Table of Content

15 March 2024 Volume 37 Issue 3
    Research on Hybrid Critical-Level Task Scheduling and Semi-Partition Algorithm in Multi-Core Processor
    ZHU Jiawei, MAO Hang, ZHANG Fengdeng
    Electronic Science and Technology. 2024, 37(3):  1-9.  doi:10.16180/j.cnki.issn1007-7820.2024.03.001
    Abstract ( 162 )   HTML ( 26 )   PDF (1186KB) ( 136 )  
    Figures and Tables | References | Related Articles | Metrics

    At present, the schedulability analysis of mixed critical level tasks and semi-partition scheduling algorithms in most multiprocessors are focused on single-core utilization. However, due to the high complexity of task scheduling in multi-core systems, the existing research results have some problems, such as unbalanced load of each processor and unsatisfactory task schedulability. To solve this problem, the application scope of Dynamic Demand Boundary Function(DDBF) is extended to multi-core processor system in this study. DDBF is improved based on half-partition scheduling algorithm, and SDDBF(Super Dynamic Demand Boundary Function) is proposed by adding forward job and forward job analysis, which can calculate and utilize resources more accurately. Based on SDDBF, the schedulability analysis method of SDA(Stepper Dispatch Algorithm) and semi-partition algorithm MCWF(Mixed-Criticality Worist First) are proposed. The simulation results show that compared with AMC(Adaptive Mixed Criticality), AMC-MAX and XU algorithms, the schedulability analysis of SDA can be improved by 5%~10%. Compared with WF_MY(Worst First_My) and WF_NEW(Worst First_New) algorithms, MCWF makes the system have better CPU(Central Processing Unit) load balancing performance at any critical level.

    A Review of Research on Cybersecurity Risk Assessment Methods
    WU Jiacheng, YU Xiao
    Electronic Science and Technology. 2024, 37(3):  10-17.  doi:10.16180/j.cnki.issn1007-7820.2024.03.002
    Abstract ( 625 )   HTML ( 22 )   PDF (988KB) ( 118 )  
    Figures and Tables | References | Related Articles | Metrics

    Cybersecurity risk assessment is an important part of building a cyberspace security system, which can effectively protect individuals and organizations from the risk of cybersecurity attacks.This study briefly outlines the theory of cybersecurity risk assessment, emphatically introduces the current mainstream cybersecurity risk assessment methods, and classifies and compares the existing methods according to their different nature, analyzes the advantages, disadvantages and application scope of each method.On this basis, this study summarizes and extracts the factors that have an impact on the cybersecurity assessment results and proposes future research priorities in the field of cybersecurity assessment. The analysis results show that the three factors of correlation, uncertainty of assessment indexes and real-time of assessment process are the main factors affecting the effect of risk assessment, and it provides a reference for the research of risk assessment methods in the future.

    Research on Electromagnetic Transient Acceleration Simulation Technoloy of New-Type Power System
    NIE Chunfang, HAO Zhenghang, CHEN Zhuo, HE Puxiang
    Electronic Science and Technology. 2024, 37(3):  18-25.  doi:10.16180/j.cnki.issn1007-7820.2024.03.003
    Abstract ( 153 )   HTML ( 6 )   PDF (1938KB) ( 58 )  
    Figures and Tables | References | Related Articles | Metrics

    In order to solve the problems of low simulation efficiency and difficulty in simulation in the electromagnetic transient simulation of new power system due to complex system topology, numerous power electronic switching devices and insufficient single-core computing capability of simulator, this study uses the ideal transformer model segmentation algorithm to divide the large-scale new power system model into several subsystems. The decoupling and order reduction of the large system are realized and the computation of the whole system as one state-space system matrix is effectively reduced during simulation. In order to further reduce the computing burden of a single processor, an accelerated simulation platform UREP300 for efficient parallel computing in the bare-metal environment is designed by using multi-core CPU(Central Processing Unit) parallel technology. The segmented model is loaded into UREP300 for accelerated simulation experiment and compared with the offline simulation of the original model based on MATLAB/Simulink. The experimental results show that the acceleration simulation technology combining the ideal transformer model segmentation and multi-core parallel operation can not only guarantee the simulation accuracy but also improve the simulation speed to 586 times of the original, which can significantly improve the simulation efficiency, and is suitable for large-scale new power system simulation work.

    Research on An Improved Closed Loop Decoding Algorithm
    YAN Yaling, WANG Luoguo, YAN Rui, WU Ming
    Electronic Science and Technology. 2024, 37(3):  26-33.  doi:10.16180/j.cnki.issn1007-7820.2024.03.004
    Abstract ( 58 )   HTML ( 7 )   PDF (972KB) ( 58 )  
    Figures and Tables | References | Related Articles | Metrics

    In view of the problem that the measurement equation and transfer function of the traditional closed-loop decoding algorithm are easy to cause steady-state errors during acceleration,an improved closed-loop decoding algorithm is proposed in this study.Before the closed-loop solution, the least square method is used to fit the output signal parameters of the rotating transformer to obtain a more accurate signal of the rotating transformer. The calibration device is designed to avoid the influence of parameter fluctuation and nonlinear factors on the system performance and enhance the stability of the system.The steady-state error, angular position error and angular velocity error of the decoding algorithm are analyzed by simulation experiment. The results show that the improved closed-loop decoding algorithm is more stable and the steady-state error is smaller.Angular position error fluctuation from (-10, 0) to (-4.0,3.5), the angular velocity error fluctuation from (-0.50,-0.25) to (-0.15,0.10).

    Simplified Model Predictive Current Control for the Six-Phase Full-Bridge Inverter Fed PMSM Drive
    YUAN Qingqing, WU Ruiqi, MA Ting, XIE Xiaotong
    Electronic Science and Technology. 2024, 37(3):  34-43.  doi:10.16180/j.cnki.issn1007-7820.2024.03.005
    Abstract ( 82 )   HTML ( 6 )   PDF (4685KB) ( 52 )  
    Figures and Tables | References | Related Articles | Metrics

    Although the full bridge inverter motor drive or open winding structure has the advantages of interphase electrical isolation, good fault tolerance and low switching frequency of the device, there are many inverter output voltage vectors, serious redundancy and control constraints.In this study, a simplified model prediction current control algorithm based on two-stage vector optimization is proposed for a six-phase permanent magnet synchronous motor driven by a six-phase full-bridge inverter powered by a common DC bus, which can effectively track and control the stator fundamental current and suppress the harmonic and zero sequence components of the stator current.Based on the criteria of stator fundamental current control, harmonic and zero sequence current suppression, 729 voltage vectors output by inverter are optimized, and 12 candidate voltage vectors are obtained.Based on this, the model predictive current control algorithm is designed.The experimental results show that the simplified model predictive current control method in this study has good dynamic and static performance, and can effectively suppress harmonic and zero sequence current components while controlling fundamental wave current, which can provide theoretical support for the research of polyphase motor drive system.

    Finite-Time Consensus Control for Multi-Agent Systems under Channel Fading
    DING Meng, CHEN Bei
    Electronic Science and Technology. 2024, 37(3):  44-50.  doi:10.16180/j.cnki.issn1007-7820.2024.03.006
    Abstract ( 51 )   HTML ( 5 )   PDF (1040KB) ( 33 )  
    Figures and Tables | References | Related Articles | Metrics

    In view of the finite time consistency tracking problem for second-order multi-agent systems with channel fading, a distributed control algorithm based on sliding mode strategy is proposed in this study. According to the topology structure of the agent, a mathematical model is built to construct the consistency error function under the influence of random channel fading.The consistency protocol based on error function is designed to transform the consistency problem into the stability problem of tracking error system.In this study, an exponential non-singular terminal sliding mode surface is designed, and the finite-time stability and sliding mode accessibility of the error system are analyzed by combining Lyapunov stability theory and sliding mode control theory.A multi-agent model with one leader and four followers is used to conduct simulation experiments. The results show that four followers can accurately track the leader and achieve the tracking consistency of the system, and the error function curve tends to 0 at 10s, which proves the effectiveness of the control strategy.

    Research on Optimal Charging Strategy of Electric Vehicle Based on Multi-Objective Particle Swarm Optimization
    LI Tingting, LOU Ke, WANG Yuan, XU Huachao
    Electronic Science and Technology. 2024, 37(3):  51-56.  doi:10.16180/j.cnki.issn1007-7820.2024.03.007
    Abstract ( 143 )   HTML ( 4 )   PDF (1090KB) ( 70 )  
    Figures and Tables | References | Related Articles | Metrics

    Household electric vehicle charging in residential areas has a strong centrality. Large-scale electric vehicle charging load causes large peak-valley load difference and other problems in the distribution network system. This study proposes a user charging selection control strategy based on Multi-Objective Particle Swarm Optimization(MPSO) algorithm. Through the analysis and prediction of electric vehicle charging load, a multi-objective optimization model is established with the minimum variance of the total system load and scheduling cost as the objective function. Meanwhile, considering the constraints of electric vehicle battery and system power, the MPSO algorithm is used to solve the optimal initial charging time of electric vehicles. The simulation results show that compared with unordered charging of EVs in residential areas, the EV charging strategy proposed in this study can effectively reduce load peak and dispatch cost.

    Research on Power Emergency Drills in Power Distribution Rooms Based on Time-Sensitive Factors and Dynamic Bayesian Networks
    XU Hao, WEI Yunbing, LU Yongxin, LI Qin
    Electronic Science and Technology. 2024, 37(3):  57-67.  doi:10.16180/j.cnki.issn1007-7820.2024.03.008
    Abstract ( 41 )   HTML ( 2 )   PDF (5062KB) ( 34 )  
    Figures and Tables | References | Related Articles | Metrics

    In view of the situation that the emergency work of the distribution room is facing severe challenges due to frequent disasters,this paper conducts a study on the power disaster accident scenario inference technology of power distribution room.Based on the analysis of the suddenness and variability of the power distribution room disasters, the uncertainty and complexity of the evolution path, the "scenario-response" analysis method is used to analyze the components of the power distribution room accidents and their relationships, and the scenario rehearsal model of the power distribution room disasters is constructed based on the dynamic Bayesian network. The effect evaluation of drill is carried out based on the principle of timeliness. A 6 kV power distribution room fire accident in a mining company is conducted case analysis. The results show that the simulation results are consistent with the actual disaster development situation, which indicates the feasibility of the power distribution room disaster scenario model.

    Thermal Simulation of COB-LED Heat Sink Based on Two-Dimensional Heat Conduction Equation
    WANG Chaorui, YANG Ping, HAN Shuai, XU Xinying
    Electronic Science and Technology. 2024, 37(3):  68-74.  doi:10.16180/j.cnki.issn1007-7820.2024.03.009
    Abstract ( 34 )   HTML ( 1 )   PDF (3460KB) ( 30 )  
    Figures and Tables | References | Related Articles | Metrics

    For solving the problem about heat dissipation of COB-LED(Chip on Board-Light Emitting Diode), a mathematical model is established based on two-dimensional heat conduction equation which can quickly calculate heat distribution on the surface of COB-LED heat sink in this study. In order to facilitate the solution of the model, the finite difference method is used to solve the mathematical model and the alternate direction implicit scheme is chosen as its difference scheme.According to the boundary conditions and initial conditions in the model, the COB-LED normal temperature lighting experiment is designed, and the simulation analysis is carried out based on ANSYS finite element analysis software. The rationality of the mathematical model is verified by comparing the solution results, simulation results and experimental results. The results show that the relative error of the maximum temperature between the solution result and the experimental results is about 23.57%, and the temperature variation trend of the two is consistent. The maximum temperature relative error between the solution result and simulation results is about 34.84%, and the temperature distribution is close. The rationality and correctness of the mathematical model are proved.

    Research on Blind Roads and Obstacle Recognition Algorithm Based on Deep Learning
    MA Wenjie, ZHANG Xuanxiong
    Electronic Science and Technology. 2024, 37(3):  75-83.  doi:10.16180/j.cnki.issn1007-7820.2024.03.010
    Abstract ( 239 )   HTML ( 10 )   PDF (3884KB) ( 118 )  
    Figures and Tables | References | Related Articles | Metrics

    Blind roads and blind road obstacles are important factors that affect the travel safety of blind people. Existing algorithms only deal with blind road segmentation and blind road obstacle detection separately, with low efficiency and high computational complexity. To solve the above problems, this study proposes a multi-task recognition algorithm based on deep learning. The algorithm extracts public features through the backbone network, after the extracted features are fused through the SPP(Spatial Pyramid Pooling)and FPN(Feature Pyramid Networks)networks, they are respectively passed into the segmentation network and the detection network to complete the tasks of blind road segmentation and blind road obstacle detection. In order to make the blind road segmentation smoother, a correction loss function is introduced. In order to improve the recall rate of obstacle detection, the NMS(Non Maximum Suppression) of the detection network is replaced by Soft-NMS. The experimental results show that the algorithm segmentation part MIoU, MPA reach 93.52%, 95.29%, respectively, and the detection part mAP(mean Average Precision)、mAP@0.5 and mAP@0.75 respectively reach 75.58%、91.58%and 74.82%. Compared with using the SegFormer network for blind road segmentation and the RetinaNet network for blind road obstacle detection, this algorithm not only improves the accuracy, but also improves the speed by 73.72%, and the FPS(Frames Per Secon) reaches 18.52. Compared with other comparative algorithms, this algorithm also has a certain improvement in speed and accuracy.

    Quantum Scheduling Algorithm for Heterogeneous Signal Processing Platform
    SHEN Xiaolong, MA Jinquan, HU Zeming, LI Na, LI Yudong
    Electronic Science and Technology. 2024, 37(3):  84-90.  doi:10.16180/j.cnki.issn1007-7820.2024.03.011
    Abstract ( 34 )   HTML ( 0 )   PDF (1853KB) ( 20 )  
    Figures and Tables | References | Related Articles | Metrics

    In order to solve the problem that the scheduling length of existing scheduling algorithms in heterogeneous signal processing platforms is large, which leads to the decline of real-time performance of signal processing applications, a quantum scheduling algorithm for heterogeneous signal processing platforms is proposed. The algorithm adopts task priority diffluence sorting strategy to obtain more accurate task scheduling order.Quantum bits are used to encode the task allocation scheme, which increases the diversity of the task allocation scheme, and the coding rules help to find the global optimal solution out of the local optimal. According to the principle of minimum computing cost and the idea of task replication, the processor is allocated to reduce the communication cost between tasks, and the quantum coding scheme is updated through the quantum turnstile to constantly approximate the optimal solution. Simulation results show that the proposed algorithm can reduce the scheduling length, improve the real-time performance of signal processing applications, and improve the working efficiency of the platform.

    Energy Saving Scheduling Algorithm of Mixed-Criticality System Based on Probability Analysis
    MAO Hang, ZHANG Fengdeng, LU Yu, ZHU Jiawei
    Electronic Science and Technology. 2024, 37(3):  91-97.  doi:10.16180/j.cnki.issn1007-7820.2024.03.012
    Abstract ( 45 )   HTML ( 4 )   PDF (1082KB) ( 37 )  
    Figures and Tables | References | Related Articles | Metrics

    In view of the problem of energy saving of fixed priority tasks in mixed criticality system,a probabilistic analysis based energy-saving scheduling algorithm for mixed criticality system is proposed in this study.The real-time requirement of hybrid critical system makes the system modeling and analysis biased to the worse case.In this type of system, task overlimit is relatively rare, and resource overallocation is easy to occur.In this study, DVFS(Dynamic Voltage Frequency Scaling) technology and mixed criticality system scheduling algorithm are combined to mine idle time, so as to reduce the energy consumption of the system on the premise of ensuring the real-time performance of the system.The proposed algorithm is verified by MCSIMU(Mixed Criticality System Simulation) simulation software. The experimental results show that the energy saving rate of the fixed priority energy-saving scheduling algorithm can reach 45% compared with that of the unused energy-saving scheduling algorithm.

    Research on Optimization of Calculation Accuracy of Finite Element Technology in Mechanical Processing
    YANG Yunhui
    Electronic Science and Technology. 2024, 37(3):  98-102.  doi:10.16180/j.cnki.issn1007-7820.2024.03.013
    Abstract ( 43 )   HTML ( 3 )   PDF (630KB) ( 41 )  
    References | Related Articles | Metrics

    Finite element model technology is widely used in the field of machining, it is also the core theory technology to realize digital control and modern machining, and has been widely concerned and deeply discussed by researchers in various fields. The calculation and simulation technology based on the finite element model can greatly improve the precision of machining and manufacturing, and a large number of machined parts experiments also provide detailed data and reference for the finite element model.This study summarizes the research history of finite element analysis technology, analyzes and summarizes the core strategy of precision optimization in the current finite element analysis technology and its shortcomings, and looks forward to the future development direction of finite element analysis technology in the machining process.


Monthly,Founded in September 1987
Competent Authorities:
Ministry of Education of the People's Republic of China
Sponsored by:Xidian University
Chief Editor:Liao Guisheng
Executive Editor:Wan Liancheng
Editor:Hei Lei
Editor and Publisher:
The Editorial Department of Electronic Science and Technology
Distribution Abroad:
China Intermational Book Trading Corporation
P.O.BOx 399,Beijing 100044,China
P.O.Box 375,2 Taibai Road(South),Xi'an 710071,China
Unit Price:$20.00