Strong Electromagnetic Interference Research Articles

A New Method for Anti-Interference Measurement of Capacitance Parameters of Long-Distance Transmission Lines Based on Harmonic Components

In the context of strong electromagnetic interference environments, the measurement accuracy of the capacitance parameters of transmission lines under power frequency measurement methods is not high. In this paper, a capacitance parameter anti-interference measurement method for transmission lines based on harmonic components is proposed to overcome the impact of power frequency interference. When applying this method, it is first necessary to open-circuit the end of the line under test. Subsequently, apply voltage to the head end of the tested line through a step-up transformer. Due to the saturation of the transformer during no-load conditions, a large number of harmonics are generated, primarily third harmonic. The third harmonic components of voltage and current on the tested transmission line are extracted using the Fourier transform. The proposed method addresses the influence of line distribution effects by establishing a distributed parameter model for long-distance transmission lines. The relevant transmission matrix for the zero-sequence distributed parameters is obtained by combining Laplace transform and similarity transform to solve the transmission line equations. Using synchronous measurement data from the third harmonic components of voltage and current at both ends of the transmission line, combined with the transmission matrix, this method accurately measures the zero-sequence capacitance parameters. The PSCAD/EMTDC simulation results and field test outcomes have demonstrated the feasibility and accuracy of the proposed method for measuring line capacitance parameters under strong electromagnetic interference.

An optimization design for fiber-optic neutron detector based on 6LiF/ZnO:Ga and wavelength shifting fibers

The fiber-optic neutron detector consists principally of a neutron-sensitive scintillator, optical fiber, and photomultiplier tube. It has features such as small size, real-time online measurement capability, and high resistance to electromagnetic interference. This detector is excellent for neutron detection in areas with limited space and strong electromagnetic interference. However, its small size results in a comparatively low neutron sensitivity. The goal of this study is to look into the relationship between detector parameters and performance in order to improve the detector design. The research begins with the development of a detector model using Monte Carlo simulation programs to investigate the relationship between the 6LiF/ZnO:Ga mass ratio, thickness, wavelength-shifting fiber length, and detector performance. The 6LiF/ZnO:Ga mass ratio was then used as the test parameter to create equivalent detector samples for experimental validation. The results show that the detector has the highest neutron sensitivity when the mass ratio of 6LiF/ZnO:Ga is 1:1. This pattern is consistent with theoretical simulation results, indicating that the optimization strategy for detector parameters is feasible. The results of this work give a theoretical foundation for the development and practical implementation of the fiber-optic neutron detector.

Nickel-Fe3O4@Graphene coated lightweight carbonized wood for efficient electromagnetic interference shielding

The miniaturization and integration of electronic equipment promote electromagnetic effect radiation pollution more and more serious. The lightweight, renewable electromagnetic interference (EMI) shielding materials is urgently needed. This study developed a high temperature carbonization, Fe3O4@Graphene impregnation, and electroless Ni technique to construct a carbonized wood composite with strong EMI shielding performance using sustainable natural wood as the raw material. The Fe3O4@Graphene is distributed throughout the carbonized wood to provide the conductivity and magnetism of the reinforced composite material, and provide more interfaces to increase the dielectric loss and magnetic loss, thereby exhibiting excellent EMI shielding performance. The results show that at low thickness (2 mm) and ultra-low density (0.284 g/cm3), the CWN-7 composite exhibits excellent EMI shielding effectiveness of up to 84.2 dB in the whole X-band (8.2–12.4 GHz). At the same time, it has extraordinary compressive strength and good thermal insulation performance. This study offers a different method for creating composite multifunctional electromagnetic shields out of carbonized green wood.

Dual-mode optical thermometers via the thermochromic Bi3+, Eu3+ co-doped La2LiSbO6 phosphors for real-time chip temperature monitoring

In recent years, with the increasing demand for non-contact temperature measurement, it is urgent to develop a new type of phosphor with double emission centers, high sensitivity and good reliability. A series of Bi3+and Eu3+ co-doped La2LiSbO6 double emission center phosphors were successfully prepared. The response characteristics of Bi3+and Eu3+ at different temperatures in the range of 293–473k were calculated by fluorescence intensity ratio (FIR) technique. The optimal relative sensitivity Sr and absolute sensitivity Sa were 1.13 % K−1 and 1.27 % K−1, respectively. Hence, La2LiSbO6:Bi3+, Eu3+ phosphors have the capability of non-contact optical temperature measurement and are a promising material for application. The phosphor is combined with the optical fiber temperature sensor to monitor the real-time temperature of the computer central processing unit. The optical fiber temperature sensor system breaks through the limitations of traditional temperature measurement, and can be used in special environments such as small size and strong electromagnetic interference. It has become an ideal choice to replace the traditional temperature sensor.

Analysis of UAV data communication stability method in extreme environment

In order to get in touch with the affected area smoothly after the disaster, this paper uses drones as air base stations. Their high mobility and sensitivity make them apt for such critical roles. However, during extreme weather conditions, these unmanned aerial vehicles (UAVs) encounter various challenges that can impair their stability and, consequently, their ability to serve as reliable air base stations. As a result, signal transmission can be interrupted or severely limited. Among the common factors affecting UAV stability are strong winds, temperature fluctuations, heavy rainfall, and electromagnetic interference. These factors can cause the UAVs to deviate from their intended flight paths, drop in altitude, or even lose connection with the ground control. As a consequence, the reliability of communication, so critical in emergency situations, gets compromised. To address the problem of degraded UAV stability, several solutions have been proposed and implemented. One approach involves enhancing the drone's onboard stabilization systems, incorporating advanced algorithms that allow it to autonomously adjust to environmental changes. Another strategy is the deployment of a network of drones, ensuring redundancy. If one drone faces difficulties, another can take over, maintaining the communication link. Furthermore, advances in materials science have led to the development of UAVs with more robust structures, capable of withstanding the rigors of adverse weather conditions. Lastly, the use of ground-based boosters or repeaters can amplify signals, ensuring that even if a UAV's transmission is weak, the communication remains uninterrupted.

Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction.

To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP). Deep-DSP is proposed to directly predict EMI-free MR signals. During scanning, MRI receive coil and EMI sensing coils simultaneously sample data within two windows (i.e., for MR data and EMI characterization data acquisition, respectively). Afterward, a residual U-Net model is trained using synthetic MRI receive coil data and EMI sensing coil data acquired during EMI signal characterization window, to predict EMI-free MR signals from signals acquired by MRI receive and EMI sensing coils. The trained model is then used to directly predict EMI-free MR signals from data acquired by MRI receive and sensing coils during the MR signal-acquisition window. This strategy was evaluated on an ultralow-field 0.055T brain MRI scanner without any RF shielding and a 1.5T whole-body scanner with incomplete RF shielding. Deep-DSP accurately predicted EMI-free MR signals in presence of strong EMI. It outperformed recently developed EDITER and convolutional neural network methods, yielding better EMI elimination and enabling use of few EMI sensing coils. Furthermore, it could work well without dedicated EMI characterization data. Deep-DSP presents an effective EMI elimination strategy that outperforms existing methods, advancing toward truly portable and patient-friendly MRI. It exploits electromagnetic coupling between MRI receive and EMI sensing coils as well as typical MR signal characteristics. Despite its deep learning nature, Deep-DSP framework is computationally simple and efficient.

The experimental and theoretical study on the spatial‐temporal distribution of electromagnetic radiation from JO‐8 explosions.

AbstractThe detonating fuse in the multistage warhead will be subjected to strong electromagnetic interference, derived from electromagnetic radiation generated by explosion of the shaped charge warhead, which may cause premature detonation or misfire. In order to explore the possible electromagnetic environment surrounded the detonating fuse, the spatial‐temporal distribution of electromagnetic radiation after the explosion of JO‐8 explosive was investigated in this paper. The electromagnetic radiation signal was collected and its frequency coverage was analyzed in the far‐field area by the field blast test. Moreover, based on electromagnetic theory, a theoretical model of electromagnetic radiation generated by the explosion of JO‐8 explosive was established, and the spatial‐temporal distribution of the electric field intensity was illustrated in detail for several typical positions after the explosion. The better agreement between experimental and theoretical results indicates that the proposed theoretical model and computational method are reasonable. On this basis, the distributions of electric field intensity for different positions and various explosive weights were predicted respectively by using distance and explosive weight as variables. This study is expected to provide a reference for the research on the electromagnetic radiation for explosive explosion and anti‐explosive electromagnetic interference.

Nacre-inspired starch-based bioplastic with excellent mechanical strength and electromagnetic interference shielding

Bioplastics have aroused significant interest in researchers to relieve the serious environmental pollution caused by the ubiquity of petroleum-based plastics. However, it remains a great challenge to construct functional bioplastics with excellent mechanical strength, water resistance, and heat resistance. Inspired by the interesting structure of nacre, a novel starch-based bioplastic was prepared via a self-assembly technique, using 2,2,6,6-tetramethylpiperidine-1-oxy-oxidized cellulose nanofibers modified starch, nano-montmorillonite, and reduced graphene oxide as raw materials. Due to the unique layered structure and rich interfacial interaction, the starch-based bioplastic exhibited excellent mechanical properties, while the tensile strength was up to 37.39 MPa. Furthermore, it represented outstanding water resistance, heat resistance, repairability, renewability and biodegradability. Especially, the starch-based bioplastic demonstrated a strong electromagnetic interference shielding effectiveness (EMI SE), which was higher than 35 dB with a thickness of 0.5 mm. These powerful properties provided the possibility for functional applications of starch-based bioplastics.

Strong Electromagnetic Interference and Protection in UAVs

With the proliferation of unmanned aerial vehicles (UAVs) and the escalating electromagnetic environment in space, there has been growing attention and research focus on the strong electromagnetic effects and electromagnetic protection design of UAVs. This paper aims to introduce the potential strong electromagnetic interference that UAVs may encounter during flight. It specifically concentrates on three crucial subsystems: the datalink system, the flight control and navigation system, and the power system. The goal is to provide an overview of the current state of research on the strong electromagnetic effects of UAVs, along with a discussion of commonly employed research methods. Additionally, this paper introduces various means of strong electromagnetic protection that can be utilized for UAVs. Finally, it concludes with a summary of the research status and development trends concerning the effects of strong electromagnetic interference and the corresponding protection measures for UAVs.

Dual-directional SCR device with dual-gate controlled mechanism for ESD protection in photoelectric chip

The dual-directional silicon-controlled rectifier (DDSCR) is an electrostatic discharge (ESD) protection device. It can provide positive and negative ESD surge paths and has excellent robustness. However, industry-level sensors operating in strong electromagnetic interference environments impose higher reliability requirements on photoelectric chips. This paper proposed a novel DDSCR with a dual-gate controlled mechanism. By incorporating the gate diode triggering and the gate field modulation mechanism into the traditional DDSCR, and further utilizing additional parasitic bipolar junction transistors (BJTs) for diversion, the proposed device exhibits significantly improved ESD characteristics. Measurement results indicate that, compared to DDSCR, the proposed device exhibits a 27.5% reduction in trigger voltage (Vt1 ), a 96.1% improvement in holding voltage (Vh ), and achieves an equivalent human body model protection level of 11.45 kV, demonstrating exceptional design area efficiency. The experimental findings validate the effectiveness of the proposed device in 5 V photoelectric chip applications.

Construction of brick/mortar-like graphene/thermoset composites with highly anisotropic thermal conductivity and strong electromagnetic interference shielding performance

A new fabricating strategy has been successfully employed to prepare brick/mortar-like graphene/thermoset composites with highly anisotropic thermal conductivity and excellent electromagnetic interference shielding performance.

Intelligent processing of electromagnetic data using detrended and identification

The application of the electromagnetic method has accelerated due to the demand for the development of mineral resource, however the strong electromagnetic interference seriously lowers the data quality, resolution and detect effect. To suppress the electromagnetic interference, this paper proposes an intelligent processing method based on detrended and identification, and applies for wide field electromagnetic method (WFEM) data. First, we combined the improved intrinsic time scale decomposition and detrended fluctuation analysis algorithm for removing the trend noise. Then, we extracted the time domain characteristics of the WFEM data after removing the trend noise. Next, the arithmetic optimization algorithm was utilized to search for the optimal smoothing factor of the probabilistic neural network (PNN) algorithm, which realized to intelligently identify the noise data and WFEM effective data. Finally, the Fourier transform was performed to extract the spectrum amplitude of the effective frequency points from the reconstructed WFEM data, and the electric field curve was obtained. In these studies and applications, the fuzzy c-mean and PNN algorithm are contrasted. The proposed method indicated that the trend noise can be adaptively extracted and eliminated, the abnormal waveform or noise interference can be intelligently identified, the reconstructed WFEM data can effectively recover the pseudo-random signal waveform, and the shape of electric field curves were more stable. Simulation experiments and measured applications has verified that the proposed method can provide technical support for deep underground exploration.

Improved noise bias compensation-equivalent circuit modeling strategy for battery state of charge estimation adaptive to strong electromagnetic interference

Strong electromagnetic interference, which has a significant impact on the performance and safety of the lithium-ion battery, usually affects the accurate state of charge (SOC). Different optimization strategies are used to estimate the model parameters and the SOC due to the unknown nonlinear characteristics caused by noise. However, the impact of sensor and model errors is treated separately. To express the sensor and model uncertainties, a noise bias compensation-equivalent circuit model (NBC-ECM) is proposed, in which sensor noise and model error voltages are employed in the model structure and the SOC estimation process of the lithium-ion battery. For parameter identification, a singular value decomposition-bias compensation recursive least squares (SVD-BCRLS) algorithm is proposed to identify the characteristic micro-parameters of the battery. Then, a moving window adaptive extended Kalman filtering (MWAEKF) algorithm based on window functions is proposed for accurate SOC estimation of lithium-ion batteries. The stability of the model parameters and the reliability of the proposed algorithm in estimating the SOC are evaluated using different noise factors: current and voltage sensor noises of 10 and 50 mA. Using the proposed SVD-BCRLS-MWAEKF algorithm, the maximum SOC error is 1.3 %, the root mean square error (RMSE) is 0.3972 %, and the mean absolute error (MAE) is 0.2316 % using the noise of 0.05 V/A under the hybrid power pulse characterization (HPPC) operating condition. With the same noise value under the Beijing bus dynamic stress test (BBDST) operating condition, the proposed algorithm SOC has a maximum SOC error of 1.57 %, an RMSE of 0.5638 %, and an MAE of 0.4475 %. Under noise interference conditions, estimation is more accurate compared to static conditions, proving that the proposed algorithm can overcome the uncertainties encountered by lithium-ion batteries for real-time BMS applications.

An All‐Stretchable, Ultraviolet Protective, and Electromagnetic‐Interference‐Free E‐Textile

AbstractFlexible and skin‐mountable electronics have drawn tremendous research attention with the booming of smart medical systems and wearing technologies, however, their environmental adaptability to electromagnetic and solar radiation has long been neglected. Herein, a novel health monitoring e‐textile with robust ultraviolet (UV) protecting and strong electromagnetic interference (EMI) shielding performance is rationally developed on an ultraelastic and bilayered nonwoven textile. Via the respective incorporation of silver flake‐modified liquid metal (AgLM) and silver nanoparticles (AgNPs) on each side of a permeable substrate, a Janus sensing layer with electrophysiological monitoring function, Joule heating ability, and excellent EMI shielding capability (up to 38.5 dB in X band) is first fabricated. Elastic microfibers embedded with sensitive photochromic microcapsules are then in situ assembled on the bioelectric‐sensing layer, achieving a bilayered e‐textile with a reversible UV‐chromic property and an extraordinary UV protection factor (UPF) of 335.56. The developed all‐stretchable and UV‐EMI proof e‐textile is utilized as a safe and comfortable on‐skin electronic to provide point‐of‐care health regulation under complex UV/EMI radiative environments. Specifically, stable Joule heating performance and accurate monitoring of electrocardiogram (ECG) and surface electromyography (sEMG) are simultaneously obtained, demonstrating promising applications in multifunctional and robust wearing electronics.

Analysis of Electromagnetic Interference for Anti-Medal UHF RFID Temperature Tag in High Power Electronic Equipment

Being inches from the rapid development of new energy technology, the capacity of high-power power electronic equipment is increasing rapidly, and the requirements for its safe and reliable operation are also rising. As a result, the demand for online temperature monitoring of such equipment is becoming increasingly urgent. RFID temperature measurement technology can be used for real-time monitoring of the temperature of powered operation equipment. However, the operation of high-power electronic equipment generates strong electromagnetic interference, which can seriously affect the normal operation of RFID temperature measurement systems. For applications involving the internal temperature measurement of high-power power electronic equipment, this paper employs an RFID anti-metal temperature tag antenna with a short-circuit cutoff structure. This structure was tested in an excitation switchgear cabinet. During the low-power operation of the cabinet, the temperature tag functioned normally. By combining an RFID antenna model with an electromagnetic interference simulation model of the main circuit of the excitation switchgear cabinet, this paper establishes an electromagnetic interference simulation model for an RFID temperature tag. It analyzes how the tag’s antenna performance parameters change when subjected to interference. Through simulation, the failure mechanism of the RFID temperature tag during the high-power operation of the excitation switchgear cabinet is clarified. The analysis found that there are both conductive electromagnetic interference and radiated electromagnetic interference in the excitation switchgear cabinet, with the conductive electromagnetic interference having a more significant effect. Conductive electromagnetic interference can seriously impact the performance of RFID temperature tags in the excitation switchgear cabinet, significantly degrading their performance. In contrast, the effect of radiated electromagnetic interference on the tags is relatively small. Therefore, this paper employs anti-metal RFID temperature tags and simulates and analyzes their electromagnetic interference characteristics.

A novel PVA/MWCNTs hydrogel with high toughness and electromagnetic shielding properties

AbstractCarbon nanotubes (CNTs) are widely utilized as conductive fillers due to their high conductivity, lightweight, and ease of modification. However, their poor dispersion limits their otherwise excellent performance. In this study, we successfully prepared a high toughness, strong electromagnetic interference (EMI) shielding hydrogel by blending polyvinyl alcohol (PVA) hydrogel with multi‐walled carbon nanotubes (MWCNTs) modified by anionic surfactant sodium dodecylbenzene sulfonate (SDBS) and (3‐aminopropyl) triethoxysilane (KH550). We found that the modifiers can not only promote the uniform dispersion of MWCNTs but also improve the mechanical properties of the hydrogel. The results demonstrate that the stress (≈14.86 MPA), elongation at break (233.9%), and compressive strength (≈2.89 MPA) of PVA/MWCNTs composite hydrogel with 1 wt% MWCNTs and 5 wt% PVA were increased by 533.6%, 241.4%, and 206.5%, respectively. Encouragingly, the total electromagnetic shielding effectiveness (SET) is 123.6 dB at a thickness of 5 mm. In summary, this work provides a general approach to functionalizing MWCNTs, which has great potential for developing EMI shielding materials with high toughness.

Thermally insulating carbon nanotubes and copper ferrite based porous polydimethylsiloxane foams for absorption-dominant electromagnetic interference shielding performance

The exponential growth of the electronic and communication industry in the last 50 years raised serious concerns about electromagnetic (EM) pollution. Consequently, suitable composite materials for electromagnetic interference (EMI) shielding have been developed to reduce EM pollution. In the present work, carbon nanotubes (CNT) and copper ferrite (CuFe2O4) nanoparticle-based porous polydimethylsiloxane (PDMS) composite foams were prepared using the baking soda template method. The PDMS foam acts as the 3-dimensional (3D) porous network, CNT gives the required conductive path and magnetic CuFe2O4 provides the necessary magnetic loss, so that the resultant foams achieved high EMI shielding through the absorption mechanism. Without the inclusion of CuFe2O4, the total EMI SE of the PDMS foam is lower than 20 dB, while various contents of the added CuFe2O4 improve the EMI SE up to 32 dB at a thickness of 3 mm. In addition, the thermal insulation properties are also reported and the resultant material shows a moderately low thermal conductivity of 0.046 W m−1 K−1. These characteristics of the composite foam highlight the strong absorption-dominated EMI shielding and thermal insulation performance, allowing it to successfully meet a wide range of applications.

Design and Optimization of Multi-Stage TMR Sensors for Power Equipment AC/DC Leakage Current Detection

Tunnel magnetoresistance (TMR) can measure weak magnetic fields and has significant advantages for use in alternating current/direct current (AC/DC ) leakage current sensors for power equipment; however, TMR current sensors are easily perturbed by external magnetic fields, and their measurement accuracy and measurement stability are limited in complex engineering application environments. To enhance the TMR sensor measurement performance, this paper proposes a new multi-stage TMR weak AC/DC sensor structure with high measurement sensitivity and anti-magnetic interference capability. The front-end magnetic measurement characteristics and interference immunity of the multi-stage TMR sensor are found to be closely related to the multi-stage ring size design via finite element simulation. The optimal size of the multipole magnetic ring is determined using an improved non-dominated ranking genetic algorithm (ACGWO-BP-NSGA-II) to derive the optimal sensor structure. Experimental results demonstrate that the newly designed multi-stage TMR current sensor has a measurement range of 60 mA, a fitting nonlinearity error of less than 1%, a measurement bandwidth of 0–80 kHz, a minimum AC measurement value of 85 μA and a minimum DC measurement value of 50 μA, as well as a strong external electromagnetic interference. The TMR sensor can effectively enhance measurement precision and stability in the presence of intense external electromagnetic interference.

Transparent and Flexible Composite Films with Excellent Electromagnetic Interference Shielding and Thermal Insulating Performance.

As the working environment becomes more complex, the visualization of windows in electronic devices increasingly requires transparent and flexible electromagnetic interference (EMI) shielding films. There is a need for materials with EMI shielding properties, while maintaining excellent high light transmission and good thermal insulation. However, the preparation of such multifunctional materials remains challenging due to the respective mechanisms of action of the different properties. Herein, a multilayer structure strategy is proposed to fabricate transparent and flexible indium tin oxide (ITO)/silver nanowire (AgNW) composite films, achieving a multifunctional integration of high light transmission, strong EMI shielding, and good thermal insulation properties of the composite films. Simultaneously, the layered structure was designed and the potential optimization mechanism of the EMI shielding performance of the composite film was analyzed, providing great flexibility for the preparation of transparent composite films. The combination of excellent EMI shielding performance, outstanding near-infrared shielding performance, and high light transmittance makes the ITO/AgNW (IA) composite films promising for abundant potential applications.

Detection of Secondary Side Position for Segmented Dynamic Wireless Charging Systems Based on Primary Phase Angle Sensing

In dynamic wireless charging systems, the detection of secondary side positions has been attracting much attention in academic research. Due to the strong electromagnetic interference and the presence of foreign objects in the charging area, the use of conventional detection methods such as wireless communication and infrared techniques may be problematic; therefore, as an alternative to solve the above problem, a new detection method based on phase angle sensing is proposed in this paper. Through phase analysis of the primary input impedance and by reference to the relationship between the input port phase angle and the secondary side position, the proposed method is able to sense the secondary side position in real time. In addition, an analysis of the sensitivity of the proposed method to parameter variations is also carried out. In order to verify the effectiveness of the proposed position detection method, a dynamic wireless charging system with four segments is built for experimental verification. The experimental results show that when the phase angle threshold is set at 300°, the secondary side position can be accurately identified, and the proposed method is quite robust within a parameter deviation of up to 4%.