Magnetic Noise Research Articles

Research on Electromagnetic Vibration and Noise of PMSM with Unconventional Stator

Research on Electromagnetic Vibration and Noise of PMSM with Unconventional Stator

An Improved Conformal Mapping Method for Electromagnetic Vibration Analysis in PMSMs With Rotor Eccentricity

An Improved Conformal Mapping Method for Electromagnetic Vibration Analysis in PMSMs With Rotor Eccentricity

Enhanced detection performance based on a differential ME sensor with strong suppression of vibration interference

Magnetoelectric (ME) sensors have enormous potential for detecting weak magnetic fields because of their high sensitivity, low power consumption, compact size and, low cost. However, inevitable vibration interference limits their application in practical environments, especially in the case of mobile platform mounting. Here, we propose a differential ME sensor, consisting of PZT macro-fiber composites (MFCs) and Metglas laminates. The differential ME sensor has two output terminals with weak mutual mechanical coupling and works in longitudinal vibration mode. MFC cores are polarized in parallel mode to guarantee their consistency of electric characteristics and reversed bias field is provided by attached magnets. Experimental results show that the differential-mode response amplitudes have a gain of −17.6 dB for low-frequency vibration at 2 Hz and ∼6.2 dB for an applied magnetic field at 3 Hz, in comparison with the single-ended mode. In addition, our proposed ME sensor also has a low inherent equivalent magnetic noise of 18.3 pT/√Hz at 1 Hz. Finally, a target detection experiment in the presence of heavy lab noise and strong vibration interference is conducted and the improved detection performance of the proposed differential ME sensor is proved.

Methods in fluctuation (noise) spectroscopy and continuous analysis for high-throughput measurements

Abstract Fluctuation (noise) spectroscopy is widely used to investigate the low-frequency dynamics of charge carriers in condensed-matter systems, aiming to (i) improve the performance of micro- and nanoscale electronic devices and sensors, and (ii) use ‘noise as a signal’ in order to fundamentally investigate the microscopic motion and transitions of charge carriers coupled to the low-lying excitations in solids. Here, we focus on measurements of the ubiquitous 1 / f -type fluctuations, often composed by a superposition of (independent or correlated) two-level systems each giving rise to a Lorentzian spectrum, denoted random telegraph noise in the time domain. We briefly review the basic concepts of noise and fluctuations and give a comprehensive overview of state-of-the-art measuring techniques, using both commercially available signal analyzers and custom software in order to perform the spectral analysis of the recorded time signals, and critically evaluate their advantages and drawbacks. We describe how to use fast data acquisition devices in a cross-correlation setup providing additional quantitative information on the magnitude of uncorrelated instrument noise, and demonstrate the mathematical intricacies of extracting the noise spectra. We introduce a new method for high-throughput measurements by automated spectral analysis based on the concept of Continuous Analysis. We demonstrate the potential of this technique, working towards a FAIR data workflow, by measurements of magnetic flux noise within the hysteresis loop of ferromagnetic nanostructures.

Stress Evaluation of Ferromagnetic Materials Based on a New Barkhausen Noise Sensor Composed by High Entropy Alloy Magnetic Core

Abstract During the service of ferromagnetic structural steel materials, stress should be evaluated accurately. Although the magnetic Barkhausen noise (MBN) testing has the ability to sense stress, it can be easily interfered with by environment. In this paper, a new MBN sensor is fabricated by selecting FeCoNi(AlMn)0.25 high entropy alloy (HEA) as the case of magnetic core to improve the accuracy of stress evaluation. The process optimization results show that the stability of MBN signal characteristics is the largest when the excitation frequency is 4 Hz and the voltage is 6 V. The signal-to-noise ratio of MBN indicates that the HEA and Ni-Zn ferrite probes have better anti-interference capability. The MBN signal characteristic values peak voltage and root mean square measured by the HEA probe can linearly quantify the stress level with higher efficiency, stability, and accuracy. The underlying reason of high sensitivity of HEA probe to the variation of MBN signals is revealed based on the magnetic properties. The microstructure and the thermodynamic parameters are analyzed to clarify whether the additions of Al and Mn atoms can affect the short-ranged magnetic exchange interaction and lattice distortion, which affects the magnetization behavior of HEA. Finally, the availability of MBN sensor with HEA magnetic core to the stress evaluation on the retired slide rails of car seats is conducted, which demonstrates its great application value.

Disparities in screening and risk stratification for hispanic adults with metabolic dysfunction-associated steatotic liver disease.

Cut-points for non-invasive tests (NITs) for risk stratification in metabolic dysfunction-associated steatotic liver disease (MASLD) were derived from predominantly non-Hispanic populations. It is unknown if these cut-points perform adequately in Hispanic individuals. We assessed the performance characteristics of current NIT cut-points among Hispanic patients and determined whether they could be further optimized. We prospectively enrolled 244 adults with biopsy-proven MASLD. Participants underwent a research visit with magnetic resonance elastography (MRE) and vibration controlled transient elastography (VCTE). Histology and imaging assessments were conducted centrally. Diagnostic performance was evaluated by area under the receiver-operating curve (AUROC) and optimal cut-points were identified by Youden J analysis. The mean (±SD) age and body mass index were 52.6 (±13) and 31.6 (±4.6) kg/m2. Overall, 40% had diabetes, 31% (N=75) were Hispanic. 40% of Hispanic and 28.4% of non-Hispanic patients had significant fibrosis. To detect significant fibrosis, MRE and VCTE exhibited significantly lower accuracy in Hispanic versus non-Hispanic participants (AUROC: MRE, 0.87 vs. 0.98, p=0.01; VCTE, 0.78 vs. 0.92, p=0.02). Clinical care algorithms yielded high false-negative rates among Hispanic participants (14% with low-risk FIB-4 and 21% with low-risk VCTE had advanced fibrosis on biopsy). Cut-points of 2.73kPa for MRE and 6.9kPa for VCTE were optimal to detect significant fibrosis in Hispanic individuals. Findings were validated in a Latin American cohort. Lower NIT cut-points may be needed to optimize surveillance for significant fibrosis due to MASLD in Hispanic populations commensurate with their higher burden and severity of disease.

Analysis and measurement of magnetic noise for tesla shielding based on superconducting coils applied to SERF magnetometer

Tesla Shielding (TS) is closed superconducting coils composed of superconducting tape, designed to resist changing magnetic fields, thereby achieving magnetic shielding. TS, optically transparent, is suitable for integration with spin exchange relaxation-Free (SERF) magnetometers, thereby improving the sensitivity of SERF magnetometers. However, no prior research has been conducted on the magnetic noise of TS. Noise source identification was conducted on the superconducting tapes used in the TS. We modeled the magnetic noise of superconducting coils, analyzed the the relationship between geometric parameters and magnetic noise of coils, and proposed methods to suppress magnetic noise. Finally, we established a measurement system to measure the magnetic noise of superconducting coils. The results confirm the feasibility of the magnetic noise calculation model and the effectiveness of the methods for suppressing magnetic noise. This study can guide the design of TS, which is important for improving the sensitivity of SERF magnetometers.

Assessing the Temperature-Dependent Characteristics of Warm-Rolled EN8 Steel through Magnetic Barkhausen Noise Technique and Predictive Modeling with Voting Regression Technique

Assessing the Temperature-Dependent Characteristics of Warm-Rolled EN8 Steel through Magnetic Barkhausen Noise Technique and Predictive Modeling with Voting Regression Technique

Hyperfine-Enhanced Gyroscope Based on Solid-State Spins.

Solid-state platforms based on electronuclear spin systems are attractive candidates for rotation sensing due to their excellent sensitivity, stability, and compact size, compatible with industrial applications. Conventional spin-based gyroscopes measure the accumulated phase of a nuclear spin superposition state to extract the rotation rate and thus suffer from spin dephasing. Here, we propose a gyroscope protocol based on a two-spin system that includes a spin intrinsically tied to the host material, while the other spin is isolated. The rotation rate is then extracted by measuring the relative rotation angle between the two spins starting from their population states, robust against spin dephasing. In particular, the relative rotation rate between the two spins can be enhanced by their hyperfine coupling by more than an order of magnitude, further boosting the achievable sensitivity. The ultimate sensitivity of the gyroscope is limited by the lifetime of the spin system and compatible with a broad dynamic range, even in the presence of magnetic noise or control errors due to initialization and qubit manipulations. Our result enables precise measurement of slow rotations and exploration of fundamental physics.

Enhancing Mechanical Characteristics of LM9 Aluminum Alloy by Optimization of Electromagnetic Vibration Analysis

Enhancing Mechanical Characteristics of LM9 Aluminum Alloy by Optimization of Electromagnetic Vibration Analysis

Concept of Electromagnetic inerter-based vibration absorbers

Inerter is a device that generates a force proportional to the relative acceleration between its two terminals. It has recently been shown that this unusual property can offer interesting advancements and performance in the realm of vibration isolation or dynamic absorbers. However, the main developments have encountered difficulties in mechanical implementation (utilizing rotating discs and gears) or achieving high-frequency efficiency. The present study proposes to synthesize actively the dynamical behavior of an inerter in order to overcome these constraints. To address the stability issue, collocated voice coils are employed as sensors and actuators at the interface of the moving masses of the device. In a case study of a hybrid tuned vibration absorber, a first experimental demonstration illustrates the feasibility of such a concept.

Torque Ripple and Electromagnetic Vibration Suppression of Fractional Slot Distributed Winding ISG Motors by Rotor Notching and Skewing

Torque Ripple and Electromagnetic Vibration Suppression of Fractional Slot Distributed Winding ISG Motors by Rotor Notching and Skewing

Simulation of pulse width modulation strategies: validation based on sound quality evaluations

Though the noise emitted by an electrical machine is less loud than the one from a combustion engine, the existing literature shows it is not always more pleasant. This is because of its strong tonal content, due to deterministic excitations (e.g. electromagnetic slotting and switching effects, mechanical gear mesh effects). The main source of magnetic noise is the radiation of the stator submitted to electromagnetic forces, which are harmonic by nature. Their highest frequency components are generated by the Pulse Width Modulation (PWM) technique designed to vary the supply frequency and operating speed of the electric machine. Several PWM strategies exist, leading to specific harmonic spectra. A temporal simulation model has been developed to auralize the corresponding electromagnetic noise emitted by the machine, considering its mechanical and electrical parameters. A testbench has been adapted to test the relevance of the model, both from an electrical and acoustic point of view. The simulation model and the testbench can be used to generate virtual and real sound stimuli to be assessed in a jury testing. The subjective evaluations allow to assess the relevance of the auralization model, but also to identify the least annoying strategies.

High sensitivity and detectivity of anomalous Hall sensor based on coupled magnetic bilayers

Detection of ultralow magnetic field requires a magnetic sensor with high sensitivity and a low noise level. In this work, we used the Co20Fe60B20/Ti/Co20Fe60B20 magnetically coupled multilayer as the core structure of an anomalous Hall sensor. We adjusted the thickness of the Ti interlayer to modify its perpendicular magnetic anisotropy and interlayer magnetic coupling, thereby improving the sensitivity of the anomalous Hall sensor. Through the investigation of magnetic field response and noise properties of devices with different Ti thicknesses, the highest sensitivity of 34 803 Ω/T and the best magnetic field detectivity of 4.6 nT/Hz at 1 Hz were achieved with a Ti thickness of 2.0 nm at room temperature. This anomalous Hall sensor has both ultrahigh sensitivity and magnetic field detectivity, making it a good candidate for applications in detecting weak magnetic fields.

The detection of magnetic gradient aided by correlated random walk

We propose a novel method for sensing the gradient direction of a weak magnetic field overwhelmed by a noisy background through studying the correlated random walk of Brown particles that carry with magnetic moment. Using numerical simulation, we find that the snapshot of the distribution of Brown particles that touched the top surface of a cubic container provides useful information, i.e., the center of the distribution pattern will deflect towards the direction of magnetic gradient. We also find that the impact of magnetic noise can be effectively suppressed by the presence of correlation when the concentration of Brown particles is in the region of 0.2ρ0<ρ<0.7ρ0. Our findings may motivate novel scheme to identify the direction of magnetic gradient in the presence of strong noise, which is undoubtedly important for practical applications.

Critical analysis of the ULF power depression as a possible Tohoku earthquake precursor

Among electromagnetic methods of short-term earthquake prediction, an approach is being actively developed based on the phenomenon of magnetic ultra-low-frequency (ULF) power depression occurring a few days before an earthquake. In particular, a nighttime geomagnetic power depression in the band 0.03–0.05 Hz was observed approximately 5 days before the catastrophic Tohoku 2011 earthquake. To verify the reliability of this method, we performed an extended analysis using data from magnetometer arrays JMA, MAGDAS, PWING, and INTERMAGNET. The selected stations included sites close to the epicenter (<300 km) and remote points (∼10000 km). The band-integrated spectral power of nighttime magnetic noise decreased significantly from March 6–9, several days before the earthquake. However, such variations occur simultaneously not only at nearby stations but also at distant stations. During this event, the ULF power depression was caused by low global geomagnetic activity, as evidenced by the planetary index SME. Thus, the depression of geomagnetic ULF noise cannot be considered a reliable short-term precursor.

Energy Harvesting Technologies in Electric Vehicles and Applications in Sustainable Agricultural Transportation: A Review

The increasing challenges of energy depletion, environmental pollution, climate change, and agricultural transportation costs demand innovative solutions. Electric vehicles (EVs) offer a promising solution towards mitigating these issues through renewable energy sources. However, limited driving range remains a crucial barrier to their widespread adoption, particularly in environmentally friendly agricultural transportation. This review paper comprehensively analyzes energy harvesting technologies in electric vehicles and their application in agricultural transportation. The focus is on their potential to improve driving range and address the specific needs of farmers in terms of maximizing their income. Very few review articles have been published on maximum number of possibilities of harvesting energies in electric vehicles, application in agricultural transportation and future prospects for improvement. Existing and current literature was systematically reviewed on various energy harvesting techniques applicable to EVs, including solar energy harvesting, regenerative braking, aerodynamic (wind) energy recovery, and vibration energy harvesting through suspension systems which are all renewable energy sources. Their advantages, working principle, limitations, and recent advancements were critically discussed. All explored energy harvesting methods show the ability to extend EV driving range. However, solar energy and wind or aerodynamic energy harvesting in EVs are theoretically possible but still under research for practical applications due to lots of limitations. Regenerative braking and vibration energy harvesting show the most promising current applications. The Electrical or electromagnetic vibration energy harvesters produce better results over mechanical (hydraulic and pneumatic harvesters). When optimization is employed, better results were achieved. Research on the application of artificial intelligence based computer algorithms to optimize and produce the best amount of harvested energy in EVs will play a significant contribution in the adoption of EVs for sustainable agricultural transportation.

Study on the weakening of stator cogging torque of modular motors by gap offsets

Two schemes have been developed to reduce the cogging torque generated by the gap between the stator modules of the modular permanent magnet synchronous motor. These schemes involve shifting the gap position to change the phase of the cogging torque, thereby eliminating some of its components and reducing its magnitude. Finite element simulation was used to verify the cogging torque of E and C type modular motors using two different schemes. The effect of the offset gap on electromagnetic performance and motor vibration noise was also analysed. The results indicate that both schemes weaken the cogging torque without significantly affecting the electromagnetic performance of the motor or increasing vibration noise.

High Output, Biocompatible, Fully Flexible Fiber‐Based Magneto‐Mechano‐Electric Generator for Standalone‐Powered Electronics

AbstractHarvesting magnetic noise fields around power cables emerges as an attractive approach due to its potential as a renewable and ubiquitous energy source for powering wireless sensor networks (WSNs) in IoT applications, miniature electronics, and implantable medical devices. Flexible polymer‐based magneto‐mechano‐electric (MME) generators gain attention for their effectiveness in magnetic energy harvesting owing to their durability and flexibility. In this study, a lead‐free, flexible MME generator is developed by using Polyvinylidene fluoride (PVDF)‐Aluminium nitride (AlN)‐nanofiber composites fabricated via electrospinning with different AlN compositions and integrated with a magnetostrictive Metglas layer that offers self‐bias characteristics. The MME generator is modeled using COMSOL Multiphysics to analyze the magnetic flux density distribution over the Metglas surface and the piezoelectric effect of the nanofiber composites, with the simulation results aligning well with the experimental data. The optimized, flexible MME generator, incorporating 15 wt.% of AlN in the PVDF/Metglas composite, achieves an open‐circuit voltage of 18.5 V and a power density of 0.93 mW‐cm−3 when exposed to an Alternating Current (AC) magnetic noise field of 6 Oe at a resonance frequency of 50 Hz. The generated power is sufficient to operate LEDs and sensor. This newly developed lead‐free, flexible MME generator shows significant promise for advanced applications in self‐powered WSNs.

Stress Engineering of Magnetization Fluctuation and Noise Spectra in Low-Barrier Nanomagnets Used as Analog and Binary Stochastic Neurons.

A single-domain nanomagnet, shaped like a thin elliptical disk with small eccentricity, has a double-well potential profile with two degenerate energy minima separated by a small barrier of a few kT (k = Boltzmann constant and T = absolute temperature). The two minima correspond to the magnetization pointing along the two mutually anti-parallel directions along the major axis of the ellipse. At room temperature, the magnetization fluctuates randomly between the two minima, mimicking telegraph noise. This makes the nanomagnet act as a "binary" stochastic neuron (BSN) with the neuronal state encoded in the magnetization orientation. If the nanomagnet is magnetostrictive, then the barrier can be depressed further by applying (electrically generated) uniaxial stress along the ellipse's major axis, thereby gradually eroding the double-well shape. When the barrier almost vanishes, the magnetization begins to randomly assume any arbitrary orientation (not just along the major axis), making the nanomagnet act as an "analog" stochastic neuron (ASN). The magnetization fluctuation then begins to increasingly resemble white noise. The full width at half maximum (FWHM) of the noise auto-correlation function decreases with increasing stress, as the fluctuation gradually transforms from telegraph noise to white noise. Consistent with this trend, the noise spectral density exhibits a 1/fβ spectrum (at high frequencies) with β decreasing from 2.00 to 1.88 with increasing stress. Stress can thus not only reconfigure a BSN to an ASN, which has its own applications, but it can also perform "noise engineering", i.e., tune the auto-correlation function and power spectral density, having applications in signal processing.