Detection Coil Research Articles

A composite testing method of homologous magnetic flux leakage and motion-induced eddy current for inner and outer defects

Magnetic flux leakage (MFL) testing, widely utilized for pipeline integrity assessments due to its efficiency and accuracy, is often challenged by motion-induced eddy currents (MIEC) that can distort MFL signals. Contrary to traditional perspectives that consider MIEC as detrimental, this paper introduces a novel MFL-MIEC composite testing method. This method leverages MIEC as a complementary technique while sharing the same excitation source. By exploring the generation and influence of MIEC on MFL signals, we simulate optimal probe positions and analyze the effects of defect position, angle, and detection speed on signal quality. Adjustments in the detection coils orientation are shown to enhance signal strength, demonstrating the methods effectiveness in identifying pipeline defects through practical experiments. This approach offers significant potential for widespread application in pipeline assessments.

Inductive Sensor Based on Micromachined Coil for Conductive Target Detection

Inductive Sensor Based on Micromachined Coil for Conductive Target Detection

The effects of the magnetic field on germination and seedling growth of chickpea (Cicer arietinum L.) and sunflower (Helianthus annuus L.)

Organisms interact with their environment and effects of environmental factors vary depending on ecology and tolerance levels. However magnetic field is an inevitable factor for all organisms. The aim of the study was to investigate the effects of different magnetic field (MF) applications on germination percentage, pigment content and antioxidant capacity of two important agricultural plant (Sunflower and Chickpea) species. Initially, seeds were exposed to 5 mT, 10 mT and 20 mT magnetic field generated by Helmholtz coil for detection of germination effects. Then seedling test was survived at the same conditions. MF was applied 20 minutes for every day at the same time period. According to germination results, MF application to sunflower and chickpea seeds was resulted with increase in germination percentage compared to control. 20 mT application caused decrease in shoot length of sunflower seedlings. On the contrary, 20 mT MF application resulted with increase in shoot length of chickpea seedlings. All magnetic field strengths increased carotenoid levels in chickpea seedlings. Also, MF application affected the phenolic and flavonoid contents of sunflower and chickpea seedlings. Depending on the increase in secondary metabolites, DPPH and FRAP activities varied. As a conclusion, MF application contributed to effect on plant metabolism and it has the potential to be used in agricultural applications.

Key factors governing the direction of SH0 mode guided waves generated by FeCo strip-based magnetostrictive sensor

Magnetostrictive sensors (MsS) are widely used to generate ultrasonic guided waves of SH0 mode for the purpose of detecting defects in plate-like structures. An MsS commonly employs a rectangular magnetostrictive strip and a sensor unit (including detection coil and magnet) to generate SH0 waves. However, the effect of coverage range of static magnetic field (Ls) and dynamic magnetic field (LD) on the SH0 wave generation direction has not been fully explored. So far, the cases of LS<<LD and LD>>LS are seldom discussed in the development of MsS for generating SH0 mode. In this study, the key factor governing the direction of SH0 mode generated by FeCo strip-based MsS was experimentally clarified. The transition phenomenon in the generation direction of SH0 wave was observed while the combination parameters crossing the control line of Ls≈LD. The phenomenon could be interpreted by the alterations in the operation mechanism of Wiedemann effect and reversed Wiedemann effect. As a result, the generation direction of SH0 mode could be tuned along the static magnetic field (Ls<<LD), the dynamic magnetic field (Ls>>LD) or the direction of both static and dynamic magnetic fields (Ls≈LD). The findings in this study is of benefit for guiding the design of MsS array with the tunable generation direction of SH0 mode.

Crack detection using a cutting-edge flexible eddy current sensor with voltage and phase measurement techniques

This study utilizes cutting-edge Flexible Eddy Current (FEC) sensors for the detection of cracks in aluminum plates with varying artificial crack sizes. The FEC sensor, relying on voltage and phase correction measurements, analyzes and processes signals from these cracks. The results demonstrate that excitation frequency and current have a significant impact on the induced current voltage and phase in the detection coil. Increasing these parameters linearly amplifies voltage, while phase changes primarily depend on the excitation frequency. To address phase change with large cracks, the phase correction method was employed, improving clarity for more accurate assessments. The study highlights the sensitivity of the FEC sensor in detecting cracks of various sizes, including subtle changes in voltage and phase for small cracks. Additionally, phase measurements, especially at higher excitation frequencies, offer better sensitivity and resolution. The study is also placed on the importance of scanning speed in acquiring crack data, as higher speeds may reduce data points and affect interpretation, requiring careful consideration.

MPI System with Bore Sizes of 75 mm and 100 mm Using Permanent Magnets and FMMD Technique.

We present two magnetic particle imaging (MPI) systems with bore sizes of 75 mm and 100 mm, respectively, using three-dimensionally arranged permanent magnets for excitation and frequency mixing magnetic detection (FMMD) coils for detection. A rotational and a translational stage were combined to move the field free line (FFL) and acquire the MPI signal, thereby enabling simultaneous overall translation and rotational movement. With this concept, the complex coil system used in many MPI systems, with its high energy consumption to generate the drive field, can be replaced. The characteristic signal of superparamagnetic iron oxide (SPIO) nanoparticles was generated via movement of the FFL and acquired using the FMMD coil. The positions of the stages and the occurrence of the f1 + 2f2 harmonics were mapped to reconstruct the spatial location of the SPIO. Image reconstruction was performed using Radon and inverse Radon transformations. As a result, the presented method based on mechanical movement of permanent magnets can be used to measure the MPI, even for samples as large as 100 mm. Our research could pave the way for further technological developments to make the equipment human size, which is one of the ultimate goals of MPI.

Identifying the plane position of the receiver coil in a multi‐transmitter IPT system through the identification of parameters

AbstractThe study introduces a method for identifying the location of receiver coils within a multi‐transmitter IPT system that utilizes shared transmitter coils. In contrast to the conventional receiver coil position recognition methods, this approach eliminates the need for additional detection coils and position sensors. Identifying the location of the receiver coil in a multi‐transmitter IPT system is achieved through the concurrent optimization of the transmitter coil and its electrical characteristics. The study presents the design of coil grouping and control mechanisms for a 3×3 multi‐transmitter. A mathematical model has been developed for the mutual inductance between receiver and transmitter coils on the X–Y plane. Adaptive cooperative particle swarm optimizer (ACPSO) facilitates the identification of mutual inductance and load parameters in a multi‐transmitter IPT system, positioning the receiver coil in a 2D plane using genetic particle swarm optimization (GAPSO) and a mutual inductance mathematical model. The discrepancy in accuracy between the receiver coil's test coordinates and the absolute coordinates remains below 3.5%.

Radial Field Detector to Improve Sensitivity of Localized Defects in Remote Field Eddy Current Technique

ABSTRACT This paper presents the development of a cone-shaped radial magnetic-field-detector–based remote field eddy current (RFEC) probe for enhanced detection of localized defects in ferritic steel tubes. The performance of the radial coil detector has been evaluated for the detection of different types of defects such as through holes, flat bottom holes and notches of different sizes and orientations. The RFEC signals are observed to be corrupted by heavy noise due to spatial variations in material permeability. To remove the random noise from the nonstationary time series RFEC signals, empirical mode decomposition (EMD) processing has been adopted and has been found to significantly improve the signal-to-noise (SNR) ratio. Furthermore, the effect of the circumferential extent of defects on the signal amplitude is analyzed through experimental and finite-element-model–based studies. The linear resolution of the designed radial coil detector and its repeatability behavior are also scrutinized. Studies demonstrate that the developed radial field detector is a promising configuration in remote field eddy current technique for enhanced defect detection and also in designing an array probe.

Design and Analysis of Micro Signal Detection Circuit for Magnetic Field Detection Utilizing Coil Sensors

Eddy current inspection has been extensively employed in non-destructive testing of various conductive materials. The coil probe, as a mainstream sensor in the eddy current detection system, inevitably encounters interference from external signals while transmitting its own signal. Therefore, developing techniques to extract valuable signals from noisy ones is crucial for ensuring accurate detection. Carbon fiber composites not only possess significantly lower electrical conductivity compared to conventional metallic materials but also exhibit notable anisotropy. To address this issue, we designed an ‘8’ coil probe set where the excitation coil does not electromagnetically interfere with the detection coil. However, practical applications that require portability and miniaturization pose challenges when utilizing this coil probe set to identify carbon content or defects due to the typically weak output signal. To address this issue, this paper proposes a design that combines the ‘8’ structure of the planar coil probe with the principle of phase-locked amplification to create a dual-phase sensitive phase-locked amplification detection circuit. These specific design ideas were tested using a weak signal, which passed through the preamplifier, secondary amplifier, and band-pass filter comprising the target channel for signal amplification and noise filtering. The effective signal amplitude is proportional to the inverse phase difference between the direct current (DC) signal and inversely proportional to the amplitude of the signal. Finally, the DC signal was passed through an analog-to-digital converter (ADC). The analog-to-digital converter (A/D) is used to collect and calculate the DC signal, enabling the detection of weak electrical signals. Simulation experiments demonstrated that the signal detection circuit has an amplitude error below 0.2% and a phase error below 0.5%. The phase-locked amplification circuit designed in this paper can effectively extract the tiny impedance change signals of the planar coil sensor probe with high sensitivity and good robustness.

An online wear metal particles monitoring warning sensor based on electromagnetic induction in lubricating oil

The online monitoring of metal particles in lubricating oil plays an important role in equipment fault diagnosis technology. This paper designs an online wear monitoring warning sensor based on the electromagnetic induction of metal particles in lubricating oil. First, different from the traditional three-coil sensing and detection method, the sensor consists of two excitation coils and one detection coil. In addition, the parallel capacitance and detection capacitance parameters are obtained by COMSOL’s scanning frequency, and the best detection capacitance is 7.53 nF. Second, according to the obtained optimal detection parallel capacitance value, the amplitude data of the particle signal, as well as the ferromagnetic particles above 60 µm and the non-ferromagnetic particles above 80 µm, are obtained. Third, according to the principle of three-coil induction, a mapping relationship model was established between the size range of metal wear particles in lubricating oil. Finally, we set up an oil wear particle platform to verify the sensor performance. The ferromagnetic and non-ferromagnetic particles are divided into multiple size ranges, and the peak-to-peak values of the output signal of different-sized wear particles are measured. We developed a prototype sensor and verified the signal consistency and repeatability of the sensor to wear metal particles. In addition, we used the sensor to test a large number of metal particles of different sizes (14 ferromagnetic particle standard samples with particle sizes ranging from 20.64 to 457.59 µm and ten non-ferromagnetic particle standard samples with particle sizes ranging from 40.52 to 348.07 µm). The experimental results show that the sensor can directly achieve monitoring sensitivity for ferromagnetic particles greater than 64.57 µm and non-ferromagnetic (copper) particles greater than 82.83 µm under the 4.2 mm aperture flow channel. The sensor can effectively realize the sensitivity on monitoring of small ferromagnetic particles and non-ferromagnetic particles, and it is particularly sensitive to small non-ferromagnetic particles.

Vector hysteresis loops of rare earth magnets measured in a biaxial vibrating sample magnetometer

Vector hysteresis loops of rare earth magnets measured in a biaxial vibrating sample magnetometer

The applications of sonar and radar systems in underwater detection

The development of sonar and radar systems utilizing sound and radio waves, respectively, has evolved significantly over the past two centuries. Recent decades have witnessed remarkable progress in remote sensing using high-frequency Doppler radars for marine surface parameter analysis. Understanding animal behavior around sustainable ocean energy sources is crucial for mitigating potential risks linked to such installations. Increasing the Signal-to-Noise Ratio (SNR) enhances signal reception. A technique estimating noise in the detection coil's first half determines the transfer function between the reference and detection coils. This enables separation of the Ultra-Nuclear Magnetic Resonance signal from noise, preserving it using non-linear fitting. Sonar systems, using sound waves, detect underwater objects, map surfaces, and track marine life. Sound waves emitted by the transmitter are reflected back to calculate distances. Challenges in sonar systems include a blind zone caused by submerged transducers in shallow water. To improve, SNR enhancement is critical. Sonar's future may rely on AI-assisted signal processing. Radar systems, operating with radio waves, share features with sonar, focusing on object detection and ranging. Improvement avenues include 3D imaging and AI-enhanced signal processing. In conclusion, sonar and radar systems are crucial tools for underwater exploration and object detection. While challenges persist, innovative solutions and AI advancements promise enhanced capabilities for both systems.

A Natural Position Observer With Vertical Detection Coil for FSCW Machines

This paper presents a sensorless control strategy using the novel detection coil for permanent magnet synchronous motor (PMSM) with fractional slot concentrated winding (FSCW). In order to eliminate the armature component in the coil voltage, the detection coil distribution is determined based on the analysis of synchronous inductance and leakage inductance for FSCW machines. Hence, the rotor position and angular velocity are estimated from the terminal voltage of detection coil, without any knowledge of motor parameters. Both finite element analysis (FEA) results and experiments are carried out to prove the effectiveness of the proposed method at steady and transient states.

A metal object detection system for electric vehicle wireless charging based on LC oscillating circuit and reverse-winding-incorporated detection coils

In magnetically coupled wireless charging systems for electric vehicles, it is common for metal objects to enter the charging system. In this case, the strong magnetic field of wireless charging causes an eddy current effect in the metal object, which generates a large amount of heat. This heat accumulation poses a risk of fire. In this paper, a novel metal object detection system designed for wireless charging of electric vehicles is proposed. The system utilizes the principle that the coil impedance and coupling coefficient change with the presence of metal objects, and a set of composite coils is designed to improve the sensitivity of detection. The detection coil and feedback coil in the composite coil are decoupled by reverse series connection. An LC oscillating circuit based on transformer feedback is used to detect metal objects, and the circuit can make good use of the parameter changes of the composite coil. Finally, an experimental platform for wireless charging metal detection in electric vehicles has been built to validate the proposed system. Through testing, it has been demonstrated that the system can detect the presence of metal objects in a timely and accurate manner.

Research on Metal and Living Foreign Object Detection Method for Electric Vehicle Wireless Charging System

In the electric vehicle wireless power transmission system, the high-frequency alternating magnetic field between the transmitter and receiver can have a certain impact on the health of living organisms and may even lead to lesions. In addition, metal foreign objects in an alternating magnetic field can cause their own heating or even cause fires due to the eddy current effect, so foreign object detection is an essential function in the wireless power transmission system of electric vehicles. In order to prevent metals and living organisms from entering the charging area and causing harm to the charging system and living organisms, this paper proposes a method for detecting living organisms and metal foreign objects. Firstly, the equivalent circuits for the detection systems of the living organism foreign objects and metal foreign objects are established, respectively, and the working theory of the detection system is analyzed by deriving equations. Secondly, the comb capacitor simulation model was constructed, and the comb capacitor electrode spacing, wire thickness, and capacitor spacing were designed based on the scale factor γ to explore the effects of the height and bottom area of the living organism’s foreign object on the comb capacitor. We constructed a simulation model of the detection coil and designed the inner diameter D, the number of turns N, and the wire spacing S of the detection coil according to the scale factor β. An arrayed detection coil and comb capacitor combination mode is proposed to realize the function of the simultaneous detection of metal and living organism foreign objects, and a compensation capacitor is introduced to keep the detection system in a resonant state. Lastly, a platform for foreign object detection experiments was set up to detect metal screws and beef chunks compared to the detection area without foreign objects. Metal screws entering the detection area cause a 20% voltage drop in the detection circuit resistor, and beef chunks entering the detection area cause a 30% voltage drop in the detection circuit resistor, so the detection method is effective in detecting both metals and living organisms. The feasibility of the combined mode of arrayed detection coils and comb capacitors was verified.

Nondestructive testing method for internal defects in ferromagnetic materials under weak bias magnetization

Magnetic flux leakage (MFL) testing is effective in detecting internal defects in ferromagnetic materials. However, it requires the saturation magnetization of materials, which is not always practicable in complex inspection environments. Therefore, this study presents a novel dynamic permeability testing (DPT) method, in which internal defects will induce dynamic permeability variations on the surface of weakly magnetized ferromagnetic materials, and the variations are then detected by alternating current detection coils with magnetic cores, enabling the identification of internal defects. The principle of DPT is analyzed through simulations, which are subsequently verified by experiments. Furthermore, the effects of excitation frequency, probe lift-off, and defect size on the DPT signal are investigated experimentally. Finally, the comparison with conventional MFL demonstrates that the DPT method can effectively identify the internal defect using a weak magnetization current of 0.1 A (about 0.25 T in the steel plate), whereas MFL requires 0.5 A (about 1.32 T) to achieve a similar detection capability under the same probe lift-off values. This new method has significant practical value, especially in situations where saturation magnetization is not feasible.

Mirror Symmetry Coils for Foreign Object Detection and Location with Wireless Power Transmission

Background: Wireless power transmission technology effectively avoids safety issues caused by accidental contact, wire aging, and friction. However, due to the presence of foreign objects, other severe accidents such as fire hazard can occur, and the charging system can be interfered with and even damaged by the foreign objects. background: As a new charging technology, the wireless power transmission (WPT) technology has shown some favorable application prospects on safety, reliability, and convenience. Method: Therefore, this paper proposes (MSD) mirror symmetry detection coils to detect and locate foreign objects. First, we conduct theoretical analysis and derive formulas to validate our proposed method. Next, we employ ANSYS Maxwell to simulate the (WPT) wireless power transmission system, considering various sizes and materials of foreign objects and comparing them to a system without foreign objects. Result: Furthermore, we conducted experiments using mirror symmetrical detection coils to detect and locate foreign objects, providing additional verification for our proposed method. Conclusion: The simulation and experimental results show that the proposed method of mirror symmetry detection coils can effectively identify and locate the foreign objects.

Optimal design of excitation coil for transient electromagnetic detection based on incident field

Optimal design of excitation coil for transient electromagnetic detection based on incident field

Recognizing Multitype Misalignments in Wireless EV Chargers With Orientation-Sensitive Coils: A Data-Driven Strategy Using Improved ResNet

In wireless electric vehicle charging systems, misalignments between ground-assembled transmitter and vehicle-assembled receiver are undesirable but inevitable, which may cause efficiency deterioration and even thermal risks. The recognition of horizontal misalignment, including that in the longitudinal and lateral direction, has been made gradual progress by previous works. While yaw angle, with rare attention, can also degrade the charging performance, especially for those employing non-centrosymmetric coupling coils, such as rectangular coils. In this paper, a data-driven strategy based on improved ResNet is proposed to recognize the above multi-type misalignments simultaneously, which is accurate, reliable, and of practical and general value. Large-scale data is sampled using the proposed detection coils by double-group cooperation, which features high sensitivity to the misalignments of all kinds, especially yaw angle. Benefit to the compression technique in the pre-processing phase, the number of training data and labels can be successfully reduced by 3/4. As the core algorithm of the overall strategy, the adaptive channel parameter recalibration ResNet (ACPR-ResNet) can effectively perceive slight differences among similar input samples and map them to proper labels. This is achieved by an adaptive operation of nonlinear transformation and recalibrated importance of channel features during the training process. The effectiveness of the proposed strategy is verified experimentally using a 6.6-kW prototype. Within the 24×24 cm range, 95.2% of the test cases have an error of less than 1.7 cm when recognizing horizontal misalignment, and 91.7% of the test cases have an error of less than 1.5° when recognizing yaw angle.

Development Trends in Digital Highway Systems and Processes under Intelligent Technology

With the acceleration of China's urbanization process, the phenomenon of urban road traffic congestion is becoming increasingly serious, and the problem of road bottlenecks is becoming increasingly prominent. The operational efficiency of urban roads has encountered challenges. The rapid development of intelligent technologies such as artificial intelligence, big data, and the Internet of Things has provided more possibilities and opportunities for the research of digital highways. These technologies can be applied to traffic flow monitoring, road condition prediction, intelligent traffic management, and other aspects to improve highway traffic efficiency and service quality. This article designs a digital highway system based on intelligent technology to alleviate traffic congestion and other issues. Firstly, traffic information is collected and tested through channels such as circular coil detectors and cameras. This article would integrate and store the collected data into the Redis database; Then, the data is analyzed, processed, and predicted using the Kalman filtering algorithm. It then sends the predicted information to the client, providing convenience for users to choose the best route. This article tests the performance of the system through experiments. The experiment shows that the system can make correct analysis and prediction even in high pedestrian traffic, find the fastest driving route, and effectively resist the impact of fluctuations in pedestrian traffic. In addition, the system has achieved good results in accuracy testing of analysis and prediction. In summary, the digital highway system based on intelligent technology is expected to improve traffic efficiency, enhance traffic safety, achieve intelligent travel services, promote sustainable transportation development, and also bring broad prospects for commercial innovation and market opportunities. With the continuous progress and application of intelligent technology, digital highway systems would become an important tool for future road traffic to respond to challenges and improve service quality.