Analysis for a Tunneling Magnetoresistive Magnetometer

Tunneling magnetoresistive (TMR) magnetic sensors are broadly applied in various fields. However, to further improve the limit of detection (LOD), it is highly desirable to realize and calculate the noise limits of such sensor systems. Thus, techniques for noise elimination can be developed. In this paper, we propose an equivalent magnetic noise model to describe the LOD of a TMR magnetometer by considering intrinsic noise sources in the TMR sensing element and readout electronics. According to the model, the contribution of each noise source can be directly obtained. Therefore, the LOD of the magnetometer can be established theoretically. Moreover, the predicted detectivity of 390 pT/ $\surd $ Hz is also demonstrated by the experimental results. The model is applicable to all kinds of TMR sensors with a “Wheatstone bridge” configuration.

Common-Mode (CM) Current Sensor Node Design for Distribution Grid Insulation Monitoring Framework Based on Multi-Objective Optimization

Insulation monitoring is essential in maintaining distribution grid reliable operation and common-mode (CM) current is an effective indicator for insulation deterioration of electrical assets. Traditional CM current measurement relies on current transformers or sensors physically connected to transmission buses, which suffers from low accuracy due to accompanied load current disturbance. This article presents an innovative CM current sensor node for insulation monitoring framework of power distribution systems based on magnetic field analysis. A CM current measurement model is developed based on formal magnetic field solution and device design is characterized as a multiobjective optimization problem solved by Pareto envelop-based selection algorithm. A prototype is presented with tunneling magnetoresistive sensor and experiments on power cable CM current measurement are implemented. Compared with conventional measurement devices, proposed sensor node realizes high-accuracy CM current monitoring in a more flexible and cost-effective manner.

Fastener Tilt Assessment Based on Magnetic Field Image Obtained With Array Tunnel Magnetoresistance Sensors

Assessing the tilt of fasteners in lap joints is crucial in the aviation industry to maintain the reliability of structures. However, low-cost, portable, and fast inspection tools are still lacking. This work investigates a novel probe with array tunneling magnetoresistance (TMR) sensors for tilt assessment. The operating principle of the probe is based on electromagnetic induction, where eddy currents are induced in the conductive sample, and then, the magnetic field images are recorded by the TMR sensors. The magnetic field images are symmetry for nontilt fasteners and asymmetry for tilt ones. This image symmetric is exploited for tilt measurement. A finite-element method model is employed to investigate the feasibility of the method, based on which an image-processing algorithm has been developed and a feature named asymmetry parameter D is extracted. It is found that D is monotonicity related to the altitude of tilt. A prototype probe, including 64 integrated TMR sensors and rectangular excitation coils, has been developed and tested. The sensors are microfabricated and then wire-bonded on a printed circuit board. The spatial resolution of the image obtained by the array sensors is as fine as 0.5 mm. Experiment results show that the probe can discriminate fasteners that tilt in any orientations from well-mounted ones. The probability of detection and the probability of false alarm are 90.9% and 13.1%, respectively, for a fastener with tilt altitude difference 0.27 mm along the scan direction. Due to its low-cost and fast inspection speed, this method is an economical and efficient alternative tool in aircraft manufacture and maintenance for fastener tilt assessment.