Anti-interference Characteristics Research Articles

Interference Characteristics of Electromagnetic Transient Overvoltage on Secondary Equipment of UHV Fixed Series Capacitors

This manuscript addresses the issue of electromagnetic radiation interference experienced by secondary equipment in ultra-high voltage (UHV) fixed series capacitors (FSCs) under electromagnetic transient overvoltage conditions, which cannot be easily determined. To tackle this, a simulation and analysis method for the electromagnetic interference characteristics of secondary equipment is proposed. First, a primary system simulation model of UHV FSC is established, including modeling the platform’s multi-conductor system. The electromagnetic transient overvoltage signals between the low-voltage busbar and the high-potential platform are then simulated and analyzed under two conditions: spark gap triggering and disconnector operation. Next, a finite element model of secondary equipment is created to simulate and analyze the electric field distribution of different materials in the area of the measuring box. The shielding effectiveness of the measuring box is calculated using the overvoltage signals at the measuring box location as excitation. This method allows for the simulation of the electric field distribution in the measuring box area for different materials and calculates the shielding efficiency of the measuring box. It effectively simulates the complex electromagnetic environment of secondary equipment, assesses the electromagnetic shielding efficiency of the measuring box, and provides a theoretical basis for analyzing and improving the anti-interference characteristics of the measuring box.

LPI radar waveform design based on complementary phase and discrete chaotic frequency joint coding

In order to reduce the probability of radar radiation signals being detected by enemy passive detection systems, this paper proposes a phase and frequency joint coding low intercept Radar waveform design method. Based on the linear frequency modulation signal, this method uses complementary binary code and chaotic sequence to phase encode the intra-pulse modulation. Code and frequency coding. The numerical simulation results show that the designed waveform exhibits pseudo-random characteristics in the time-frequency domain, and the low recognition performance is improved; The signal has an extremely low peak sidelobe level after matched filtering, showing excellent low intercept performance; its three-dimensional ambiguity function diagram presents an ideal “graph”. Fishing type”, with good distance, speed resolution and anti-interference characteristics.

Generation of NIR Spectral Band from RGB Image with Wavelet Domain Spectral Extrapolation Generative Adversarial Network

Near-infrared (NIR) imaging exhibits outstanding penetration capabilities and robust anti-interference characteristics. However, acquiring high-resolution and high-fidelity NIR images is difficult due to the limited mobility, high cost, and low resolution of NIR imaging hardware. In this paper, we proposed a new end-to-end Wavelet Domain Spectral Extrapolation Generative Adversarial Network (WSEGAN) to generate highly realistic NIR images from RGB images. Since RGB and NIR images have different types of noise and artifacts, which affects the quality of NIR images generation. We design a generator with a discrete wavelet transform and an attention mechanism to capture multi-resolution contextual information, and a multi-scale discriminator to capture detailed and global features. Then, the proposed approach is evaluated by three different datasets to achieve optimal results regarding both visual effects and quantitative evaluation. The normalized difference vegetation index (NDVI) is utilized to validate the effectiveness of the generated NIR images. The result demonstrates a strong correlation between the generated images and the actual vegetation distribution. More importantly, the proposed network is testified to generate NIR images to be fused with the RGB image source for agricultural target detection tasks. In dark conditions, results show that using multi-modal data instead of RGB images improves mAP0.5 detection accuracy by 4% on the CAPSICUM dataset and by 8% on the KIWI dataset across five object detection methods. This follows the physical significance of the NIR imaging and demonstrates the potential use of the NIR images generated by the proposed method.

Advancements in Key Parameters of Frequency-Modulated Continuous-Wave Light Detection and Ranging: A Research Review

As LiDAR technology progressively advances, the capability of radar in detecting targets has become increasingly vital across diverse domains, including industrial, military, and automotive sectors. Frequency-modulated continuous-wave (FMCW) LiDAR in particular has garnered substantial interest due to its efficient direct velocity measurement and excellent anti-interference characteristics. It is widely recognized for its significant potential within radar technology. This study begins by elucidating the operational mechanism of FMCW LiDAR and delves into its basic principles. It discuss, in depth, the influence of various parameters on FMCW LiDAR’s performance and reviews the latest progress in the field. This paper proposes that future studies should focus on the synergistic optimization of key parameters to promote the miniaturization, weight reduction, cost-effectiveness, and longevity of FMCW LiDAR systems. This approach aims at the comprehensive development of FMCW LiDAR, striving for significant improvements in system performance. By optimizing these key parameters, the goal is to promote FMCW LiDAR technology, ensuring more reliable and accurate applications in automated driving and environmental sensing.

Diagnosis for railway point machines using novel derivative multi-scale permutation entropy and decision fusion based on vibration signals

Abstract Railway point machines (RPMs) are safety-critical pieces of equipment closely related to train operation safety. Due to their high failure rate, it is urgent to develop an effective diagnosis method for RPMs. Considering the easy-to-collect and anti-interference characteristics of vibration signals, this paper develops a vibration-based diagnosis method. First, to address the difficulty of multi-scale permutation entropy in characterizing the fault information contained in the derivatives of the raw signal, a novel feature named derivative multi-scale permutation entropy is designed, which can further complete the fault information of RPMs. Second, to further improve the diagnosis accuracy of support vector machines, a decision fusion strategy based on three feature sets is developed, which can further improve the diagnosis accuracy, especially in the normal-reverse direction. Finally, the effect and superiority of the proposed method are verified based on the collected vibration signals from Xi’an Railway Signal Co.,Ltd by experiment comparisons. The diagnosis accuracies of reverse-normal and normal-reverse directions reach 99.43% and 100% respectively, indicating its superiority.

Object-plane encoding hyperspectral three-dimensional collaborative imaging method.

Different from traditional image-plane encoding spectral imaging method, this paper proposes an object-plane encoding hyperspectral three-dimensional collaborative imaging method, which is based on the idea of spectral displacement invariance and multiplexing encoding and decoding. The 4D data of the scene is scanned by coded apertures generated by the projector, and then the encoded data of the scene is obtained. During the reconstruction process, there is no need for phase unwrapping operation or data fusion. The reconstruction result shows excellent performance with a spectral resolution of 3 nm, nearly 120 spectral bands, depth accuracy of 0.25 mm. Compared with the image-plane encoding spectral imaging method, the object-plane encoding spectral imaging method exhibits better anti-interference characteristics, and the reconstruction quality of the object-plane encoding spectral imaging method is better than that of the image-plane encoding spectral imaging method in the scattering environments.

A novel naphthalimide-derived “turn-off” chemosensor for the detection of Cu2+, F- and CN- ions

The development of selective chemosensor for the detection of detrimental analytes in the environment is crucial due to their catastrophic effects. In this study, a novel Schiff base derived from naphthalimide and salicylaldehyde was designed and prepared for the detection of Cu2+, F-, and CN- ions in CH3CN as medium. The chemosensor exhibits a red shift in the presence of Cu2+, F-, and CN- ions accompanied by naked eye color change in the presence of F- and CN- ions. On the other hand, a “turn-off” response was observed in the presence of ion Cu2+, F-, and CN- ions in the fluorescent spectrum. The good anti-interference characteristics, strong binding, and low limit of detection (LOD) of the chemosensor revealed its sensitivity against Cu2+, F-, and CN- ions i.e. 1.25 × 10-5 M, 1.07 × 10-6 M, and 0.98 × 10-6 M, respectively. The binding ratio (1:1) was determined by Job's plot between the chemosensor and ions. In addition, the binding of ions with the chemosensor was proposed which was further supported by time-dependent density functional theory (TD-DFT) and IR spectrum data.

Optimal Design of Data Acquisition System for Fault Diagnosis of Hydraulic Machinery

Abstract Fault diagnosis of hydraulic machinery has high requirements on the synchronization of monitoring data and the anti-interference of monitoring equipment. The performance and data quality of the existing operation monitoring equipment of the unit cannot meet the requirements. At the same time, due to the variety of sensors and the different wiring methods of different types of sensors, the preparation work such as wiring of data acquisition equipment in the test is complicated. This paper analyzes the application requirements of fault diagnosis data and the problems existing in the conventional data collection process. A data collection solution specified for diagnosis of hydraulic machinery, which better solves the problem of data synchronization, is designed. The new designed system has high sampling accuracy and anti-interference characteristics, as well as the advantages of strong capability and simple equipment deployment. The proposed system has been applied in multiple power stations, pumping stations and pump test platforms. The relevant functions have been effectively verified.

Design of a Reconfigurable Band-notched Wideband Antenna using EBG Structures

A compact WLAN band-notched reconfigurable wideband antenna using two mushroom-like electromagnetic band-gap (EBG) structures is proposed in this paper. It is designed based on a dual wideband microstrip feed patch antenna with operating frequency bands of 2.2-3.7 GHz and 4.8-6 GHz. One of the EBG cells is positioned alongside the feed line, while the other EBG cell is laid on the back of the substrate. The patch or ground of the two EBG units are fed with a stronger current through a ground slot and a parasitic stub respectively, and the connections between the EBG structures and the antenna are controlled by loading a PIN diode with two 56 pF DC blocking capacitors. The advantage of this proposed design is that the antenna and the EBG unit can be designed independently. The proposed antenna has an overall size of 35×46×1.6 mm3. When testing the S11 of the antenna, the influence of the bias circuit on the antenna is also considered. The measured results show that the proposed antenna can generate two notched bands of 2.3-2.49 GHz and 5.11-5.51 GHz of WLAN, and the realized gain in the notch bands can be reduced to -2.65 dBi and -4.55 dBi, respectively, demonstrating its anti-interference characteristics, and can be applied in band notch broadband communication systems or anti-interference communication equipments such as unmanned aerial vehicles and radars.

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the structure and motion characteristics of the robot, a two-layer neural network topology model for the robot is constructed by coupling 22 Hopfield neuron nonlinear oscillators. Then, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), the membership functions are offline learned and trained to construct the CPG-ANFIS-PID motion control strategy for the robot. Through simulation research on the impact of CPG-ANFIS-PID input parameters on the swimming performance of the robot, it is verified that the control strategy can quickly respond to input parameter changes between different swimming modes, and stably output smooth and continuous dynamic position signals, which has certain advantages. Then, the motion performance of the robot prototype is analyzed experimentally and compared with the simulation results. The results show that the CPG-ANFIS-PID motion control strategy can output coupled waveform signals stably, and control the executing mechanisms of the pneumatic soft bionic robot to achieve biological rhythms motion propulsion waveforms, confirming that the control strategy has accuracy and anti-interference characteristics, and enable the robot have certain maneuverability, flexibility, and environmental adaptability. The significance of this work lies in establishing a CPG-ANFIS-PID control strategy applicable to pneumatic soft bionic robot and proposing a rhythmic motion control method applicable to pneumatic soft bionic robot.

Highly Conductive and Sensitive Wearable Strain Sensors with Metal/Nanoparticle Double Layer for Noninterference Voice Detection.

Human voice recognition via skin-attachable devices has significant potential for gathering important physiological information from acoustic data without background noise interference. In this study, a highly sensitive and conductive wearable crack-based strain sensor was developed for voice-recognition systems. The sensor was fabricated using a double-layer structure of Ag nanoparticles (NPs) and Ag metal on a biocompatible polydimethylsiloxane substrate. The top metal layer acts as a conducting active layer, whereas the bottom Ag NP layer induces channel cracks in the upper layer, effectively hindering current flow. Subsequently, the double-layer film exhibits a low electrical resistance value (<5 × 10-5 Ω cm), ultrahigh sensitivity (gauge factor = 1870), and a fast response/recovery time (252/168 μs). A sound wave was detected at a high frequency of 15 kHz with a signal-to-noise ratio (SNR) over 40 dB. The sensor exhibited excellent anti-interference characteristics and effectively differentiated between different voice qualities (modal, pressed, and breathy), with a systematic analysis revealing successful detection of the laryngeal state and glottal source. This ultrasensitive wearable sensor has potential applications in various physiological signal measurement methods, personalized healthcare systems, and ubiquitous computing.

An Improved Model-Free Adaptive Nonlinear Control and Its Automatic Application

In order to enhance the performance of model-free adaptive control (MFAC) in solving the control problem caused by interference and improve the tracking speed, this paper focuses on the analysis and research of the system affected by interference using the MFAC method. This method is based on dynamic linearization technology, with system data which are represented by a full format dynamic linearization (FFDL) model that is very similar to actual industrial processes. In this work, a control law is derived by incorporating and assigning weights to both the output error and the output error rate (OER) as the performance index. Rigorous proofs are provided to establish convergence and stability. Considering the inherent complexity of actual systems, this paper also presents the MFAC-OER scheme for multiple-input–multiple-output (MIMO) systems. Furthermore, the effectiveness and practicality of the improved control strategy are evaluated through numerical arithmetic examples and control processes involving water level regulation in a circulating fluidized bed (CFB). Comparisons with conventional MFAC and PID control methods show that the enhanced control method is capable of quickly and accurately tracking the desired signal. Additionally, it exhibits superior anti-interference characteristics and is able to respond in a timely manner to changes in the operating conditions of the circulating fluidized bed system. As a result, it ensures the normal operation of the coal saver and water supply pipe without damage.

A Parameter Estimation Algorithm for Damped Real-value Sinusoid in Noise

Abstract To improve the parameter estimation performance of damped real-value sinusoid in noise, a novel algorithm with high accuracy and computational efficiency is proposed that combines the characteristics of good anti-interference, small computation of frequency-domain methods, and high parameter estimation accuracy of time-domain methods. First, the Discrete Fourier Transform (DFT) algorithm and the two-point spectrum interpolation algorithm of the frequency-domain methods are used to improve the noise immunity. Then, the linear prediction property and the enhancement filter of the time-domain methods are used to improve the parameter estimation accuracy. In addition, the parameter estimation performance of the proposed algorithm is verified by computational complexity analysis and test experiments, and the practical application effectiveness of the proposed algorithm is demonstrated on the Coriolis Mass Flowmeter (CMF) experimental platform. The experimental results show that the proposed algorithm effectively improves the real-time performance and the parameter estimation accuracy is better than that of the existing excellent algorithms.

Immunity of shunt active power filter based on improved LADRC

To improve the dynamic response speed and performance of active power filter controller, and improve the robustness, tracking ability, and disturbance rejection ability of linear active disturbance rejection controller (ADRC), an improved linear ADRC (LADRC) is proposed. First, a new error adjustment total disturbance is introduced into the linear expansion state observer to adjust the total disturbance of the linear expansion state observer. Then, on the premise of system stability, the controller is applied to the voltage outer loop of shunt active power filter (SAPF), and the mathematical model of active power filter is deduced, and it is controlled according to the first-order linear active disturbance rejection controller. Finally, through frequency domain analysis, the stability, noise immunity, and tracking performance of the improved LADRC are analyzed. Using MATLAB and Simulink simulation platform, the current stability and tracking performance of SAPF under improved LADRC control are simulated and verified, and compared with traditional methods. The simulation results show that the waveform fluctuation of A-phase voltage on the grid side of this method is relatively smooth, and the voltage on the grid side is always kept at ±50 V; the voltage curve of SAPF DC side is kept between the actual set values, about 820 V; the waveform fluctuation of A-phase current on the load side is small, which is ±220 A; the harmonic distortion rate is 4%. It is verified that this method has good tracking effect and anti-interference characteristics, which is of great significance to improve the control performance of active power filter.

Liquid metal enabled plant injectable electronics

Extensive efforts have been made on utilizing conductive materials to monitor plant growth states. However, traditional methods are facing difficulties as physiological signals are usually concealed within plant tissues. Here, we propose a new conceptual plant injectable electronics based on the fluidic properties and high conductivity of liquid metals, which can not only resolve the existing challenges but also endow plants with diverse electronic capabilities. Following this principle, the basic electronic components (resistors, inductors, and capacitors) are successfully fabricated by injecting liquid metal into the target sites of the living plant. Furthermore, we demonstrate typical applications derived therefrom, including highly stable electrodes, long-term working sensors, and stealthy antennae with variable characteristics. Specifically, the resulting liquid metal injectable electrodes exhibit outstanding electric signal capture capability (over 2000% improvement versus printed electrodes), and remarkable anti-interference characteristics compared to conventional rigid needle electrodes. Injectable resistance and capacitance sensors provide ever-useful ways for real-time monitoring of plant position and physiological signals. More importantly, the capacitive sensor obtained by injection gives access to information about the interior of the plant that cannot be detected from non-injectable capacitive sensors otherwise. Additionally, antennas invisible from the outside with variable characteristics are manufactured and evaluated in situ in living plants, further justifying the capability of the plant injectable electronics. The present principle suggests an unconventional strategy to combine plants and electronics, which signifies a paradigm shift and is expected to serve as a basic platform for additional investigation in plant electrophysiology, electronic plants, and plant robots.

Visual Attention Quality Research for Social Media Applications: A Case Study on Photo Sharing Applications

With the rapid growth of smart terminal industry and User-Generated Content products, Social Media Applications (SMA) products, represented by TikTok, have been booming growth. How to capture and maintain users’ attention in order to prolong their stay on the product and increase customer stickiness has become the focus of the industry. Therefore, according to the duration and characteristics of users using SMA, this paper takes the layout of SMA as an example to study the visual attention quality. Firstly, through the literature review, the study of visual attention quality in SMA was summarized into four aspects, including the span, maintenance, allocation, and switch of attention. Secondly, eye movement and behavior experiments were designed based on common content consumption tasks of SMA users to verify the hypotheses proposed in this paper. According to the results: (1) In terms of attention maintenance, linear layout outperformed masonry layout, masonry layout outperformed matrix layout, and in terms of attention span, the reverse was true; (2) In attention allocation, linear layout showed the best anti-interference characteristics; The masonry layout is suitable to be used in the task search stage and also in the dual-task execution stage; (3) In terms of attention switch, the energy cost of attention switch increased in the order of matrix layout, masonry layout and linear layout. (4) In terms of interaction, double-clicking interaction had more advantages in attention allocation and cognitive load than swiping interaction. The research in this paper has provided objective and quantitative data support for the design and operation of SMA products.

Insight into TEMPO-oxidized cellulose-based composites as electrochemical sensors for dopamine assessment

The diagnosis and treatment of many neurological and psychiatric problems depend on establishing simple, inexpensive, and comfortable electrochemical sensors for dopamine (DA) detection. Herein, 2,2,6,6 tetramethylpiperidine-1-oxyl (TEMPO)-oxidized cellulose nanofibers (TOC) were successfully loaded with silver nanoparticles (AgNPs) and/or graphite (Gr) and crosslinked by tannic acid, producing composites. This study describes a suitable casting procedure for the composite synthesis of TOC/AgNPs and/or Gr for the electrochemical detection of dopamine. Electrochemical impedance spectra (EIS), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) were employed to characterize the TOC/AgNPs/Gr composites. In addition, the direct electrochemistry of electrodes treated with the prepared composites was examined using cyclic voltammetry. The TOC/AgNPs/Gr composite-modified electrode improved electrochemical performance towards detecting dopamine compared to TOC/Gr-modified electrodes. Upon employing amperometric measurement, our electrochemical instrument has a wide linear range (0.005–250 μM), a low limit of detection (0.0005 μM) at S/N = 3, and a high sensitivity (0.963 μA μM−1 cm−2). Additionally, it was demonstrated that DA detection seemed to have outstanding anti-interference characteristics. The proposed electrochemical sensors meet the clinical criteria regarding reproducibility, selectivity, stability, and recovery. The straightforward electrochemical method utilized in this paper may provide a potential framework for creating dopamine quantification biosensors.

Multi-domain united link adaptation technique in high-throughput satellite communication system

Under the condition of using the same frequency resources, the communication capacity of high-throughput satellites is tens or even hundreds of times higher than that of traditional satellites. Compared with traditional satellites, high-throughput satellites have a large capacity, high speed, and anti-interference characteristics. However, the high-throughput satellite communication link using Ku/Ka-band is vulnerable to weather factors such as rain attenuation, so the system should have a control mechanism to achieve fade countermeasures. The existing methods include transmission power adjustment, mod cod adaptive adjustment, carrier symbol rate adjustment, etc. In this paper, various technical means are comprehensively used to compare and analyze the effect of combined control and propose a multi-domain united link adaptation technique to optimize link availability and resource utilization.

In-Orbit Calibration of Phase Retardance for Channeled Spectropolarimeter.

The phase retardance of the optical system (PROS) is a crucial factor limiting the accuracy of the Stokes vector reconstruction for the channeled spectropolarimeter. The dependence on reference light with a specific angle of polarization (AOP) and the sensitivity to environmental disturbance brings challenges to the in-orbit calibration of PROS. In this work, we propose an instant calibration scheme with a simple program. A function with a monitoring role is constructed to precisely acquire a reference beam with a specific AOP. Combined with numerical analysis, high-precision calibration without the onboard calibrator is realized. The simulation and experiments prove the effectiveness and anti-interference characteristics of the scheme. Our research under the framework of fieldable channeled spectropolarimeter shows that the reconstruction accuracy of S2 and S3 in the whole wavenumber domain are 7.2 × 10-3 and 3.3 × 10-3, respectively. The highlight of the scheme is to simplify the calibration program and ensure that the PROS high-precision calibration is not disturbed by the orbital environment.

MIL-88B(Fe) MOF modified screen-printed electrodes for non-enzymatic electrochemical sensing of malathion

ABSTRACT An enzyme-free electrochemical approach for ultra-trace quantification of the organophosphate insecticide malathion is proposed in this study. It is premised on screen-printed carbon electrodes modified by the MIL-88B(Fe) metal–organic framework (MOF). A one-pot solvothermal method was used to synthesise MIL-88B(Fe). The surface modification of electrodes allowed for increased electroactive surface area and accelerated electron transport on the electrode. Inhibition in the redox signal of MIL-88B(Fe) was observed due to the affinity between metal centres of the MOF and the functional groups of malathion, leading to an accurate determination of malathion. The proposed sensor effectively quantified malathion in the wide concentration range of 1 × 10−12 M to 1 × 10−6 M. The limit of detection for malathion was 0.79 pM. The proposed sensor also possessed excellent stability, repeatability, and anti-interference characteristics. Furthermore, the proposed sensor demonstrated satisfactory malathion recovery in spiked vegetable samples.