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    Design of Multifunctional Array Signal Processing System Based on FPGA
    LUO Xin,FENG Wu,SUN Weijie,LIU Maliang
    Electronic Science and Technology    2023, 36 (3): 1-6.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.001
    Abstract826)   HTML466)    PDF(pc) (2270KB)(171)       Save

    In order to adapt to the characteristics of high real-time performance and large computation of the array signal processing system, this study proposes a multifunctional array signal processing system based on FPGA. By using advanced large-scale high-performance FPGA and multichannel high-precision ADC chips, the synchronous acquisition and digital down conversion processing of 40 intermediate frequency signals can be accomplished, and 36 sets of beam data can be obtained by digital beamforming. By configuring various types of external interfaces, the network data interaction, serial port control, beam control and MGT high-speed data transmission can be achieved. In this study, the hardware and software architecture of the system is presented, and the chip models, peripheral interface and the realization method of each software function module are introduced in detail. The measurement results indicate that the system meets the design requirements, has a strong array signal processing capabilities and good versatility and scalability.

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    An Accurate Design Approach for the Folded Cascode Operational Amplifier
    WANG Jiaqi,LÜ Gaochong,GUO Yushun
    Electronic Science and Technology    2023, 36 (3): 50-54.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.008
    Abstract676)   HTML11)    PDF(pc) (663KB)(144)       Save

    The results obtained from the traditional design procedure of the folded cascode amplifier are inaccurate. The optimization method can produce fairly accurate design results, but consumes large amount of computations. This study presents an accurate design method for this kind of amplifier. Through SPICE simulation, the errors caused by the analysis and approximation of various performance indicators in the traditional design process are compensated. At the same time, The device size calculation based on the BSIM model is adopted, and this design process is repeatedly executed, which gradually eliminates the errors existing in the traditional design process and obtains accurate design results. Compared with the traditional manual method, the proposed method is more accurate and avoids repeated debugging during design. When compared with the optimization method, although the proposed design still needs to go through an iterative process, the calculation amount is smaller due to the faster convergence. The circuit design under the actual process library of 0.18 μm and 90 nm is taken as an example, and the simulation experiments proves the correctness and effectiveness of the proposed method.

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    Text Keyword Extraction Method Based on BERT and LightGBM
    HE Chuanpeng,YIN Ling,HUANG Bo,WANG Mingsheng,GUO Ruyan,ZHANG Shuai,JU Jiaji
    Electronic Science and Technology    2023, 36 (3): 7-13.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.002
    Abstract547)   HTML15)    PDF(pc) (1624KB)(55)       Save

    Traditional text keyword extraction methods ignore the contextual semantic information and cannot solve the problem of ambiguity of a word, so the extraction effect is not ideal. Based on the LDA and BERT models, this study proposes the LDA-BERT-LightGBM (LB-LightGBM) model. The LDA topic model is selected to obtain the topic of each review and its word distribution, candidate keywords are filtered out according to the threshold, and the filtered words and the original review text are spliced and input into the BERT model. The word vector training is performed to obtain the word vector containing the text topic, so the text keyword extraction problem is converted into a two-classification problem through the LightGBM algorithm. The textrank algorithm, LDA algorithm, LightGBM algorithm and the proposed LB-LightGBM model are compared through experiments on the accuracy rate P, recall rate R and F1 of text keyword extraction in the present study. The results show that when TopN takes 3~6, the average value of F1 is 3.5% higher than that of the optimal method, indicating that the extraction effect of this method is generally better than that of the comparison method selected in the experiment, and the text keywords can be found more accurately.

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    Optimal Design of Permanent Magnet Synchronous Machine Based on Analytic Model
    ZHU Tuo,LI Zheng,ZHANG Kai,LI Zi
    Electronic Science and Technology    2023, 36 (3): 69-75.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.011
    Abstract510)   HTML44)    PDF(pc) (1917KB)(54)       Save

    Electromagnetic torque and eddy current loss are two important indexes of permanent magnet synchronous motor. Under the limited conditions of volume, effectively improving electromagnetic torque and reducing rotor eddy current loss are the key for motor design. In view of this problem, the analytical method is used to calculate the electromagnetic torque and eddy current loss respectively, and the PSO algorithm is used to optimize the size parameters of the motor. The analytical model includes armature reactive magnetic field and no-load magnetic field model. When calculating eddy current loss, eddy current reaction and circumferential segmentation of permanent magnet are considered. The objective function of the optimization algorithm uses weight values to convert multi-objective into single objective. The comparison between the analytical solution and the time-stepping finite element numerical solution shows that the error of the analytical solution is about 2%. The response surface of parameter influence analysis reveals that the correlation between electromagnetic torque and eddy current loss is consistent when the stator winding pitch is 25°. The optimization iteration results show that the optimized design reduces the average eddy current loss by 76%, the average electromagnetic torque by 22%, and the electromagnetic torque ripple by 68%.

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    Short-Term Photovoltaic Power Prediction Based on VMD and Improved TCN
    HUANG Yuan,WEI Yunbing,TONG Dongbing,WANG Weigao
    Electronic Science and Technology    2023, 36 (3): 42-49.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.007
    Abstract443)   HTML7)    PDF(pc) (1971KB)(33)       Save

    Photovoltaic power generation fluctuates, photovoltaic output is easily affected by various meteorological characteristics, and traditional TCN networks tend to over-enhance spatial characteristics and weaken individual characteristics. In view of these problem, a short-term photovoltaic power generation prediction model based on VMD and improved TCN is proposed in this study. The original photovoltaic power generation time series is decomposed into several modal components of different frequencies through VMD, and each modal component and the corresponding meteorological data are input to the improved TCN network for modeling and learning. The center frequency method is used to determine the optimal decomposition modal number of VMD. On the basis of the traditional TCN prediction model, DropBlock regularization is used to replace Dropout regularization to achieve the effect of suppressing information synergy in the convolutional layer, and the attention mechanism is introduced to autonomously mine and highlight the impact of key meteorological input characteristics and quantify the impact of various meteorological factors on photovoltaic power generation to improve forecasting precision. Based on the real data of a photovoltaic power station in Jiangsu, the simulation experiments show that the RMSE of the proposed prediction method is 0.62 MW and the MAPE is 2.03%.

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    Path Planning and Smoothing for Unmanned Surface Vehicle Based on Improved Ant Colony Optimization
    SUN Pengna,ZHANG Zhongmin
    Electronic Science and Technology    2023, 36 (3): 14-20.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.003
    Abstract398)   HTML12)    PDF(pc) (910KB)(45)       Save

    In view of the problems of USV path planning in complex environment, such as large steering angle, many turning points, and high energy consumption, a path planning and smoothing method based on improved ant colony optimization is proposed. The method adopts the grid method for environmental modeling, and improves the path optimization and static obstacle avoidance ability by introducing the path smoothness and distance heuristic factor into the heuristic function and introducing the obstacle heuristic factor into the path transition probability. Combined with heuristic factors, the pheromone update standard is improved, and the adaptability of the algorithm to increase the volatile factor of pheromone can be adjusted. And then the key nodes of the optimal path are extracted and smoothed to further guarantee path smoothness and security. According to the simulation results of obstacle avoidance under different grid map, compared with the traditional ACO, the path optimization speed of improved ACO is increased by 45%~62%, and the steering times of path is reduced by 25%~44 %. Moreover, the path security and feasibility after smoothing are improved. The above results show that the autonomous path planning of USV in different environments is realized.

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    Research on Control Strategy of Single-Phase Grid-Connected Inverter Based on dSPACE
    XIA Zihao,LI Yudong
    Electronic Science and Technology    2023, 36 (3): 62-68.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.010
    Abstract372)   HTML15)    PDF(pc) (1907KB)(35)       Save

    In view of the problem of high harmonic content of grid-connected current caused by voltage distortion, a control strategy combining quasi-proportional resonance control and voltage feed-forward is proposed in this study. Considering the infinite gain of the quasi-proportional resonance controller at the resonant frequency, the steady-state error of grid-connected current is reduced, and the voltage feed-forward is introduced to eliminate the influence of voltage on the system, so as to improve the quality of grid-connected current. The structure of single-phase grid-connected inverter is analyzed, the harmonic component of grid-connected current caused by voltage distortion is suppressed by closed-loop control, and the parameters of quasi-proportional resonance controller are set by control variable method, so as to analyze the influence of parameters of quasi-proportional resonance controller on system performance. Finally, the MATLAB/Simulink simulation model and the dSPACE-DS1104 hardware-in-the-loop simulation platform are established to verify the effectiveness of the proposed strategy under different strategies.

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    Research Progress of Node Assignment Optimization Strategy in Road Traffic Network
    LU Dongxiang
    Electronic Science and Technology    2023, 36 (3): 81-86.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.013
    Abstract335)   HTML14)    PDF(pc) (734KB)(42)       Save

    In order to further improve the traffic efficiency of urban road traffic network, a variety of intelligent optimization algorithms such as particle swarm optimization algorithm and neural network algorithm have attracted extensive attention. Recently, the popularization and application of deep learning technology has greatly improved the efficiency of node identification of urban traffic network, and the node scheduling of traffic network has expanded the application of deep learning technology. In this study, the key problems of traffic node scheduling are analyzed in detail, and the research status of relevant network node allocation is summarized. On this basis, the proposed study thoroughly discusses and analyzes the application prospect of node scheduling and deep learning in urban transportation network, and prospects the future research direction of node allocation optimization strategy in transportation network.

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    Design and FPGA Implementation of Large Scale Matrix Inversion Accelerator Based on LDL Algorithm
    YU Haoran,XIAO Hao
    Electronic Science and Technology    2023, 36 (7): 1-7.   DOI: 10.16180/j.cnki.issn1007-7820.2023.07.001
    Abstract331)   HTML492)    PDF(pc) (1252KB)(253)       Save

    Matrix inversion is a basic problem in engineering calculation. In large-scale MIMO systems, array signal processing, image signal processing and other applications, the processing speed of large-scale matrix inversion is very important to the system performance. However, the traditional matrix inversion method has high computational complexity, low parallelism and consumes a lot of storage space, which is not conducive to hardware acceleration. Aiming at the hardware acceleration problem of large-scale matrix inversion, this study studies the matrix inversion algorithm based on LDL decomposition and proposes a large-scale matrix inversion acceleration architecture based on this algorithm. Using the characteristic that the diagonal elements of triangular matrix after LDL decomposition are all 1, the matrix is designed by block iteration, which reduces the amount of calculation and improves the calculation speed. This study designs and implements the accelerator based on Xilinx Virtex7 FPGA. The experimental results show that under the 128 order matrix, the throughput is 105.2 Inv·s-1 and the maximum clock frequency is 200 MHz. Compared with the existing matrix inversion acceleration scheme, this design occupies less hardware resources and has higher performance.

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    Research Progress of Smart Grid Data Security Based on Internet of Things Technology
    YING Jieyao
    Electronic Science and Technology    2023, 36 (3): 76-80.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.012
    Abstract328)   HTML36)    PDF(pc) (639KB)(38)       Save

    In order to protect the core data in smart grid equipment and users' personal privacy, a number of Internet of things security technologies such as distributed computing and homomorphic encryption have gradually attracted attention. In recent years, the development of internet of things technology has promoted the rapid popularization of intelligent power grid, and the application of smart grid has promoted the renewal of internet of things technology. Through introducing various attack methods faced by smart grid, this study reviews and combs the research background and current situation of smart grid data security. On this basis, the definitions of false data injection attack and personal privacy protection are discussed and analyzed, and the future research direction and ideas of smart grid data security technology are prospected.

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    Small Signal Modeling of Flexible Interconnected Microgrid
    LU Hongwen,YUAN Xufeng,CHEN Ruijie,LI Yulong
    Electronic Science and Technology    2023, 36 (3): 21-28.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.004
    Abstract328)   HTML11)    PDF(pc) (3840KB)(43)       Save

    In view of the problem that the traditional PCC hard switch cannot actively adjust the power flow, the back-to-back converters are used to replace the traditional PCC hard switch to flexibly interconnect the distribution network and microgrid, so as to facilitate the coordinated control between them. In order to analyze the stability of the system and consider the different number of distributed generators in microgrid of different scales, a microgrid small signal state space model framework with N distributed generators connected through back-to-back converter is established. The eigenvalue analysis is carried out using MATLAB, and the key parameters affecting the stability and dynamic performance of microgrid are determined. Finally, a microgrid flexible grid connection operation model based on droop control is built on PSCAD / EMTDC platform. The established small signal model is combined with the built simulation model, and the simulation is carried out under multiple working conditions to verify the correctness of the modeling, analysis and conclusion.

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    Fault-Tolerant Clock Synchronization Algorithm Based on Grey Prediction
    LU Yu,ZHANG Li,ZHANG Fengdeng
    Electronic Science and Technology    2023, 36 (3): 29-35.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.005
    Abstract317)   HTML7)    PDF(pc) (842KB)(47)       Save

    In view of the problem of clock Byzantine failure and node communication link loss failure in the non-master clock synchronization in the distributed real-time system, a fault-tolerant clock synchronization algorithm based on gray prediction is proposed in this study. The proposed algorithm is based on the LL model of the broadcast communication network, and uses the gray prediction method of GM (1,1) to analyze the correction deviation value of the previous round, so as to predict the correction deviation value of the node in the failure order, and then obtain the correction value through calculation. The experimental results show that the gray prediction algorithm proposed in this study can tolerate Byzantine faults, and at the same time, it can overcome the problems caused by the failure of node communication link loss, and improve the universality of the FTA algorithm. The data comparison analysis results show that the clock synchronization precision of this algorithm is improved by 24.3% when compared with Original algorithm. At the same time, the algorithm complexity has certain advantages when compared with other algorithms.

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    Task Partitioning Optimization Algorithm Based on MrsP Protocol
    ZHANG Haitao,ZHANG Tong,ZHANG Yuhui,GUAN Yinfeng,ZHANG Fengdeng
    Electronic Science and Technology    2023, 36 (3): 36-41.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.006
    Abstract307)   HTML4)    PDF(pc) (785KB)(19)       Save

    Scheduling and resource sharing are the core problems in multiprocessor real-time systems, the corresponding scheduling algorithm and shared resource access protocol will directly affect the performance of the system, which requires the scheduling algorithm and resource access protocol to maximize the computing power of the hardware platform on the basis of ensuring real-time performance. However, most existing scheduling algorithms assume that tasks are independent of each other and do not consider resource sharing among tasks. Besides, shared resource access protocols also focus on rules and worst-case response time analysis. In this regard, the whole schedule ability condition of multiprocessor real-time system is obtained by combining P-RM algorithm and MrsP protocol. According to the characteristics of the MrsP protocol, this study proposes a task division algorithm to reduce the blocking time. By improving the calculation method of the task utilization, the proposed method solves the problem of repeated calculation in the critical area. Compared with the previous task partitioning algorithm, the proposed algorithm also solves the key area of double-counting and splits the redistribution after task classification problem. Experiments resalts show that the number of processors required by the algorithm is reduced by 15% to 20%.

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    An Acoustic Treatment Method for On-Line Fault Monitoring of Electromechanical Systems in Complex Noise Environment
    BAI Xingyu,GOU Yutao,JIANG Yu,LIU Mingyu
    Electronic Science and Technology    2023, 36 (3): 55-61.   DOI: 10.16180/j.cnki.issn1007-7820.2023.03.009
    Abstract303)   HTML6)    PDF(pc) (2517KB)(25)       Save

    In view of the problem of electromechanical system fault detection under complex background noise environment, this study proposes a noise suppression and fault monitoring method based on broadband acoustic processing. This method starts from acoustic signal pick-up and processing, and establishes the voiceprint database of the normal operating state of the system by collecting, tracking the data and suppressing the complex background noise of the acoustic signal under the normal operating state of the electromechanical equipment. In addition, the proposed method further realizes the detection and classification of fault signals through the voiceprint signal matching and pattern recognition technology based on broadband acoustic processing, and then realizes the online monitoring of the operating state of the electromechanical system and the autonomous early warning of invisible faults. This processing method organically combines the autocorrelation noise suppression technology based on data tracking and the fault signal detection and classification technology based on broadband acoustic processing, which can monitor the early hidden faults of the electromechanical system and effectively solve the fault detection problem of the electromechanical system in the complex noise environment. The simulation experiment finally proves the effectiveness and good practicability of the proposed method.

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    A Review of Research on EEG Signal Preprocessing Methods
    LUO Ruipeng,FENG Mingke,HUANG Xin,ZOU Renling,LI Dan
    Electronic Science and Technology    2023, 36 (4): 36-43.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.005
    Abstract269)   HTML12)    PDF(pc) (1019KB)(99)       Save

    EEG signal is a complex and important biological signal, which is widely used in the research of brain-like intelligence technology and brain-computer interface. In this study, the types and characteristics of common non-physiological artifacts and physiological artifacts that interfere with normal EEG signals are introduced, and the causes of physiological artifacts are analyzed in detail. Through the review of various EEG artifact removal methods and the analysis of the application status, the research progress of traditional artifact removal methods and new artifact removal methods is compared and summarized, and the advantages and disadvantages of artifact removal methods are further analyzed. Some methods have been successfully applied to the processing of electrocardiogram, ECG and EMG artifacts in EEG signals.The current demand for artifact removal from EEG signals and the problems faced are also given in the present study, and the future research directions are analyzed and prospected.

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    Summary of Research on Table Tennis Trajectory Prediction and Rotation Measurement
    LÜ Chengxu,FAN Suozhong,JI Yunfeng,YOU Yiping
    Electronic Science and Technology    2023, 36 (4): 90-102.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.013
    Abstract252)   HTML10)    PDF(pc) (1529KB)(70)       Save

    In the process of table tennis man-machine sparring, the ball will rotate when it collides with the racket/table, which will cause the sphere to deviate due to the influence of the Magnus force. Therefore, it is difficult to meet the requirements of accurate trajectory prediction of table tennis robot. Trajectory prediction and rotation measurement technology can help improve the robot's ability of prediction and striking. In order to help researchers in this field understand the research methods and existing technologies of table tennis trajectory prediction and rotation measurement, the new developments in the research of table tennis trajectory prediction and rotation measurement are reviewed. After reclassifying and sorting out the research results based on the research achievements in this field in recent years, the advantages and disadvantages of different methods are analyzed and the key issues are sorted out. Finally, the future research trend of table tennis trajectory prediction and rotation measurement is prospected.

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    Design of Low Sidelobe W-Band Sparse Array Consists of Horn-Like Antenna
    ZHOU Biao,ZHANG Shuai,ZHANG Dexun,LIN Zhicheng,WANG Jian
    Electronic Science and Technology    2023, 36 (9): 8-14.   DOI: 10.16180/j.cnki.issn1007-7820.2023.09.002
    Abstract183)   HTML11)    PDF(pc) (1500KB)(37)       Save

    In order to solve the design problem of wideband wide-angle low sidelobed phased array antenna caused by factors such as large loss, manufacturing process, T/R component size, number of channels and location, a wideband type horn antenna unit in the frequency range of 80~110 GHz is designed in this study, and the antenna standing wave ratio is less than 1.8. Considering the space limitation of T/R components, a 64-element high-gain, low-sidelobe, wide-band and wide-angle scanning array antenna is designed by optimizing the array position, and a small low-profile air waveguide feeding network is designed for the array. The simulation results show that the designed 64 element sparse array has the advantages of wide bandwidth, wide angle, low sidelobes, high gain, easy fabrication and realization, and the gain is higher than 22.6 dB, the sidelobes level is lower than -6.2 dB, and the active VSWR of each element is less than 2 under the scanning range of ±40°.

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    Short-Term Power Load Forecasting Based on FA-SVR-LSTM Combined Model
    WEN Yanfei,WANG Wanxiong
    Electronic Science and Technology    2023, 36 (9): 1-7.   DOI: 10.16180/j.cnki.issn1007-7820.2023.09.001
    Abstract165)   HTML51)    PDF(pc) (957KB)(50)       Save

    As the basis for maintaining the operation and analysis of the power grid system, short-term power load forecasting provides judgment basis and information for the economic dispatch and safety analysis of the power grid system, and plays an important role in maintaining the normal operation of the power grid system. In this study, the FA(Firefly Algorithm) is used to optimize the penalty factor c, nuclear parameter g of SVR(Support Vector Regression) model and the number of neurons m and learning rate lr of LSTM(Long Short-Term Memory) model. The FA-SVR-LSTM combined prediction model is established using the optimal parameters, and the sample data are predicted. Taking the historical data of power load of Florida as an example, four reference models of LSTM, SVR, FA-SVR and FA-LSTM are established to predict the power load of 360 h in 15 days, and the results are compared with those of FA-SVR-LSTM. The experimental results show that compared with LSTM and SVR model, the prediction accuracy of FA-SVR-LSTM model is improved by 33.184 9% and 30.326 5%, respectively. The evaluation values of MAPE and RMSE are significantly lower than those of the other four models. These results indicate that the prediction effect of FA-SVR-LSTM combined model is significantly improved when compared with other models.

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    Integrated Control Strategy of Wind Turbine Inertia Support and Primary Frequency Regulation
    ZHU Jiawen,CHEN Zhuo,LIU Renzhi,LIU Bolin,CHEN Xiangping
    Electronic Science and Technology    2023, 36 (5): 9-15.   DOI: 10.16180/j.cnki.issn1007-7820.2023.05.002
    Abstract159)   HTML6)    PDF(pc) (913KB)(33)       Save

    In response to the problem of reduced system inertia and insufficient frequency regulation capacity due to large-scale wind power connection to the grid, an integrated control strategy scheme for wind turbine inertia support and primary frequency regulation is proposed. In this scheme, the load reduction control of wind turbine is adjusted based on the characteristics of wind turbine slurry distance angle, and the reserve capacity required for wind turbine frequency modulation is reserved, which further solves the combination problem between the frequency change of the power grid and the virtual moment of inertia in the load reduction mode. In addition, the wind turbine speed protection is considered to set the static adjustment coefficient, and combined with the inertia support control, to achieve the wind turbine integrated frequency control strategy. The co-simulation model including wind farm is built in MATLAB/Simulink platform. The results show that the wind turbine can quickly provide virtual rotational inertia support to the grid, reduce the rate of change of the initial grid frequency perturbation, and regulate the output power according to the adjusted static regulation differential coefficients to improve the frequency stability of the wind power connected to the grid, which verifies the rationality of the proposed control strategy.

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    Design and FPGA Implementation of Dehazing Based on Channel Difference Model and Guided Filtering
    CAO Hongfang,WANG Xiaolei,DU Gaoming,LI Zhenmin,NI Wei
    Electronic Science and Technology    2023, 36 (8): 1-6.   DOI: 10.16180/j.cnki.issn1007-7820.2023.08.001
    Abstract155)   HTML1409)    PDF(pc) (2063KB)(176)       Save

    Computer vision systems are affected by foggy weather, resulting in poor quality images captured. To solve this problem, this study proposes a guided filtering dehazing algorithm based on channel difference model and its FPGA design. The channel difference model is obtained by separating the bright channel and dark channel of foggy image, and the model is used as a guide map for guided filtering to smooth the foggy image. Finally, a high boost filtering operation is performed to obtain a dehazed image. The hardware architecture is designed and implemented on FPGA. The experimental results show that the image scene after dehazing has uniform illumination, high degree of texture information recovery and high color fidelity. For an image of 480×270 size, the integrated frequency of the circuit is 108.448 MHz, the throughput is 323.47 MB·s-1, and the time to complete the entire dehazing is 0.001 2 s. These results indicate that the proposed algorithm and its hardware design can effectively improve image visibility and dehazing speed.

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    Application Research on Wireless Setting Technology of Electronic Fuze
    ZHANG Mingyue,FANG Liqing,GUO Deqing,SHI Yonglei,LIU Bingnan
    Electronic Science and Technology    2023, 36 (6): 57-63.   DOI: 10.16180/j.cnki.issn1007-7820.2023.06.009
    Abstract142)   HTML3)    PDF(pc) (1515KB)(10)       Save

    Modern war requires weapons to have a higher degree of environmental adaptability and more accurate guidance ability. As the core control component of guided weapons, the rapid response ability of electronic fuze and accurate control ability are not only closely related to the performance of weapons but also an important factor affecting the striking ability of weapons. Wireless setting technology is one of the core technologies of precision-guided weapons. Compared with the traditional wired setting technology, wireless setting technology has the characteristics of non-contact, fast setting speed, and strong adaptability. Quickly and stably transmitting the control information to the electronic fuse through wireless setting technology is one of the key technologies for the development of intelligent ammunition in the future. Principles of different wireless setting technologies, the causes of wireless setting technology are analyzed, and the necessity of wireless setting technology research is obtained. This study summarizes the key technologies and characteristics of three main wireless installation methods, electromagnetic induction installation, RF installation, and magnetic coupling resonance installation, and looks forward to the future development trend of wireless installation technology.

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    Abnormal Data Detection and SOC Estimation Algorithm for Lithium Battery Considering Measured Outliers
    WANG Changsong,CHEN Hui,WANG Licheng,QU Feng
    Electronic Science and Technology    2023, 36 (5): 34-40.   DOI: 10.16180/j.cnki.issn1007-7820.2023.05.006
    Abstract138)   HTML2)    PDF(pc) (1077KB)(22)       Save

    In view of the problem of outliers in sensor measurement in lithium battery, a chi-square detector and corresponding filtering algorithm are designed to eliminate the influence of outliers on lithium battery state of charge estimation in this study. The second-order RC equivalent circuit is selected to describe the battery dynamic model, and the parameters of the battery model are identified by Kalman filter in an off-line way. Considering the existence of outliers in sensor data, the chi-square detector is used to detect the outliers in real-time. When outliers are detected, an improved SOC estimation algorithm that only depends on the model is proposed according to the idea of zero-order preservation, which can resist the measured outliers well. Under FUDS condition, the experimental simulation shows that the designed outlier detector and the improved SOC estimation algorithm can accurately detect the occurrence of outliers, and the estimation error of SOC is guaranteed within 2%, reflecting good estimation performance.

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    Design of SoC Secure Memory Based on Lightweight Block Cipher
    LIU Wei,ZENG Xiangyi,XIAO Hao
    Electronic Science and Technology    2023, 36 (9): 15-20.   DOI: 10.16180/j.cnki.issn1007-7820.2023.09.003
    Abstract138)   HTML12)    PDF(pc) (976KB)(39)       Save

    In view of the security risks faced by RAM(Random Access Memory) and Flash memory of embedded on-chip systems, this study outlines physical attacks against memory of traditional SoC(System on Chip) chips, and presents a memory controller that supports encryption algorithms. Using the lightweight block cipher algorithm LBlock-s, the cryptographic security analysis shows that the algorithm has a good resistance to differential cryptanalysis. Compared with traditional block cipher algorithms such as AES(Advanced Encryption Standard), the proposed method reduces hardware resource consumption while guaranteeing security and is suitable for all kinds of resource-constrained secure SoC chips. To improve the data throughput, the hardware structure of the algorithm is expanded so that the standard 32 rounds of encryption or decryption take 1 clock cycle. This scheme guarantees that sensitive data cannot be parsed even if acquired by the attacker without consuming more hardware resources and encrypting delay, and effectively avoids physical attack on the security chip.

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    TDOA Sound Source Localization Method Based on Particle Swarm Optimization Algorithm
    ZHANG Dagui,ZHOU Zhifeng,ZHANG Yi,WANG Liduan
    Electronic Science and Technology    2023, 36 (9): 21-28.   DOI: 10.16180/j.cnki.issn1007-7820.2023.09.004
    Abstract124)   HTML10)    PDF(pc) (1009KB)(33)       Save

    In order to solve the problem of 3D coordinate estimation of sound source based on planar microphone array, this study introduces particle swarm optimization algorithm in TDOA(Time Difference of Arrival) sound source localization algorithm. The true value of the delay difference is calculated using the generalized cross-correlation method of the PHAT(Phase Transform) weighting function. Combined with the coordinate position of the microphone, the estimated value of the delay difference between the hypothetical sound source arriving at the microphone is calculated through the geometric relationship. The sum of the squares of the error between the actual value and the estimated value of the design delay is the particle fitness function. The particle swarm optimization algorithm is used to search for the sound source points in the space that conform to the fitness function, so as to realize the sound source position estimation. The simulation results show that the proposed algorithm has better robustness and noise resistance than the spherical interpolation method when the calculation speed is similar to that of the spherical interpolation method.

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    Chinese License Plate Detection and Recognition in Unconstrained Scenarios Based on YOLO
    CHEN Ziang,LIU Na,YUAN Ye,LI Qingdu,WAN Lihong
    Electronic Science and Technology    2023, 36 (10): 1-8.   DOI: 10.16180/j.cnki.issn1007-7820.2023.10.001
    Abstract124)   HTML18)    PDF(pc) (2014KB)(90)       Save

    In view of the problems of traditional Chinese license plate recognition methods, such as the requirement of scenes, poor real-time performance, and inability to deploy on edge devices, this study proposes a Chinese license plate detection and recognition method based on YOLO(You Only Look Once) in unconstrained scenes. This method is divided into two modules: license plate detection and license plate character recognition. In the license plate detection part, the improved YOLOv5 model is used to predict four groups of key points for license plate correction based on the prediction of target candidate regions, and the pre-training model trained on the COCO data set is used for training, which reduces the error detection problem caused by the complex environment and has high real-time performance. In the license plate character recognition part, the CRNN(Convolutional Recurrent Neural Network) model is improved, which greatly reduces the parameters and computation of the algorithm, so that it can be successfully deployed in various edge devices. Experimental results show that the proposed method can efficiently detect and recognize license plates in complex environments. The map value of the proposed license plate detection model is 3.0% higher than that of Retina-face in the license plate detection data set. Compared with LPR-Net, the accuracy of license plate character recognition model in license plate recognition data set is improved by 4.2%.

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    Importance Evaluation of Power Grid Nodes Based on Dynamic and Static Indexes
    SUN Xiuting,LI Yonggang,ZHANG Xing,XU Zhongyu,YU Yu
    Electronic Science and Technology    2023, 36 (4): 1-8.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.001
    Abstract115)   HTML61)    PDF(pc) (1044KB)(109)       Save

    With the continuous development of smart grid technology, the scientific and accurate evaluation of smart grid with high reliability is required. The failure of important nodes in the smart grid will lead to large-scale power outages, so the evaluation of the important nodes in the smart grid is an important manifestation of evaluating the reliability of the smart grid.In this study, different dynamic and static comprehensive indicators such as local environment, global attribute, network topology and load level of nodes are studied. These comprehensive indicator models are used to evaluate the importance of nodes in smart grid. Finally, the TOPSIS method is adopted to combine dynamic and static indicators to evaluate the importance of smart grid nodes, and the IEEE-30 nodes are simulated and verified. The results show that the importance of node 6 is relatively high, which should be protected.

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    Identification and Statistical Analysis of Coal Macerals Based on the Idea of Peak Splitting
    CHEN Chun,SHU Huisheng,KAN Xiu,SUN Weizhou
    Electronic Science and Technology    2023, 36 (4): 9-20.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.002
    Abstract104)   HTML4)    PDF(pc) (3097KB)(24)       Save

    In view of the low accuracy of the existing methods to identify coal macerals, a method for identifying and statistical analysis of coal macerals based on the idea of peak splitting is proposed in this study. The peak offset range of vitrinite of each coal type is determined from the point of view of individual particle, and an adaptive peak finding algorithm is proposed to select the effective peak point of coal and rock particles. In the coal macerals identification stage, the multi-strategy peak position identification algorithm is designed to classify the coal and rock particles into active-inert particles requiring peak clustering and pure vitrinite particles, inertinite particles and exinite particles without peak clustering, and the peak positions of coal and rock particles requiring peak clustering are selected. Then, Gaussian fitting is carried out based on peak splitting rules and statistical methods to determine the threshold values of exinite, vitrinite, and inertinite respectively, and complete the clustering and segmentation of coal and rock particles. The experimental results show that the proposed method can effectively identify single coal particles and realize quantitative statistics of maceral content, with an accuracy of 96.85% and the minimum entropy of 0.615 3. Compared with the traditional method, the proposed method has higher accuracy and has better practical application significance.

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    An Improved Average Current Control Method for Single-Phase Totem Pole Rectifier
    XIA Yuanshuai,XIE Ming,YANG Yang,YAO Lei
    Electronic Science and Technology    2023, 36 (5): 23-27.   DOI: 10.16180/j.cnki.issn1007-7820.2023.05.004
    Abstract99)   HTML3)    PDF(pc) (1173KB)(31)       Save

    In order to effectively suppress the harmonic pollution caused by power electronic equipment to the power grid and solve the problem of energy shortage, high-efficiency AC/DC PFC converter has attracted extensive attention. In order to solve the problems of conversion efficiency and current zero-crossing distortion of totem pole PFC converter, the diode in traditional topology is replaced by power switching tube, and an improved average current control strategy based on CCM mode is proposed. The control strategy improves the control mode of high-frequency bridge arm, reduces diode freewheeling loss and improves the conversion efficiency of the converter by introducing complementary PWM. The working principle and control strategy of totem pole topology circuit are described in detail, and the proposed strategy is simulated based on MATLAB/Simulink platform. On this basis, a prototype is designed and built. The experimental results show that the conversion efficiency of the proposed method is improved by 1.5%, and the current has no obvious zero-crossing peak, which proves the effectiveness and feasibility of the proposed improved control strategy.

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    Short-Term Wind Speed Prediction Based on EMD-GWO-SVR Combined Model
    LIN Lin,WANG Wanxiong
    Electronic Science and Technology    2023, 36 (5): 1-8.   DOI: 10.16180/j.cnki.issn1007-7820.2023.05.001
    Abstract99)   HTML75)    PDF(pc) (1228KB)(117)       Save

    Wind speed prediction is of great significance to wind power plant scheduling and control. In view of the randomness and intermittence of wind speed series, an EMD-GWO-SVR combined prediction model is proposed in this study. Empirical mode decomposition is performed on the original sequence, and grey wolf optimization algorithm is used to optimize the parameters of the support vector regression model. Then, the optimized parameters are substituted into the support vector regression model, and the decomposed eigenmode function and residual term are predicted, respectively. The predicted results are added together to predict the wind speed. Taking the historical meteorological data of Jiuquan in Gansu province as an example, six forecasting models including BP neural network, SVR, PSO-SVR, GWO-SVR, EMD-PSO-SVR and EMD-GWO-SVR, are established to forecast the wind speed. The simulation results show that the prediction accuracy of the proposed EMD-GWO-SVR model is 61.759 8% higher than that of SVR, and the evaluation values of MAE, MAPE and RMSE error indexes are significantly lower than those of the other five models.

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    Automatic Alignment System for Visible Light Communication Based on Image Processing
    YUAN Zhenbo,BAI Bo,ZHANG Xiaowei,LUO Liujun,SHANG Tao
    Electronic Science and Technology    2023, 36 (6): 8-15.   DOI: 10.16180/j.cnki.issn1007-7820.2023.06.002
    Abstract98)   HTML4)    PDF(pc) (1641KB)(17)       Save

    In order to improve the communication quality of visible light downlink, an automatic alignment system for visible light communication based on OpenMV is designed in this study. The system realizes automatic recognition of indoor white LED is based on image processing and color recognition. The system uses gray-scale centroid method to determine the centroid coordinates of white LED, and the PID algorithm is used to drive steering gears to achieve the tracking of the indoor white light LED. The experimental results show that the automatic alignment system of visible light communication can realize the automatic alignment of white LED under various motion trajectories at the receiving distance of 2 m, and the maximum alignment angle error is less than 0.534°. In addition, whether the white LED is blocked or there is an interfering light source, system can still maintain the good tracking effect, indicating that system has good robustness.

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    Three-Dimensional Laser SLAM Method with IMU
    ZHANG Ming,ZHANG Guobao,ZHU Hongwei
    Electronic Science and Technology    2023, 36 (6): 27-33.   DOI: 10.16180/j.cnki.issn1007-7820.2023.06.005
    Abstract94)   HTML2)    PDF(pc) (3210KB)(15)       Save

    In view of the problem of low positioning accuracy and poor robustness of the lidar SLAM(Simultaneous Localization and Mapping), this study proposes a SLAM method that combines IMU(Inertial Measurement Unit) data with the three-dimensional point cloud registration process. Based on the research of LeGO-LOAM(Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain), IMU data is introduced in the ground point extraction link, and the point cloud is mapped to the world coordinate system to reduce the influence of carrier jitter on the ground point extraction. The output information of IMU is used to eliminate the distortion of the point cloud due to the movement of the carrier and enhance the robustness of the algorithm. The three-point clustering method is used to perform cluster analysis on a frame of point cloud, which reduces the interference of noise, speeds up the point cloud registration process and improves the positioning accuracy of the algorithm. Meanwhile, closed-loop detection is introduced to reduce the cumulative error in the matching process and obtain the global optimal solution. The results show that in a large-scale outdoor interference environment, the improved SLAM algorithm reduces the trajectory fluctuations obtained by the solution, improves the point cloud registration accuracy, and enhances the robustness of the algorithm.

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    Dynamic Optimal Scheduling Strategy for Integrated Energy Systems Considering Shiftable Loads
    LIU Jinzhi,ZHANG Huilin,MA Lixin,WANG Hao,TANG Zheng
    Electronic Science and Technology    2023, 36 (4): 78-83.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.011
    Abstract94)   HTML3)    PDF(pc) (2427KB)(37)       Save

    The integrated energy system has attracted wide attention from all walks of life because of its multi-energy complementation, coordination and optimization and other characteristics. However, when the thermal power unit in the system is running, its peak shaving ability has certain limitations. In order to reduce the energy cost of the integrated energy system, increase the energy efficiency of the system and improve its peak shaving capacity, this study proposes a dynamic optimal dispatch strategy for the integrated energy system considering the shiftable load. With the aim of minimizing the overall operation and maintenance cost of the system, a simulation model is built by combining the translational load and related examples, and the adaptive chaotic particle swarm optimization algorithm is used to solve the problem. The results show that when the shiftable load is introduced, the multi-energy microgrid can better achieve the purpose of peak shaving and valley filling, and reduce the overall operating cost of the system, and achieve the effect of energy saving and emission reduction. At the same time, this study compares the traditional particle swarm algorithm with the adaptive chaotic particle swarm algorithm and verifies that the adaptive chaotic particle swarm algorithm is superior to the traditional particle swarm algorithm in terms of accuracy and efficiency.

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    A Novel PMSM Load Torque and Moment of Inertia Identification Strategy
    ZHU Lingtong,JIANG Quan
    Electronic Science and Technology    2023, 36 (6): 80-86.   DOI: 10.16180/j.cnki.issn1007-7820.2023.06.012
    Abstract89)   HTML2)    PDF(pc) (915KB)(28)       Save

    Accurate identification of load torque and moment of inertia is one of the keys to realize high-performance servo control of permanent magnet synchronous motor. Currently, the identification of load torque and moment of inertia is mostly limited to itself, which is not related to the interaction and restriction between load torque and moment of inertia. In view of this problem, firstly, an interconnected extended sliding mode observer is designed, which fully considers the interaction between load torque and moment of inertia, and the identified moment of inertia is applied to the proportional coefficient and integral coefficient of motor speed loop, so that the two extended sliding mode observers have more accurate and stable speed input. The comparison between the proposed strategy and other algorithms show that the new identification strategy makes the identification of load torque and moment of inertia have faster response ability and better identification accuracy. In addition, in order to verify the anti-interference ability and identification stability of the identification system, the identification is carried out based on the variable speed and load mutation environment. The simulation results show that the new strategy in this study still has a relatively stable identification effect even in the complex environment.

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    Super-Resolution Imaging of Laminate Debonding Defects via Deconvolutional Neural Network and Ultrasound Guided Waves
    YUE Shengyao,XU Baiqiang,XU Guidong,XU Chenguang,ZHANG Sai
    Electronic Science and Technology    2023, 36 (8): 7-13.   DOI: 10.16180/j.cnki.issn1007-7820.2023.08.002
    Abstract87)   HTML10)    PDF(pc) (1987KB)(30)       Save

    Traditional ultrasonic guided wave imaging detection methods are difficult to accurately characterize structural damage details. In order to obtain detailed features of the damage, the deconvolutional neural network model via deep learning is proposed to investigate the super-resolution imaging problem of subwavelength debonding defects in laminate plates. Initial imaging results are obtained by finite element simulation with the total focusing method. The labeled 12 550 damage images are trained and tested based on extended database expanded by data enhancement method. The results show that compared with the original full-focus imaging algorithm, the deconvolution neural network model improves the accuracy of damage location by 5%, the imaging accuracy is higher than 91%, and the positioning error is lower than 1.8 mm, indicating that the proposed method can significantly improve the resolution of network imaging results and better display the details of subwavelength damage. The above results show that the proposed method has high detection efficiency and does not require manual experience, and has good application value in engineering practice.

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    Optimization Method of Planar Microphone Array Configuration Based on Genetic Algorithm
    ZHANG Dagui,ZHOU Zhifeng,ZHANG Yi
    Electronic Science and Technology    2023, 36 (7): 24-31.   DOI: 10.16180/j.cnki.issn1007-7820.2023.07.004
    Abstract86)   HTML9)    PDF(pc) (1993KB)(34)       Save

    In the sound source localization system, the first problem to be solved is to use a smaller number of microphones and design an array configuration with better performance in a limited plane range. This sutdy proposes an array optimization method based on genetic algorithm to solve the problem. The design of the fitness objective function of the genetic algorithm comprehensively considers the array beam pattern, the width of the main lobe, the level of the side lobe and the number of microphones. By improving the genetic algorithm, the genetic algorithm can be realized in the application of microphone array optimization. The simulation results show that: compared with the traditional cross-shaped and rectangular planar regular arrays, the optimized array configuration can reduce the number of microphones used while ensuring the performance of the array. Compared with the particle swarm optimization algorithm, the array optimized by the improved genetic algorithm has better performance.

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    Fault Diagnosis of Few Shot Industrial Process Based on Transfer BN-CNN Framework
    OU Jingyi,TIAN Ying,XIANG Xin,SONG Qizhe
    Electronic Science and Technology    2023, 36 (7): 49-55.   DOI: 10.16180/j.cnki.issn1007-7820.2023.07.007
    Abstract86)   HTML5)    PDF(pc) (912KB)(34)       Save

    In view of the problem of weak diagnosis performance caused by insufficient training samples in industrial process fault diagnosis, a transfer BN-CNN framework is proposed based on transfer learning and deep learning in this study. In order to reduce the dependence of the network on the initialization method, a batch normalization layer is introduced into the convolution neural network to normalize the hidden layer of the model. To solve the problem of insufficient label data in the target domain, the sample-based transfer learning method is used to expand the labeled data volume of the target domain. By introducing the model based transfer learning method, the BN-CNN network is pre-trained with sufficient source domain data, and some parameters of the network are fine-tuned by using the expanded target domain. The difficulty of training the deep neural network with a small number of samples is reduced, and a fault diagnosis model suitable for target domain is obtained. The comparison experiments on TE industrial data set show that the proposed has good diagnostic performance for small samples of industrial process faults, and its average accuracy is 0.804.

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    Hybrid Recommendation Algorithm Fused with User Behavior Sequence Prediction
    SUN Hong,LU Meike
    Electronic Science and Technology    2023, 36 (4): 84-89.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.012
    Abstract85)   HTML4)    PDF(pc) (807KB)(24)       Save

    The capture of user interest hidden in the user behavior sequence is a hot research direction of recommendation algorithms in recent years. The traditional sequence prediction model uses the last product clicked by the user as the target, and establishes the association between user behavior and the target product, but does not fully dig out the sequence relationship between user sequences. This study improves on the traditional DIN model, uses continuous behavior over a period of time as the target vector, uses the transformer structure to complete the sequence-to-sequence prediction task, and further extracts and utilizes the user's deep interest in the user behavior sequence, and it is recommended in conjunction with DIN as an auxiliary feature. The experimental results on the Amazon book and the electronic data sets show that the DIN-based hybrid recommendation model proposed in this study increases the AUC index of the original DIN model by about 0.7% and 1.9%, respectively. It can be seen that the hybrid recommendation based on user behavior sequence prediction can play a certain auxiliary role in the multi-feature recommendation system. In addition, the influence of user sequence length on the model results is also explored.

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    Research on Radio Wave Propagation Prediction Model of Vehicle-Mounted Ultrashort Wave Radio
    LI Min,ZHANG Guangshuo,XU Zhijiang,XIE Hongxing,LU Hongmin
    Electronic Science and Technology    2023, 36 (7): 64-69.   DOI: 10.16180/j.cnki.issn1007-7820.2023.07.009
    Abstract83)   HTML6)    PDF(pc) (1434KB)(26)       Save

    Given the problem that the communication distance and quality of the vehicle-mounted ultrashort wave radio are affected by ground attachments and topography in the actual combat environment, a radio wave propagation prediction model of vehicle-mounted ultrashort wave radio is established based on ray tracing and machine learning. The integrated modeling of armored combat vehicle and vehicle antenna is established to obtain the antenna radiation pattern, and combined with electronic images, the radio wave propagation simulation model based on ray tracing technology is established. Based on the machine learning algorithm of the random forest and data results for the simulation model, the radio wave propagation prediction model based on the random forest was established. Compared with traditional classical radio wave propagation models such as the Egli and Okumura-Hata models, the radio wave propagation prediction model based on the random forest has higher accuracy. The root mean square error reaches 2.190 1 dB, and the coefficient of determination reaches 0.960 1. It can accurately predict radio wave propagation in the tactical communication environment.

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    Cooperative Localization of IMMKF and Chan-Taylor Algorithm
    WANG Xinyue,YU Huimin,HU Luning
    Electronic Science and Technology    2023, 36 (12): 1-8.   DOI: 10.16180/j.cnki.issn1007-7820.2023.12.001
    Abstract83)   HTML15)    PDF(pc) (1037KB)(51)       Save

    TDOA(Time Difference of Arrival) rangmg method is a typical opproach for UWB(Ultra Wide Band) indoor location.A Chan-Taylor-IMMKF(Interacting Multiple Model Kalman Filter) localization technique is suggested in this study to address the unavoidable random error and inaccurate location of targets with changing motion states. With the addition of the adaptive algorithm IMM, the algorithm is made up of the Chan-Taylor weighting algorithm and the Kalman filter algorithm. The Chan-Taylor weighting procedure is used to acquire the target estimated coordinates for the first time. The coordinate value is then used as the measurement value for the Kalman filter of the adaptive algorithm IMM, and the target coordinates are filtered many times. The target's final estimated coordinates are provided by the final weighting. The experimental results reveal that the filtered Chan-Taylor weighting algorithm outperforms both conventional Kalman filtering and the unfiltered Chan-Taylor weighting algorithm. The algorithm successfully lowers the system's random error and fixes the issue that the conventional Kalman filter cannot track the significant error when the target abruptly changes its motion state,and the mean error standard deviation is controlled within 15 cm.

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    Research on Transformer Fault Diagnosis Based on Improved Sparrow Search Algorithm Optimization BN
    TONG Zhaojing,QIAO Zhengrui,LI Jinxiang,LAN Mengyue,JING Lifei
    Electronic Science and Technology    2023, 36 (4): 52-58.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.007
    Abstract82)   HTML2)    PDF(pc) (1684KB)(23)       Save

    In view of at the problems of low accuracy and poor stability of transformer fault diagnosis, a transformer fault diagnosis method based on improved sparrow search algorithm and optimized Bayesian network is proposed. By calculating mutual information, the maximum support tree is established and directional processing is carried out to obtain the initial structure of Bayesian network, that is, the initial population, a new cooperation mechanism and sine cosine algorithm are introduced into the algorithm to improve the convergence speed and global search ability of the algorithm. Based on the analysis of dissolved gas in oil, a transformer fault diagnosis model based on improved sparrow search algorithm and optimized Bayesian network is established. In order to prove the superiority of the proposed method, the proposed method is compared with the existing transformer fault diagnosis methods. The results show that the proposed method has the highest fault diagnosis rate and can diagnose the transformer fault more accurately.

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    Identification of Foreign Objects on Transmission Lines Using Lightweight Network Algorithm
    TANG Zheng,ZHANG Huilin,MA Lixin,LIU Jinzhi,WANG Hao
    Electronic Science and Technology    2023, 36 (4): 71-77.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.010
    Abstract81)   HTML7)    PDF(pc) (2567KB)(24)       Save

    In view of the power inspection problem caused by various foreign objects on the transmission line, the deep learning image recognition method can be used for detection. This study proposes an improved lightweight network detection algorithm model. By replacing the backbone feature extraction network of YOLOv4 with lightweight neural network GhostNet, the redundancy of feature map generated by image input calculation is reduced. The PANet module of YOLOv4 is modified, and the depth separable convolution module is used to replace the common convolution module, which can reduce the amount of parameter calculation. The results show that, compared with the original YOLOv4 detection algorithm, when the IOU threshold is 0.5, the average accuracy of the improved algorithm decreases by 2.1%, but the detection speed is 2.21 times that of the original algorithm, and the parameter calculation amount is only 17.84% of the original algorithm. The comparison with other algorithms shows that the parameter performance of the proposed algorithm meets the demand. Under the condition of maintaining high accuracy, the detection speed of the proposed algorithm is improved and the computation amount is reduced, which proves the effectiveness and feasibility of the proposed algorithm in target detection.

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    A Firmware Security Update Scheme for Embedded Devices
    ZENG Xiangyi,LIU Wei,XIAO Hao
    Electronic Science and Technology    2023, 36 (8): 14-18.   DOI: 10.16180/j.cnki.issn1007-7820.2023.08.003
    Abstract81)   HTML10)    PDF(pc) (1427KB)(28)       Save

    In view of the security problem of embedded device firmware update, this study proposes a multi-check firmware security update scheme based on hash, symmetric and asymmetric encryption algorithms. In this study, the master key pairs, temporary key pairs, shared key and hash chain are designed to protect firmware update from identity authentication, data encryption, integrity check and other aspects, which can effectively prevent illegal users, firmware tampering, firmware data leakage, replay attack, firmware rollback and other attacks. In this study, the concrete implementation of the security update scheme is carried out. The experiment results show that compared with the ISP(In System Programming) and IAP(In Application Pragramming) technologies without any security protection, the scheme achieves the security protection of the whole process of firmware update at the time cost of about 7% and 11%, it provides a safe and reliable update method for embedded device firmware update.

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    Recognition Method of the Combined Trackside Signal Light Based on Image Processing
    GUO Qicheng,SHEN Tuo,ZHANG Xuanxiong
    Electronic Science and Technology    2023, 36 (7): 8-15.   DOI: 10.16180/j.cnki.issn1007-7820.2023.07.002
    Abstract80)   HTML7)    PDF(pc) (5287KB)(38)       Save

    The trackside signal light is an important guidance for a running train in a rail transportation system. However, the combined trackside signal light included two colors is also used as a specific sign in addition to the usual single color signal light. In order to solve the recognition problem of the combined trackside signal light, a method based on image processing technology is employed to recognize the combined trackside signal light located within 150 m in front of train. As a result, the candidate region characteristics of the combined trackside signal light are extracted by color segmentation, morphological processing, and Hough transform. On the other hand, the combined trackside signal light can be positioned on the right of running rail train. The central spacing between two single lights can determine whether or not existing combined trackside signal light to remove the possible interferences from other lights or environment. The experimental results indicate that this method can accurately locate and recognize the combined trackside signal light, and the color correction ratio is 94.14% for green and yellow light, 96.21% for two green lights, 86.67% for two yellow lights.

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    Underwater Occlusion Target Detection Algorithm Based on Attention Mechanism
    SHI Jianke,QIAO Meiying,LI Bingfeng,ZHAO Yan
    Electronic Science and Technology    2023, 36 (5): 62-70.   DOI: 10.16180/j.cnki.issn1007-7820.2023.05.010
    Abstract80)   HTML4)    PDF(pc) (4296KB)(22)       Save

    In view of the problems of foreground occlusion and background blur in underwater target detection task, an underwater target detection algorithm based on attention mechanism is proposed. Firstly, the image enhancement algorithms are used to improve the image quality. Then, based on the similarity function of the non-local neural network, the concatenation similarity function with logical reasoning capability is fused to enhance the expression ability of the network to the global context features. Additionally, the improved non-local neural network is combined with the triplet attention to make up for the channel features lost by the non-local neural network. Finally, the dilated convolution module is used to replace the pooling operation in triplet attention to reduce the loss of fine-grained information. Experiments show that the proposed algorithm increases the detection accuracy of baseline method from 65.66% to 68.55% on the data set provided by the 2020 National Underwater Target Detection Contest, which proves the effectiveness of the proposed algorithm.

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    Super-Resolution Image Reconstruction Algorithm Based on Multi-Feature Gated Feedback Residual Network
    SUN Hong,ZHANG Yuxiang
    Electronic Science and Technology    2023, 36 (4): 65-70.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.009
    Abstract79)   HTML2)    PDF(pc) (1227KB)(35)       Save

    In view of the problem of insufficient feature utilization of low-resolution image in super-resolution reconstruction, a multi-feature gated feedback residual network is proposed based on feedback mechanism and attention mechanism. The network has a simple structure and realizes the reuse of network parameters with a circular way, which can save compute resource effectively. The output features of network iteration are retained to achieve multi-feature fusion. In addition, a further feature refine block is used to extract the reconstructed high-resolution image features to obtain better reconstruction result. Experimental results on five test data sets show that when the scale factor is 4, the peak signal-to-noise ratio of the proposed network is 32.50 dB, 28.83 dB, 27.75 dB, 26.65 dB and 31.12 dB, respectively. Compared with the comparison networks, the test results of the proposed algorithm are significantly improved.

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    PI Approximate Engineering Design of DC-DC Conversion Compensation Network
    WU Fuzhuan,XIANG Naihuang,ZHOU Yuanhao,CHEN Mengna
    Electronic Science and Technology    2023, 36 (5): 16-22.   DOI: 10.16180/j.cnki.issn1007-7820.2023.05.003
    Abstract76)   HTML6)    PDF(pc) (805KB)(16)       Save

    In view of the blindness of the trial-and-error method in the design of DC-DC transform compensation network and the complexity of theoretical analysis, based on the state space average method, this study takes Buck as an example to model the DC-DC transformation system. Under the condition that the amplitude margin and phase margin are satisfied, the relationship between the compensation network kp, ki and the system parameter duty ratio D, inductance L and capacitance C is derived, and on this basis, an engineering approximation method is proposed. The proposed method is verified by PSIM simulation and a prototype platform based on DSP. The results show that the results obtained by this engineering approximation method are basically consistent with the theoretical analysis method, that is, the traditional control method, no matter in the case of voltage single closed loop or in the case of voltage outer loop and current inner loop. This engineering approximation method avoids the blindness of trial and error and the complexity of traditional control methods, which is the complexity of traditional control methods, and provides a quick method and idea for the rapid design of compensation networks in actual projects.

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    Research on Low Mach Number Transitional Cavity Jet Noise Reduction of High-Speed Train Pantograph
    TANG Zenan,MIAO Xiaodan,YANG Jian,YUAN Tianchen
    Electronic Science and Technology    2023, 36 (4): 29-35.   DOI: 10.16180/j.cnki.issn1007-7820.2023.04.004
    Abstract75)   HTML4)    PDF(pc) (3302KB)(19)       Save

    The pantograph and its cavity are the main sources of aerodynamic noise in high-speed trains, and it is particularly important to reduce this noise. There is less attention paid to the pantograph cavity compared to the pantograph in previous studies on aerodynamic noise of high-speed trains. In view of the problem of aerodynamic noise reduction of high-speed train pantograph and its cavity, numerical calculation methods are utilized to investigate the flow field characteristics and the law of noise propagation of the simplified high-speed train model under the condition of 350 km·h-1. The results show that the application of jet on the front edge of the pure cavity can significantly reduce the unsteady flow in the cavity and near the pantograph. When the jet velocity is 27 m·s-1, the maximum reduction in sound source pressure level of radiated noise on the back wall to the top and side of the cavity is 5 dB, and the noise at the monitoring point on the side of the pantograph is significantly reduced. The proposed study provides a direction for the research of transitional cavity jet noise reduction under low Mach number.

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    A Farmland Parcel Extraction Network Based on Multi-Scale Semantic Information Enhancement
    ZENG Xinxin,ZHANG Hongyan
    Electronic Science and Technology    2023, 36 (7): 70-74.   DOI: 10.16180/j.cnki.issn1007-7820.2023.07.010
    Abstract74)   HTML5)    PDF(pc) (2273KB)(31)       Save

    Facing the problems of adhesion of adjacent parcels and incomplete parcels due to the high heterogeneity and the small region among neighbor parcels, a farmland parcel extraction network based on multi-scale semantic information enhancement is proposed in this study. To alleviate the adhesion between parcels, the multi-scale feature extraction module with parallel structure is used, which retained the high-resolution feature maps to maintain high-precision edge information and reduce the loss of spatial location information due to downsampling. Furthermore, to reduce the phenomenon of incomplete parcels, the global semantic information enhancement module based on attentional mechanism is utilized to enhance the classification ability of the network by capture global semantic information instead of local semantic information. According to the experimental results, it is shown that the proposed method is 1%~13% better than the four typical algorithms in existing studies in terms of IoU, OA, and F1-score evaluation indexes.

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    UWB/PDR Pedestrian Localization System Based on Adaptive UKF
    LU Minlong,GUO Wei,ZHANG Xuanxiong
    Electronic Science and Technology    2023, 36 (6): 41-49.   DOI: 10.16180/j.cnki.issn1007-7820.2023.06.007
    Abstract73)   HTML3)    PDF(pc) (2447KB)(5)       Save

    Ultra-Wide Band(UWB) wireless communication technology has been widely used in the field of indoor navigation and positioning. However, the stability of pedestrian positioning systems based on UWB is not good in complex indoor environments, resulting in increased positioning errors. In order to solve this problem, this study proposes a Pedestrian Dead Reckoning(UWB/PDR) system based on adaptive Unscented Kalman Filter(UKF). The system uses the UKF algorithm to fuse the PDR model and the UWB positioning information to obtain the optimal position estimate. The probability density function of the step difference obtained by the UWB positioning and the PDR system is used to calculate the non-line of sight evaluation probability of the positioning point, and the evaluation result is applied to the adaptive noise adjustment of the system to improve the adaptability of the system for the environment. Experimental verification results show that the system can effectively reduce the positioning error in a complex environment, improve the accuracy and stability of the pedestrian positioning results, and its average positioning accuracy is less than 10 cm.

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    A Survey of Text-to-Image Synthesis Based on Generative Adversarial Network
    LI Yueyang,TONG Guoxiang,ZHAO Yingzhi,LUO Qi
    Electronic Science and Technology    2023, 36 (10): 39-55.   DOI: 10.16180/j.cnki.issn1007-7820.2023.10.006
    Abstract73)   HTML6)    PDF(pc) (5679KB)(40)       Save

    The text-to-image synthesis refers to translating the text description in sentence form into an image with similar semantics to the text. In the early research, the task of image generation is mainly based on keyword or sentence retrieval to align the visual content matched with the text. With the generative adversarial network, the method of text-to-image synthesis has made great progress in visual realism, diversity and semantic similarity. The generative adversarial network generates reasonable and real images through the confrontation between generator and discriminator, and shows strong ability in the fields of image restoration and super-resolution generation. Based on the review and summary of the latest research results in the field of text-to-image synthesis, a new classification method is proposed: Attention enhancement, multi-stage enhancement, scene layout enhancement and universality enhancement. The challenges and future development direction of text-to-image synthesis are also discussed in this study.

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