bluuebunny/crossref_metadata_2025 huggingface dataset:
Clear imaging of ion cloud rotation using a combination of a thin metal wire, a micro-channel plate attached to a phosphor screen, and a high-speed camera
Authors: Nakajima Yutaro , Himura Haruhiko , Okada Toshikazu
Published: April 2022

To obtain the radial profile of the ion velocity ui(r) of a pure ion cloud, for the first time, we successfully captured images of the shadow of a thin rotating metal wire by scanning the pure ion cloud using a combination of a micro-channel plate attached to a phosphor screen and a high-speed camera. It appears that the rotation angle of the measured metal wire agrees with the estimated value based on the theory of two-dimensional equilibria of non-neutral plasmas, rather than the magnetron motion of a single ion confined in a Penning trap. This method may be utilized as a tool to experimentally investigate ui(r, t) in electrically non-neutral two-fluid plasmas, which is an unexplored topic in advanced plasma physics.
Efficiency of nonthermal particle acceleration in magnetic reconnection
Authors: Hoshino Masahiro
Published: April 2022

The nonthermal particle acceleration during magnetic reconnection remains a fundamental topic in several astrophysical phenomena, such as solar flares, pulsar wind, and magnetars, for more than half a century, and one of the unresolved questions is its efficiency. Recently, nonthermal particle acceleration mechanisms during reconnection have been extensively studied by particle-in-cell simulations, yet it is an intriguing enigma as to how the magnetic field energy is divided into thermally heated plasmas and nonthermal particles. Here, we study both non-relativistic and relativistic magnetic reconnections using large-scale particle-in-cell simulation for a pair plasma and indicate that the production of the nonthermal particle becomes efficient with increasing the plasma temperature. In the relativistic hot plasma case, we determine that the heated plasmas by reconnection can be approximated by a kappa distribution function with the kappa index of approximately 3 or less (equivalent to 2 or less for the power-law index), and the nonthermal energy density of reconnection is approximately over 95% of the total internal energy in the downstream exhaust.
The features of haloacetic acid oxidation that contribute to stratospheric ozone depletion
Authors: Savilov Serguei V. , Strokova Natalia E. , Ivanov Anton S. , Kuramshina Gulnara M. , Morozov Igor I.
Published: April 2022

Environmental context Due to The Montreal Protocol, stratospheric ozone concentration is slowly regenerating, however, the recovery rate is slower than predicted by photochemical models. FTIR spectroscopy together with quantum chemical calculations confirmed that ozone reacts with halogenated acids adsorbed at a model aerosol surface. Reactions occur at low temperatures without photochemical activation with formation of halogen oxides that are known to promote catalytic cycles of ozone depletion. Abstract The present work addresses the problem of stratospheric ozone depletion. While gas phase and photochemically induced reactions of ozone are well studied, the mechanisms of heterogeneous O3 interactions with different halogenated species still remain uncertain. An in situ FTIR investigation of low-temperature heterogeneous reactions of ozone and haloacetic acids in conditions close to stratospheric was performed and supported by ab initio quantum chemical calculations. Products of ozone reaction with differently chlorine and bromine-substituted acetic acids were identified and possible reactions pathways were suggested. Ozone can attach to a carbon atom to release a halogen atom that forms a halogen oxide. Halogen oxide in its turn can take part in the catalytic cycles of ozone depletion. Suggested reaction pathways leading to the additional release of the chlorine oxides can enhance the atmospheric models that calculate ozone concentration.
Local Density of States Modulated by Strain in Marginally Twisted Bilayer Graphene
Authors: Ma Jia-Jun , Wang Zhen-Yu , Xu Shui-Gang , Gao Yu-Xiang , Zhang Yu-Yang , Dai Qing , Lin Xiao , Du Shi-Xuan , Ren Jindong , Gao Hong-Jun
Published: April 2022

In marginally twisted bilayer graphene, the Moiré pattern consists of the maximized AB (BA) stacking regions, minimized AA stacking regions and triangular networks of domain walls. Here we realize the strain-modulated electronic structures of marginally twisted bilayer graphene by scanning tunneling microscopy/spectroscopy and density functional theory (DFT) calculations. The experimental data show four peaks near the Fermi energy at the AA regions. DFT calculations indicate that the two new peaks closer to the Fermi level may originate from the intrinsic heterostrain and the electric field implemented by back gate is likely to account for the observed shift of the four peaks. Furthermore, the dI/dV map across Moiré patterns with different strain strengths exhibits a distinct appearance of the helical edge states.
Single-focus phase singularity generated by spiral zone plate with quasi-random distributed quantum dots
Authors: Zang Huaping , Miao Zhuanglei , Liang Erjun , Li Yongjie , Fan Quanping , Wei Lai , Zhou Weimin , Cao Leifeng
Published: April 2022

We report on a new vortex lens for producing a single-focus phase singularity which is termed as a quasi-random-dot-array binary spiral zone plates (QBSZPs). Differing from the abrupt transitions of the conventional spiral zone plates (SZPs), the key idea of the QBSZPs is to realize a sinusoidal transmittance by properly arranging lots of quantum dot arrays which take on the values of 0 and 1 in two dimensions. In this typical design, the number density of the selected primitives obey sinusoidal distribution along the radial direction and quasi-random in the azimuthal direction. Theoretical analysis indicates that the higher-order foci which inevitably exist in the SZPs have been indeed effectively suppressed with the QBSZPs. Moreover, the focusing performance of the QBSZPs is influenced by the ratio of circumcircle diameter of the primitives to the outermost zone width. These findings, which have been demonstrated by the performed experiment, may offer a new direction towards improving the performance of biomedical imaging, quantum computation and optical manipulation.
Research on bearing fault diagnosis method based on transformer neural network
Authors: Yang Zhuohong , Cen Jian , Liu Xi , Xiong Jianbin , Chen Honghua
Published: April 2022

The Attention mechanism (AM) has been widely used for fault diagnosis and identifying the health of industrial equipment. Existing research has only used AM in combination with deep networks, or to replace certain components of these deep networks. This reliance on deep networks severely limits the feature extraction capability of AM. In this paper, a bearing fault diagnosis method is proposed based on a signal Transformer neural network (SiT) with pure AM. First, the raw one-dimensional vibration time-series signal is segmented and a new segmented learning strategy is introduced. Second, linear encoding and position encoding are performed on the segmented subsequences. Finally, the encoded subsequence is fed to the Transformer for feature extraction to achieve fault identification. The validity of the proposed method is verified using the Case Western Reserve University dataset and the self-priming centrifugal pump bearing dataset. Compared with other existing methods, the proposed method still achieves the highest average diagnostic accuracy without any data preprocessing. The results demonstrate that the proposed SiT based on pure AM can extract features and identify faults from the raw vibration signal, and has superior diagnostic performance.
Phenomenological optics with self-made liquid lenses in the physics classroom
Authors: Spiecker Henrike , Bitzenbauer Philipp
Published: April 2022

Why does a raindrop on a window pane show an image of the environment that is turned upside-down? And why does vision go blurry underwater, but is perfectly clear with diving goggles? Our everyday life is rich in optical phenomena. Unfortunately, these phenomena often play a subordinate role in Optics teaching, compared to ray constructions or mechanistic light models. In our new teaching-learning sequence designed for introductory physics courses at secondary schools, the observation of the phenomena assumes a more prominent position and the observer’s sense of sight becomes the starting point of learning about Optics. The centrepiece of our concept is the use of students’ self-made Optics inventory including liquid lenses in various experiments.
Investigation of the switching characteristics of high-pressure subnanosecond gas dischargers with the purpose of a sharp increasing of the breakdown voltages and the switching speed
Authors: Ivanov Stepan N
Published: April 2022

The paper analyzes the data obtained in the subnanosecond time range on the times (t
br) and speeds (V
br) of switching of hydrogen diode dischargers. These data were obtained in a wide range of hydrogen pressures (p) and the degree of the discharge gap overvoltage (the length of the cathode–anode gap d) in a uniform electric field. It is shown that the reduced strength of the average electric field E
br/p in the discharge gap at the moment of the beginning of the breakdown significantly decreases when the gas pressure increases from 5 atm to 50 atm. An increase in pressure from 50 atm to 60 atm leads to a sharp (by 40% ÷ 135%, depending on the d) increase in the pulse breakdown voltage (U
br) and an increase in E
br/p. In proportion to the growth of E
br/p the switching speed V
br of the discharge gas gap increases. The observed effect is explained by the change in the discharge initiation mechanisms. The limitation of U
br and V
br in the hydrogen pressure range from 5 atm to 50 atm occurs as a result of gas ionization by runaway electrons and the subsequent development of a multi-avalanche discharge in the volume of the discharge gap. With a further increase in pressure, the discharge develops according to the streamer type. To design ultrafast gas dischargers of the subnanosecond range intended for switching high voltages, it is necessary to select an appropriate range of working gas pressures in order to ensure the development of a streamer-type discharge.
Overcoming temporal dispersion for measurement of activity-related impedance changes in unmyelinated nerves
Authors: Tarotin Ilya , Mastitskaya Svetlana , Ravagli Enrico , Perkins Justin D , Holder David , Aristovich Kirill
Published: April 2022

Objective. Fast neural electrical impedance tomography is an imaging technique that has been successful in visualising electrically evoked activity of myelinated fibres in peripheral nerves by measurement of the impedance changes (dZ) accompanying excitation. However, imaging of unmyelinated fibres is challenging due to temporal dispersion (TP) which occurs due to variability in conduction velocities of the fibres and leads to a decrease of the signal below the noise with distance from the stimulus. To overcome TP and allow electrical impedance tomography imaging in unmyelinated nerves, a new experimental and signal processing paradigm is required allowing dZ measurement further from the site of stimulation than compound neural activity is visible. The development of such a paradigm was the main objective of this study. Approach. A finite element-based statistical model of TP in porcine subdiaphragmatic nerve was developed and experimentally validated ex-vivo. Two paradigms for nerve stimulation and processing of the resulting data—continuous stimulation and trains of stimuli, were implemented; the optimal paradigm for recording dispersed dZ in unmyelinated nerves was determined. Main results. While continuous stimulation and coherent spikes averaging led to higher signal-to-noise ratios (SNRs) at close distances from the stimulus, stimulation by trains was more consistent across distances and allowed dZ measurement at up to 15 cm from the stimulus (SNR = 1.8 ± 0.8) if averaged for 30 min. Significance. The study develops a method that for the first time allows measurement of dZ in unmyelinated nerves in simulation and experiment, at the distances where compound action potentials are fully dispersed.
Gaussian mixture modelling by exploiting competitive stop EM algorithm
Authors: Jia Kexin , Xin Yuxia , Cheng Ting
Published: April 2022

To improve the robustness of order selection and parameter learning for Gaussian mixture model (GMM), this paper proposes a competitive stop expectation-maximization (EM) algorithm, which is based on two stop conditions. The first condition is a Lilliefors test based multivariate (MV) normality criterion, which is used to determine whether to split a component into two different components. The EM algorithm stops splitting when all components have MV normality. The minimum description length (MDL) criterion is used in the second condition, which competes with the first condition to prevent the EM algorithm from over-splitting. Simulation experiments verify the effectiveness of the proposed algorithm.
Inverse kinematic solver based on machine learning sequential procedure for robotic applications
Authors: Aggogeri Francesco , Pellegrini Nicola , Taesi Claudio , Tagliani Franco Luis
Published: April 2022

This paper presents an inverse kinematic solver for a robotic arm based on an artificial neural network, ANN, architecture. The motion of the robotic arm is controlled by the kinematics of the ANN. The novelty of the proposed method is the validation using a proprietary robot of a novel procedure that applies three networks in a sequential mode to predict one joint value at a time. The inclusion of the genetic algorithm in the ANN definition and the adoption of sequential technique significantly reduced the manual settings and increased the obtained accuracy with respect to the traditional network deployment. The simulated outcomes proved the efficacy of the proposed approach in robotic motion control. The final architecture has three hidden layers: {40 (tansig), 35 (tansig), 30 (tansig)}. The resultant MSE in joint space is close to 3.235*10-4 rad2 and 0.1318mm2 in Cartesian space for the testing dataset. The maximum trajectory error for the validation curves, a planar circle and a spatial spring, is lower than 0.27mm for each axis.
Outdoor real-time RGBD sensor fusion of stereo camera and sparse lidar
Authors: Kong Qi , Zhang Liangliang , Xu Xin
Published: April 2022

Autonomous driving technology relies on high-resolution, high-performance vision sensing technology. As the two most popular sensors in the industry, Lidar and stereo cameras play an important role in sensing, detection, control and planning decisions. At this stage, the Lidar can obtain more accurate depth map information, but with the increase of resolution, its cost increases sharply and cannot be applied in large scale in the market. At the same time, the depth detection scheme based on computer vision has high resolution, but the data accuracy is very low. In order to solve the practical application defects of the above two sensors, this paper proposes a new sensor fusion method for stereo camera and low-resolution Lidar, which has high resolution, high performance and low cost. This paper adopts new sensor design, multi-sensor calibration, classification and selection of Lidar pointcloud features, large-scale and efficient stereo image matching and depth map calculation, and method of filling missing information based on pointcloud segmentation. To verify the effectiveness of the method in this paper, this paper used high-resolution Lidar as ground truth for comparison. The results show that the fusion method can achieve an average improved accuracy of 30% within a close range of 30 meters, while achieving 98% resolution. In addition, this paper presents a scheme for visualizing multi-sensor image fusion, and encapsulates five modules: multi-sensor calibration, large-scale stereo depth calculation, low-resolution Lidar simulation, sensor data fusion, and fusion image and error visualization, in order to facilitate future secondary development.
Collision-free control strategy for on-ramp merging: A spatial-dependent constraint following approach
Authors: Tianchuang Meng , Zhanyi Hu , Jin Huang , Diange Yang , Zeyu Yang , Zhihua Zhong
Published: April 2022

This paper focuses on the problem of on-ramp merging control under the cooperation of intelligent and connected vehicles. A decentralized collision-free control strategy is proposed for on-ramp merging control. Each vehicle in the virtual platoon constructed by all vehicles on the arterial road and the on-ramp is equipped with a spatial-dependent constraint following controller. Under nonlinear vehicle dynamics, the proposed controller is proved to be uniformly bounded, thus assuring that each vehicle can satisfy the safety requirements to avoid collision at any specific spatial location, especially at the most dangerous merging point. Compared with time-dependence, this spatial-dependence means much more stability because spatial conditions during the on-ramp merging process are more static and invariant. Finally, a simulation containing six vehicles with relatively extreme testing conditions is conduct to validate the effectiveness of the proposed approach. The results demonstrate that the spacing errors can converge to 0 with respect to varying spatial-dependent desired spacings. The spacing errors of the six vehicles are kept at a relatively low level with a maximum value of 3.0778m. The maximal acceleration is 0.6060 m/s 2 and the maximal deceleration is -1.4042 m/s 2. All vehicles can achieve collision-free safety for on-ramp merging with a smooth and non-saturated control input generated by the proposed controller.
Design of Home-use Fire Fighting Robots and Research on Automatic Control System
Authors: Ma Yuchen , Zhang SiYang , Wang Yifan
Published: April 2022

Responding quickly to fires, reducing secondary disasters and ensuring the safety of life and property are important issues in firefighting. With the progress of science and technology, firefighting robots have entered people’s sight. Based on this, this paper proposes a home-based firefighting robot to reduce fire losses. The home-type firefighting robot is equipped with a walking system and a clamping device. ANSYS software is used to perform finite element analysis on key components to verify the rationality of the structural design. The program mainly uses the PWM module in the K60 chip, and the I/O module is designed. CCD is used for image acquisition and K60 microprocessor. The classical PID control algorithm is still used to make the fire robot achieve the effect of smooth and fast movement. The incremental PID algorithm is used to realize the fast response of the motor.
Integrated decision and control at multi-lane intersections with mixed traffic flow
Authors: Jiang Jianhua , Ren Yangang , Guan Yang , Eben Li Shengbo , Yin Yuming , Yu Dongjie , Jin Xiaoping
Published: April 2022

Autonomous driving at intersections is one of the most complicated and accident-prone traffic scenarios, especially with mixed traffic participants such as vehicles, bicycles and pedestrians. The driving policy should make safe decisions to handle the dynamic traffic conditions and meet the requirements of on-board computation. However, most of the current researches focuses on simplified intersections considering only the surrounding vehicles and idealized traffic lights. This paper improves the integrated decision and control framework and develops a learning-based algorithm to deal with complex intersections with mixed traffic flows, which can not only take account of realistic characteristics of traffic lights, but also learn a safe policy under different safety constraints. We first consider different velocity models for green and red lights in the training process and use a finite state machine to handle different modes of light transformation. Then we design different types of distance constraints for vehicles, traffic lights, pedestrians, bicycles respectively and formulize the constrained optimal control problems (OCPs) to be optimized. Finally, reinforcement learning (RL) with value and policy networks is adopted to solve the series of OCPs. In order to verify the safety and efficiency of the proposed method, we design a multi-lane intersection with the existence of large-scale mixed traffic participants and set practical traffic light phases. The simulation results indicate that the trained decision and control policy can well balance safety and tracking performance. Compared with model predictive control (MPC), the computational time is three orders of magnitude lower.
The invention relates to a small logistics handling trolley based on omni-directional wheel movement
Authors: Yang Xinyu
Published: April 2022

Through the research and analysis of the existing gantry crane and cantilever crane to unload and transport goods, at the same time the application of the characteristics of triangular stability, a combination of the advantages of the three; A triangular omnidirectional cantilever crane is designed and developed by using electric push rod instead of rope lifting and the most basic triangular body.
Research on slope monitoring based on array inclinometer technology
Authors: Xing Yuxuan , Li Xisheng , You Jia , Shu Xiongying , Hu Tao , Zheng Cheng Cai
Published: April 2022

Based on the requirement of slope stability monitoring, an inclinometer with MEMS accelerometer array is designed. The inclinometer consists of a control module based on STM32 and a measurement module based on triaxial accelerometer. When the slope is displaced, the position of the accelerometer changes in space, and the accelerometer generates an output, which is sent to STM32, then calculated and converted to realize the attitude analysis. Finally, it is sent to the upper computer through the 485 bus. The equipment uses the attitude analysis algorithm based on Euler angle and vector superposition method to realize the two-dimensional image representation of slope inclination.
Research on the position and attitude control method of the spatial arc for a five-axis hybrid tapping robot
Authors: Wu Taiyu , Gu Jin , Zhang Yawei , Zhang Bin
Published: April 2022

Automatic rubber harvesting can not only reduce the cost of latex production, but also stabilize the output and improve the production efficiency. In order to lay the foundation for the movement of the robot around the tapping trajectory and meet the performance requirements of the robot in the tapping operation, this paper studies the position and attitude interpolation algorithm of the spatial arc for a five-degree-of-freedom hybrid tapping robot to realize the synchronous motion of the spatial arc pose control. In the verification test, the tip of the pen installed at the end of the robot draws a coherent clear arc in the space. The end vector is perpendicular to the normal vector of the arc trajectory and keeps pointing to the center of the trajectory at the same time, which verifies the correctness of the position and attitude control method.
Design of Embedded Line Galloping Monitoring System Based on Wireless Communication Technology
Authors: Gong Yu , Dai Yunfeng , Liu Anhong , Chen Wen , Xu Feng , Zhao Yiyi
Published: April 2022

In order to meet the requirements of multi-measurement nodes and high temperature resistance, this project draws extensive experience from relevant industries based on the relevant requirements. A bus temperature measurement system based on two-bus technology is developed. The system is based on two buses and combines OFDM technology to modulate signals on carriers with different frequencies. Through parallel transmission, the original signal is demodulated using differential coherent demodulation. The simulation results show that the system can effectively deal with channel signal interference.
A new method for automated driving image defogging based on improved dark channel prior
Authors: Huang Shanshan , Qin Haoxing , Li Qingchao , Yuan Hua
Published: April 2022

To tackle the problem of blurred image subjects due to haze in the images captured by the automatic driving system, which affects the safety of automated driving, a new, improved dark channel image defogging method based on adaptive domain dark channel calculation, fast bilateral filtering to optimize transmittance and automatic color equalization is proposed. First, map the original image based on the haze image degradation model and evaluate the atmospheric light intensity and transmittance based on the adaptive domain. Then, the atmospheric transmittance is optimized by combining the powerful value filtering with the fast bilateral filtering method. Finally, the image is further optimized by using the multi-channel automatic color gradation equalization method to solve the phenomenon of oversaturated color and dark brightness in the filtered image. The results show that the algorithm of this paper has high clarity and contrast, reduces the computation and running time, preserves the image edge information, has an excellent fog removal effect, and is highly adaptive for automatic driving image processing.
Research on braking dynamics of multi-axle vehicle
Authors: Yan Yan , Chen Xu , Wang Wenzhe , Hang Peng , Chen Haishan , Liu Jinbo
Published: April 2022

Braking dynamics is an important part of longitudinal dynamics. Through the analysis of braking performance of multi-axle vehicles, we can deepen our understanding of longitudinal dynamics. Starting from the braking dynamics analysis of the whole vehicle, this paper proposes to establish the braking dynamics model of multi-axle vehicle by using the suspension deformation coordination equation, so as to calculate the general calculation formula of ground reaction force of multi-axle vehicle when braking. The brake force distribution of 4-axle brake is analyzed to verify its rationality and provide basis for multi-axle brake design.
Research on multi-functional intelligent ventilator based on UC/OS-III operating system for gas concentration detection
Authors: Ren Ziqiong , Yu Haoze , Wang Shuaifeng , Li Jinwei , Huang ShuangXi , Guo Yeyong
Published: April 2022

In order to change the traditional gas concentration inspection and exhaust device, the system through the gas concentration to control the rotation of the fan, to achieve real-time gas concentration monitoring, alarm control and GPS global positioning. In this study, STM32F4ZGT6 with ARM Coretex-M4 as the core controller is combined with embedded system design, and MDK is used to develop software programming. Through the ADC MQ-9 carbon monoxide sensor detection module and infrared NDIR carbon dioxide sensor detection module of the output of the analog conversion to digital quantity acquisition and processing, when the gas concentration exceeds the pre-set threshold, triggering a buzzer alarm, timer and the energy conservation and exhaust fan work, implementation is beyond the rapid circulation of the gas and gas concentration inside and outside the display of the time.Through bluetooth and mobile phone connection, real-time check of gas concentration, using the upper computer to control the operation mode of exhaust fan and change the gas concentration threshold. Modular programming is adopted in this study to improve the maintainability and facilitate debugging and modification in the later stage of the study. Through practical verification, the system can realize the detection of carbon monoxide and carbon dioxide concentration, real-time alarm monitoring, GPS positioning and change exhaust fan working mode and other functions, with real time, practicality and reliability.
Design of wireless voice transmission system based on nRF52833
Authors: Xue BaoBao , Wang ZhiFeng
Published: April 2022

This article chooses pulse density modulation, 2.4GHZ radio frequency, I2S bus nRF52833 chip as the central processing unit to develop the wireless audio transmission system. And carry on the theoretical design and analysis to the hardware module and software module of the whole system, and test the RF distance and power consumption, as well as the audio delay and fidelity, basically realise the design of the wireless voice transmission system based on nRF52833.
Design of a phased array with a beam scanning functionality based on the arithmetic phase difference
Authors: Fan Haifeng , Zhang Yiming , Wang Xuhong , Gao Junxia
Published: April 2022

The demand for phased array antennas increases not only for the traditional military industry but also in commercial areas such 5G mobile network platforms, Internet of Things (IoT), and satellite communication applications. In this paper, a phased array with beam scanning function is designed based on arithmetic phase difference between array elements. In the design process, the initial complex model is simplified into a simple element model with periodic conditions, which makes the analysis faster and more efficient. Finally, two phased array designs based on microstrip patch antenna are studied, and the simulation results verify the correctness of the design method.
Rolling bearing fault diagnosis method based on OSFFDM and adaptive multi-scale weighted morphological filtering
Authors: Huang Siqi , Wang Xinglong , Yang Siguo , Tan Zhiyin
Published: April 2022

The Order-statistic filtering Fourier decomposition (OSFFDM) is a decomposition method that obtains components of different frequency bands by pre-processing the Fourier spectrum. The OSFFDM method overcomes the problem of a large number of invalid components in FDM. However, OSFFDM only considers the frequency band search problem, and does not really solve the interference problem of noise and irrelevant components. To solve this problem, a bearing fault diagnosis method named OSFFDM and adaptive multi-scale weighted morphological filtering (AMWMF) is proposed. First, the order-statistic filtering and smoothing methods are used to fit the envelope trend term of the Fourier frequency spectrum of the raw signal. Second, according to the envelope trend, a series of single components are obtained through the idea of segmentation and reconstruction. Then, the AMWMF is used to filter the component with the maximum kurtosis value. Finally, the envelope spectrum is used to analyze the filtered signal. In the analysis of the actual collected bearing vibration signal, the diagnostic results of the combination of OSFFDM and AMWMF and existing methods such as EMD and FDM are studied and compared. From the comparison results, it can be observed that the OSFFDM and AMWMF method can effectively identify bearing fault information. By calculating the signal-to-noise ratio (SNR) of the optimal component, the proposed method has a higher SNR, that is, less noise interference. The comparison of the diagnosis results further verifies the effectiveness and superiority of the OSFFDM and AMWMF method.
Research and Application of the Network Security Monitoring Capability Evaluation Model of Power Control System Based on AHP and Fuzzy Comprehensive Evaluation
Authors: Wang Penghao , Wang Shaobo , Chi Lijun , Ren Xiaokai , Wu Wei , Cheng Wenjie
Published: April 2022

In recent years, China’s cyberspace security is facing increasingly severe challenges. As the national key basic information infrastructure, power control system is very important which is related to the national economy and the people’s livelihood. So network security of power control system should be taken seriously. The network security monitoring capability of power control system has a direct impact on the security of power business such as power production and supply. However, there are few studies on the evaluation of its network security monitoring capability. This paper puts forward the network security monitoring capability evaluation model of power control system based on AHP and fuzzy comprehensive evaluation, according to the research of public network security management capability evaluation, the particularity of network security monitoring system of power control system and the investigation opinions of 20 expert teams in power industry’s network security field. Then, the model is used to evaluate the network security monitoring capability of three municipal power control systems, and the final scores are 93.09, 88.65 and 90.17 respectively. The model established in this paper realizes the quantitative evaluation of the network security monitoring capability of the power control system. And it will help the power company to carry out targeted rectification and improvement according to the calculating result of this model. So the research and application in this paper has a certain practical engineering significance.
EMI Analysis of a Switching Power Supply
Authors: Li Leixin , Zhang Xiangjin
Published: April 2022

Switching power supply is easy to produce electromagnetic interference in the working process. Switching power supply is both an interference source and a sensitive device. Therefore, the boost circuit of switching power supply is modelled and simulated. It is concluded that the surge current and peak voltage generated by the boost circuit are the main causes of electromagnetic interference. According to the reasons, the electromagnetic interference suppression measures are proposed. It mainly includes three measures, namely adding capacitors at both ends of the switching tube, adding a filter circuit at the low voltage input end of the switching power supply, adding an optical coupler equipment and adding a common-differential-mode synthetic choke coil filter. These measures all effectively reduce the influence of electromagnetic interference of the switching power supply, and they are beneficial to improve the reliability of the switching power supply.
Fault analysis caused by short circuit current DC component Related to circuit breaker
Authors: Wu Tianbo , Yue Yunkai , Duolikun Diliyaer , Chen wentao
Published: April 2022

Concerning a 750kV power plant circuit breaker refused to move accident, combined with the action process of accident circuit breaker and the waveform of fault current, analyze the cause of the breakout of the circuit breaker. This paper described the process of the accident from four stages and analyzed the fault waveform in detail. The result shows that the circuit breaker in the DC converter station recloses when the current of circuit breaker in power plant reaches the maximum reverse. The recloses of the circuit breaker in the converter station causing the power plant of the circuit breaker to produce a larger DC component and the DC component caused the short-circuit current-zero offset of the circuit breaker in power plant and the breaker on the power plant side failed to open due to no zero crossing. The simulation result shows that the circuit breaker of power plant does not appear DC component while the reclosing time of the circuit breaker in the DC converter station ahead of 5ms. It verifies that the analysis results are correct.
Grounding fault test technology of distribution network based on zero sequence power direction judgment
Authors: Guo Linyun , Wu Qiong , Yuan Zehong , Tao Zhaoyu
Published: April 2022

Distribution network grounding fault testing technology relies on a single criterion, which has a positioning blind area, resulting in large ranging error. In this paper, a grounding fault test technology for distribution network based on zero sequence power direction determination is proposed. The direction from the power supply side to the load terminal is specified as the positive direction of the network, the fault equivalent zero sequence current is modeled, and the high-frequency component of transient zero sequence current containing main fault characteristics is extracted. The fault line is determined based on the zero sequence power direction. For the fault line, the zero sequence power is less than zero, and the absolute value is much greater than the normal line, and the line selection device can select the line normally. The grounding fault test model of distribution network is established, and the fault current difference of each measuring point is calculated. When the difference is the smallest, it is identified as the fault location. The average ranging error of the test technology based on zero sequence power direction determination is 50.68m, which is 20.24m and 23.55m lower than that based on wavelet analysis and EMD. Therefore, it can accurately determine the fault line and has strong positioning advantages.
Research on Fault Location of SF6 Circuit Breaker Relay Coil Based on Traveling-Wave Reflection Method
Authors: Qian Shuaiwei , Wang Lu , Chen Jianxi , Peng Yanjun , Pan Ningbo , Huang Yongqiang , Zhou Xiong
Published: April 2022

—The traveling wave-reflection method is proposed to locate the short circuit fault of the opening/closing coil of the circuit breaker, the capacitance and inductance matrix of the opening/closing coil are calculated by finite element simulation, and the wave impedance model of the coil is established based on ATP-EMTP. A low-voltage square wave pulse signal is injected into the head end of the winding to detect the characteristic curve of the reflected wave when an inter-turn short-circuit fault occurs. The generalized fractal dimension of reflection wave characteristic curve was calculated and its variation as the position of short circuit change was analysed. Compared with box dimension, the variation of information dimension and correlation dimension are more obvious, thus information dimension and correlation dimension are selected as inpus, and the evaluation model of inter-turn short circuit position is established based on probabilistic neural network.
Research on inter-turn short circuit fault location of SF6 circuit breaker energy storage motor coil based on traveling wave reflection method
Authors: Qin Jian , Peng Yanjun , Wang Lu , Wang Jianxi , Pan Ningbo , Huang Yongqiang , Zhang Xiaohui
Published: April 2022

—The traveling wave reflection method is proposed to locate the inter-turn short circuit fault of the circuit breaker energy storage motor coil. The capacitance and inductance matrices of the energy storage motor coil are calculated by finite element simulation, and the wave impedance model of the coil is established based on ATP-EMTP. The low-voltage square wave pulse signal is injected at the winding head to detect the characteristic curve of reflected wave when inter-turn short circuit fault occurs. The variation law of generalized fractal dimension of reflection wave characteristic curve with short circuit position is analyzed. The short-circuit position is evaluated based on BP neural network, and the evaluation accuracy is 100 %, indicating that this method is feasible.
Fine-Grained Image Classification based on Self-attention Feature Fusion and Graph-Propagation
Authors: Pan Chen , Wu Wei
Published: April 2022

The goal of FGVC is to distinguish different subclasses under the same common class. Because data sets often have large intra-class differences and large inter-class similarity, FGVC is more challenging than traditional image classification. Previous work focused on mining salient regions in images and directly utilizing their features, but ignored that the features of regions are semantically related and the regional groups have stronger differences. In order to solve the above problem, we propose a FGVC method based on self-attention feature fusion and graph-propagation, consists of two branches, one of the branch based on the characteristics of map mining granularity characteristics of image, another branch study the inner semantic relevance between the regional characteristic vecto named CFSM, by iteration to enhance information elements and suppress useless element to improve the ability to recognize. A large number of experiments have proved the effectiveness of the proposed network, which has good accuracy and efficiency on the three benchmark data sets of Stanford Cars, FGVC-Aircraft and CUB200.
Research status of improvement based on DV-Hop non-range positioning algorithm
Authors: Yan Rongjie
Published: April 2022

In order to solve the problem of poor positioning of the DV-Hop algorithm, it is a current research hotspot. In view of the three aspects of error distribution, the research plan for effective improvement is listed. In the field of the minimum number of hops, the RSSI-based weighting correction and the use of deviation factor improvement; in the average distance of hops, the calculation of distance error improvement and the use of angle value weighting processing; in the calculation of unknown nodes, the weighting of the least square method and the triangle centroid method two. This correction is estimated. Relevant scholars of the above methods can solve the problem of poor positioning of the classic DV-Hop algorithm through simulation experiments.
Research on automatic test sequence generation method of computer interlocking test
Authors: Kuang Jiangyu , He Tao
Published: April 2022

Railway computer interlocking system is the core equipment of station signal control system, which directly affects the reliability and safety of the whole system. It is essential to test the interlocking software comprehensively and strictly [1]. The traditional interlocking test is conducted by testers to control the quality and efficiency of the test. According to the reference railway transportation “Interim Measures for railway signal interlocking test”, combined with the signal interlocking relationship test checklist, compared with the actual station yard of railway station, relying on manual preparation and manual implementation of test items, the test efficiency is relatively low. Therefore, the realization of automatic interlocking test has become a research hotspot at present. Interlocking function test belongs to the research field of black box test. On the premise of ensuring the comprehensiveness of test, generating efficient test sequence is the research focus of this subject.
Research on flame recognition technology based on local complex features
Authors: Zhu Di , Ahmad Kamarul Arifin , Chen Aolin
Published: April 2022

Traditional flame recognition methods based on image features are difficult to extract flame image features effectively, resulting in low flame recognition accuracy, while such methods mostly perform specific flame recognition for specific scenes, and when the scene, flame color and other features change, it is difficult to perform flame recognition effectively. To address this problem, this paper proposes a flame recognition scheme based on local complex features. Its main purpose is to fuse multi-scene flame data, introduce the characteristics of flame in color space through the process of extracting feature descriptors in SIFT, so as to filter the extracted feature descriptors with noise interferers, and transform the extracted feature descriptors into feature vectors by using the key point bag-of-words method, and finally a general fast flame recognition model based on the limit learning machine. In this paper, we explore the upper limit of the capability of traditional image feature representation to pave the way for the application of deep learning to the flame recognition problem.
Energy Consumption Optimization of Edge Computing Based on Reinforcement Learning
Authors: Jiang XiangYu
Published: April 2022

Cloud computing faces the problem of over-centralization, where the distance between users and cloud servers is very far. The communication between users and clouds faces long communication latency and high computational energy consumption. Edge computing is a hot research topic in academia now. Edge computing sinks cloud computing nodes to the edge, allowing users to offload tasks directly to edge servers. Compared with cloud computing, edge computing is closer to the user side. The communication between users and edge servers has lower transmission latency and less energy consumption. In order to better exploit the features and promote the development of edge computing, in this paper, we mainly focus on exploring the basic architecture of edge computing. In addition, we propose a scheme that can optimize the energy consumption of edge computing based on reinforcement learning methods. Finally, we verify the effectiveness of our proposed scheme by comparing it with other schemes through simulation experiments.
Research of Binocular Visual Inertial Algorithm Based on Point and Line Features
Authors: Zhou Yipeng , Li Maohai , Shao Guowei
Published: April 2022

To solve the problem of poor performance of the binocular visual inertial odometer VINS-Fusion in scenes with low texture and large luminosity changes, a binocular visual inertial odometer PLVINS-Fusion is designed that integrates line feature measurement information, which use line features to easy to extract in low-texture scenes, and have the advantage of more robust tracking performance in scenes with large luminosity changes. Point and line features are extracted in the front-end visual extraction at the same time, and line feature residuals are added to the back-end nonlinear optimization, construct a bag-of-words model combining point and line features in the loop detection module. On this basis, a real-time photometric calibration algorithm is adopted to jointly optimize the exposure time, the camera response function and the vignetting factor, and the stability of KLT optical flow tracking is improved by correcting the image brightness. Experiments on benchmark dataset show that the optimized algorithm has higher robustness and effectively improves the positioning accuracy, and meets the real-time performance requirement.
An RFID multi-Tag anti-collision algorithm based on Successive Interference Cancellation with power adaptive regulation
Authors: Gao Xingyue , Lou Huanli , Miao Qingyuan
Published: April 2022

Radio Frequency Identification (RFID) is a key technology supporting the Internet of Things (IoT). The simultaneous identification of multiple Tag signals by a Reader will generate the Tag collision problem, which will significantly reduce the identification efficiency of the system and prolong the identification time in the scenario of large-scale Tags. In order to solve this problem, this paper researches RFID Tag collision prevention algorithm, and establishes a multi-Tag collision prevention algorithm model by analyzing the Aloha Tag collision prevention algorithm, which can accurately portray the slot efficiency and time efficiency of the system when recognizing multiple Tags; then establishes a power adaptive regulation RFID multi-Tag identification algorithm using Successive Interference Cancellation (SIC) technology. After simulation and verification results show that the constrained Reader can resolve the signal to noise ratio threshold of 6.9db, the slot efficiency and time efficiency of the SIC-based RFID Tag anti-collision algorithm is improved by 179% and 154% compared to the ISOC algorithm; the designed RFID power adaptive regulation algorithm is improved by 259% and 203% compared to the ISOC algorithm in terms of slot efficiency and time efficiency 203%.
An abnormal user login behavior detection method of industrial control system based on multi-dimensional probability analysis
Authors: Zhang Wenzhe , Zeng Chuyang , Cao Yang , Qin Zuming , Chen Haiguang
Published: April 2022

Aiming at the poor detection performance of user abnormal login behavior in the complex environment of industrial control system, a new method based on multi-dimensional probability analysis is proposed. First of all, login time, source, destination and other login parameters are collected. Secondly, the abnormal probability of login parameters is calculated. Thirdly, the login transfer probability among multiple destination hosts is calculated. Finally, through the comprehensive analysis of the above three probabilities, an abnormal login behavior detection model based on multi-dimensional probability analysis is constructed. Experiments show that this method can effectively identify the abnormal login behavior of users caused by various types of network attacks.