Research on Magnetically Coupled Resonant Detection Method for Breakpoint of Four Mesh Grounding Grid

Magnetically coupled resonant technology is a novel method for solving the breakpoint locating of power grounding grid.But the method can only detect breakpoints of a single mesh grounding grid at present.In this paper,a magnetically coupled resonant detection method for four-hole grounding grid breakpoint is proposed.Firstly,the equivalent circuit model of the four mesh grounding grid with two types of breakpoints,namely edge branch and intermediate branch,is established.The input impedance and phase angle of the system are obtained by analyzing the equivalent capacitance and equivalent resistance in the model.Secondly,the magnetically coupled resonant physical process of grounding grid faults is solved via HFSS software.The magnetic field intensity and phase frequency characteristic curves of four mesh holes with different branches and positions of breakpoints and different corrosion degrees are studied,and an experimental system is built to verify the feasibility.The results show that under the condition of grounding grid buried depth of 0.5 m and input frequency of 1~15MHz,and there is an inverse relationship between equivalent capacitance and distortion frequency,the phase angle is positively correlated with the degree of corrosion of grounding grid,and the error of signal distortion frequency can be positioned at 5%.This paper provides some ideas for the application of magnetic coupling grounding grid detection technology.

Vector magnetometry in zero bias magnetic field using nitrogen-vacancy ensembles

The application of the vector magnetometry based on nitrogen-vacancy(NV)ensembles has been widely investigatedin multiple areas.It has the superiority of high sensitivity and high stability in ambient conditions with microscale spatialresolution.However,a bias magnetic field is necessary to fully separate the resonance lines of optically detected magneticresonance(ODMR)spectrum of NV ensembles.This brings disturbances in samples being detected and limits the rangeof application.Here,we demonstrate a method of vector magnetometry in zero bias magnetic field using NV ensembles.By utilizing the anisotropy property of fluorescence excited from NV centers,we analyzed the ODMR spectrum of NVensembles under various polarized angles of excitation laser in zero bias magnetic field with a quantitative numerical modeland reconstructed the magnetic field vector.The minimum magnetic field modulus that can be resolved accurately is downto~0.64 G theoretically depending on the ODMR spectral line width(1.8 MHz),and~2 G experimentally due to noisesin fluorescence signals and errors in calibration.By using 13C purified and low nitrogen concentration diamond combinedwith improving calibration of unknown parameters,the ODMR spectral line width can be further decreased below 0.5 MHz,corresponding to~0.18 G minimum resolvable magnetic field modulus.

One Step Quick Detection of Cancer Cell Surface Marker by Integrated NiFe-based Magnetic Biosensing Cell Cultural Chip

RGD peptides has been used to detect cell surface integrin and direct clinical effective therapeutic drug selection. Herein we report that a quick one step detection of cell surface marker that was realized by a specially designed NiF e-based magnetic biosensing cell chip combined with functionalized magnetic nanoparticles. Magnetic nanoparticles with 20-30 nm in diameter were prepared by coprecipitation and modified with RGD-4C, and the resultant RGD-functionalized magnetic nanoparticles were used for targeting cancer cells cultured on the NiF e-based magnetic biosensing chip and distinguish the amount of cell surface receptor-integrin.Cell lines such as Calu3, Hela, A549, CaF br, HEK293 and HUVEC exhibiting different integrin expression were chosen as test samples. Calu3, Hela, HEK293 and HUVEC cells were successfully identified. This approach has advantages in the qualitative screening test. Compared with traditional method, it is fast, sensitive, low cost,easy-operative, and needs very little human intervention. The novel method has great potential in applications such as fast clinical cell surface marker detection, and diagnosis of early cancer, and can be easily extended to other biomedical applications based on molecular recognition.

Research of the Phase Sensitive Detection Property of Magnetic Sensor Based on Hall Effect

Aim to detect the characteristic weak magnetic field signal against the strong noises background. Methods In combination with a low-pass-filter, the correlation output of magne-* tic sensors between the magnetic field and reference current was utilized to provide a DC output voltage proportional to the applied magnetic induction, computer simulation was* done to investigate the correlation output of the Hall-effect sensors. Results Some analysis results concerning the noise property, harmonic supppression and the sensitivity were given. Conclsion The minimum detection signal of the equipment evolved from the mentioned cor-* relation theory can be 10-6 T. In addition to the DC output, such sensors can also measure the phase of the detected magnetic induction and has good harmonic suppression as well as* noise elimination.

Magnetic Detection Method for Seabed Cable in Marine Engineering Surveying

The detection and identification of the seabed cable is becoming an important task in the marine engineering. The features of the magnetic anomaly can be used to detect the existence of the seabed cable. The magnetic field model is presented, and the consistency of the magnetic anomaly distribution between the simulation of the model and the observed data is verified. The comparison shows that the seabed cable can be effectively detected and identified with reasonable method.

Single-channel vector magnetic information detection method based on diamond NV color center

A method of detecting the single channel triaxial magnetic field information based on diamond nitrogen-vacancy(NV)color center is introduced.Firstly,the incident angle of the bias magnetic field which can achieve the equal frequency difference optically-detected magnetic resonance(ODMR)spectrum of diamond NV color center is calculated theoretically,and the triaxial magnetic information solution model is also constructed.Secondly,the microwave time-controlled circuit module is designed to generate equal timing and equal frequency difference microwave pulse signals in one channel.Combining with the optical detection magnetic resonance technology,the purpose of sequentially locking and detecting the four formant signals on one side of the diamond NV color center(m_(s)=-1 state signal)is achieved,and the vector magnetic field information detection is accomplished by combining the triaxial magnetic information solution model.The system can obtain magnetic field detection in a range of 0 mT-0.82 mT.The system's magnetic noise sensitivity is 14.2 nT/Hz^(1/2),and the deviation angle errors of magnetic field detectionθ_(x) andθ_(y) are 1.3° and 8.2° respectively.

Experimental investigation of vector static magnetic field detection using an NV center with a single first-shell ^(13)C nuclear spin in diamond

We perform a proof-of-principle experiment that uses a single negatively charged nitrogen–vacancy（NV） color center with a nearest neighbor ^13C nuclear spin in diamond to detect the strength and direction（including both polar and azimuth angles） of a static vector magnetic field by optical detection magnetic resonance（ODMR） technique. With the known hyperfine coupling tensor between an NV center and a nearest neighbor ^13C nuclear spin, we show that the information of static vector magnetic field could be extracted by observing the pulsed continuous wave（CW） spectrum.

Edge detection of magnetic tile cracks,based on wavelet

In order to extract the defect edge information on the magnetic tile surface with low contrast and textured background,an edge detection algorithm based on image weighted information entropy and wavelet modulus maxima is proposed.At first,a new Butterworth high pass filter(BHPF) with adaptive cutoff frequency is produced,because the clarity and complexity of the textured background are described by the weighted information entropy of the image gradient variance quantitatively,and the filter can change its parameters through matching the non-linear relationship between the information entropy and the cutoff frequency.And then,the best decomposition scale is obtained by the level determination function to prevent edge information from missing.At last,edge points are got by double threshold after obtaining the wavelet modulus maxima,and then the edge image is linked by the edge points to ensure the edge continuity and veracity.Experiment results indicate that the proposed algorithm outperforms the conventional Canny and Sobel algorithm,and the edge detection algorithm can also detect other defects,and lays the foundation for defecting auto- recognition.

A method and device for online magnetic resonance multiphase flow detection

Most multiphase flow separation detection methods used commonly in oilfields are low in efficiency and accuracy,and have data delay.An online multiphase flow detection method is proposed based on magnetic resonance technology,and its supporting device has been made and tested in lab and field.The detection technology works in two parts:measure phase holdup in static state and measure flow rate in flowing state.Oil-water ratio is first measured and then gas holdup.The device is composed of a segmented magnet structure and a dual antenna structure for measuring flowing fluid.A highly compact magnetic resonance spectrometer system and intelligent software are developed.Lab experiments and field application show that the online detection system has the following merits:it can measure flow rate and phase holdup only based on magnetic resonance technology;it can detect in-place transient fluid production at high frequency and thus monitor transient fluid production in real time;it can detect oil,gas and water in a full range at high precision,the detection isn’t affected by salinity and emulsification.It is a green,safe and energy-saving system.

Composite excitation multi-extension direction defect magnetic flux leakage detection technology

In the traditional pipeline magnetic flux leakage(MFL)detection technology,circumferential or axial excitation is mainly used to excite the magnetic field of defects.However,the domestic and foreign pipeline detection devices currently in operation are mainly axial excitation MFL detection tools,in which circumferential cracks can be clearly identified,but the detection sensitivity of axial cracks is not high,thus forming a detection blind zone.Therefore,a composite excitation multi-extension direction defect MFL detection method is proposed,which can realize the simultaneous detection of axial and circumferential defects.On the basis of the electromagnetic theory Maxwell equation and Biot Savart law,a mathematical model of circumferential and axial magnetization is firstly established.Then finite element simulation software is used to establish a model of a new type of magnetic flux leakage detection device,and a simulation analysis of crack detection in multiple extension directions is carried out.Finally,under the conditions of the relationship model between the change rate of leakage magnetic field and external excitation intensity under unsaturated magnetization and the multi-stage coil magnetization model,the sample vehicle towing experiment is carried out.The paper aims to analyze the feasibility and effectiveness of the new magnetic flux leakage detection device for detecting defects in different extension directions.Based on the final experimental results,the new composite excitation multi extension direction leakage magnetic field detector has a good detection effect for defects in the axial and circumferential extension directions.

Giant magneto-impedance sensor with working point selfadaptation for unshielded human bio-magnetic detection

Background Compared with traditional biomagnetic field detection devices,such as superconducting quantum interference devices(SQUIDs)and atomic magnetometers,only giant magneto impedance(GMI)sensors can be applied for unshielded human brain biomagnetic detection,and they have the potential for application in next-generation wearable equipment for brain-computer interfaces(BCIs).Achieving a better GMI sensor without magnetic shielding requires the stimulation of the GMI effect to be maximized and environmental noise interference to be minimized.Moreover,the GMI effect stimulated in an amorphous filament is closely related to its working point,which is sensitive to both the external magnetic field and the drive current of the filament.Methods In this paper,we propose a new noise reducing GMI gradiometer with a dual-loop self-adapting structure.Noise reduction is realized by a direction-flexible differential probe,and the dual-loop structure optimizes and stabilizes the working point by automatically controlling the external magnetic field and drive current.This dual-loop structure is fully program controlled by a micro control unit(MCU),which not only simplifies the traditional constant parameter sensor circuit,saving the time required to adjust the circuit component parameters,but also improves the sensor performance and environmental adaptation.Results In the performance test,within 2 min of self-adaptation,our sensor showed a better sensitivity and signal-to-noise ratio(SNR)than those of the traditional designs and achieved a background noise of 12 pT/√Hz at 10 Hz and 7pT/√Hz at 200 Hz.Conclusion To the best of our knowledge,our sensor is the first to realize self-adaptation of both the external magnetic field and the drive current.

Analysis of atom detection via the magnetic optical effect

We demonstrated a new method of atom detection by means of the magnetic optical effect. The number density of the atom cloud was measured by detecting the rotation angle of the polarization plane of linearly polarized probe light when propagating inside the atomic cloud. Detuning, the magnetic field and light intensity dependencies of the rotation angle were studied theoretically and experimentally to find the best parameter for atom detection. In this way, we managed to achieve a rotation angle of 0.22 rad with a signal to noise ratio （SNR） of 75 and a contrast of 87.5%.

Magnetic resonance cholangiopancreatography image enhancement for automatic disease detection

AIM:To sufficiently improve magnetic resonance cholangiopancreatography(MRCP) quality to enable reliable computer-aided diagnosis(CAD).METHODS:A set of image enhancement strategies that included filters(i.e.Gaussian,median,Wiener and Perona-Malik),wavelets(i.e.contourlet,ridgelet and a non-orthogonal noise compensation implementation),graph-cut approaches using lazy-snapping and Phase Unwrapping MAxflow,and binary thresholding using a fixed threshold and dynamic thresholding via histogram analysis were implemented to overcome the adverse characteristics of MRCP images such as acquisition noise,artifacts,partial volume effect and large inter-and intra-patient image intensity variations,all of which pose problems in application development.Subjective evaluation of several popular pre-processing techniques was undertaken to improve the quality of the 2D MRCP images and enhance the detection of the significant biliary structures within them,with the purpose of biliary disease detection.RESULTS:The results varied as expected since each algorithm capitalized on different characteristics of the images.For denoising,the Perona-Malik and contourlet approaches were found to be the most suitable.In terms of extraction of the significant biliary structures and removal of background,the thresholding approaches performed well.The interactive scheme performed the best,especially by using the strengths of the graphcut algorithm enhanced by user-friendly lazy-snapping for foreground and background marker selection.CONCLUSION:Tests show promising results for some techniques,but not others,as viable image enhancement modules for automatic CAD systems for biliary and liver diseases.

Low Cost,Low Power Magnetic IEDs Detection Method Using Biaxial Magnetometry Digital Sensors

The magnetic improvised explosive devices （IEDs）, also commonly known as a type of a sticky bomb, is simply constructed devices yet very lethal. This paper puts forward the idea of an electronic compass that is capable of sensing the change of a magnetic field generated by a magnet and translating it into interpretable data, which could act as the base for the further studies and assist in developing a greener automated system for detecting this device. The electronic compass is specifically chosen for reducing power consumption of systems in addition to the fact that it is available at a low cost.

High-Precision Vital Signs Detection Method Based on Spectrum Refinement and Extended DCMA

In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement and the extended differentiate and cross multiply al-gorithm(DCMA)has been proposed.Firstly,the improved DFT algorithm is used to accurately obtain the distance window of human body.Secondly,phase ambiguity in phase extraction is avoided based on extended DCMA algorithm.Then,the spectrum range of refinement is determ-ined according to the peak position of the spectrum,and the respiratory and heartbeat frequency information is obtained by using chirp z-transform(CZT)algorithm to perform local spectrum re-finement.For verification,this paper has simulated the radar echo signal modulated by the simu-lated cardiopulmonary signal according to the proposed algorithm.By recovering the simulated car-diopulmonary signal,the high-precision respiratory and heartbeat frequency have been obtained.The results show that the proposed algorithm can effectively restore human breathing and heart-beat signals,and the relative error of frequency estimation is basically kept below 1.5%.

Study on Metal Detection with an Electromagnetic Induction Probe Utilizing a Rotating Magnetic Field

The present paper describes an investigation conducted on metal detectors installed with a scanning probe.The authors applied a rotating magnetic field probe to metal detection.The rotating magnetic field probe is comprised of two vertically placed rectangular exciting coils and a circular detecting coil.The experimental results confirmed that the probe can detect metal objects and provide more information about their shape,direction,and electromagnetic characteristics than conventional metal detector probes.A two-dimensional signal display shows a low-resolution image of the metal object and the signal phase indicates the object’s direction and electromagnetic characteristics.The experimental results show that excellent reconstruction of the surface shapes of metal objects can be obtained for both magnetic and nonmagnetic metals under present conditions.There is also the potential for the approximate shape of a metal object to be estimated from the reconstructed image.

Detection of surface cutting defect on magnet using Fourier image reconstruction

A magnet is an important component of a speaker,as it makes the coil move back forth,and it is commonly used in mobile information terminals.Defects may appear on the surface of the magnet while cutting it into smaller slices,and hence,automatic detection of surface cutting defect detection becomes an important task for magnet production.In this work,an image-based detection system for magnet surface defect was constructed,a Fourier image reconstruction based on the magnet surface image processing method was proposed.The Fourier transform was used to get the spectrum image of the magnet image,and the defect was shown as a bright line in it.The Hough transform was used to detect the angle of the bright line,and this line was removed to eliminate the defect from the original gray image;then the inverse Fourier transform was applied to get the background gray image.The defect region was obtained by evaluating the gray-level differences between the original image and the background gray image.Further,the effects of several parameters in this method were studied and the optimized values were obtained.Experiment results show that the proposed method can detect surface cutting defects in a magnet automatically and efficiently.

A New High-Precision and Lightweight Detection Model for Illegal Construction Objects Based on Deep Learning

Illegal construction has caused serious harm around the world. However, current methods are difficult to detect illegal construction activities in time, and the calculation complexity and the parameters of them are large. To solve these challenges, a new and unique detection method is proposed, which detects objects related to illegal buildings in time to discover illegal construction activities. Meanwhile, a new dataset and a high-precision and lightweight detector are proposed. The proposed detector is based on the algorithm You Only Look Once (YOLOv4). The use of DenseNet as the backbone of YDHNet enables better feature transfer and reuse, improves detection accuracy, and reduces computational costs. Meanwhile, depthwise separable convolution is employed to lightweight the neck and head to further reduce computational costs. Furthermore, H-swish is utilized to enhance non-linear feature extraction and improve detection accuracy. Experimental results illustrate that YDHNet realizes a mean average precision of 89.60% on the proposed dataset, which is 3.78% higher than YOLOv4. The computational cost and parameter count of YDHNet are 26.22 GFLOPs and 16.18 MB, respectively. Compared to YOLOv4 and other detectors, YDHNet not only has lower computational costs and higher detection accuracy, but also timely identifies illegal construction objects and automatically detects illegal construction activities.

Initial Rotor Position Detection of 12/10 Flux-switching Permanent Magnet Motors

电机转子初始位置检测的精度直接决定其启动运行时的性能。针对12/10极永磁磁通切换型电机,在验证其凸极性的基础上,采用注入脉振高频信号实现转子初始位置估计。通过对传统高频脉振正弦电压信号注入的分析,研究了基于高频方波或三角波的注入方法,再利用电流差值调制或直接信号调制方法得到位置误差信号,同时根据磁路的饱和效应,通过对d轴电流过零点时间差值的累加,实现了磁极方向辨识。分析了位置误差信号的系数与初始位置检测收敛性的关系。通过实验验证了所提方法的正确性和可行性。

CoFe_(2)O_(4) decorated graphene/C_(18)-functionalized mesoporous silica nanocomposites prepared for magnetic enrichment and electrochemical detection of promethazine in beef

Promethazine(PHZ)is used as a sedative in veterinary medicine,and its residue can threaten the health of human.The electrochemical detection of PHZ is suitable method for application in the field.However,the traditional electroanalysis is difficult to perform directly in meat samples due to matrix interference.This work integrates magnetic solid-phase extraction and differential pulse voltammetry for highly sensitive and selective determination of PHZ in beef and beef liver for the first time.CoFe_(2)O_(4)/graphene coated with C_(18)-functionalized mesoporous silica(MG@mSiO_(2)-C_(18))is synthesized as dispersed magnetic adsorbent to extract PHZ.Magnetic glassy carbon electrode modified with nitrogen-doped hollow carbon microspheres(HCM)attracts the MG@mSiO_(2)-C_(18)with PHZ,and directly detects the PHZ without elution procedure.MG@mSiO_(2)-C_(18)can separate PHZ to avoid the interference of impurities on following detection,and also concentrate PHZ on magnetic electrode.Additionally,the electrode modification with HCM can amplify the electrochemical signal of PHZ.Finally,the integrated PHZ determination method exhibits a wide linear range from 0.08μmol/L to 300μmol/L with a low limit of detection of 9.8 nmol/L.The beef sample analysis presents excellent recovery,demonstrating that this protocol is promising for the rapid and onsite detection of PHZ in real meat samples。