Table of Content

15 January 2023 Volume 36 Issue 1

  

Research on the Method for Density Reconstruction Based on Compressed Sensing in High-Energy Flash Radiography

LU Cunbo,SHENG Yunxiao

Electronic Science and Technology. 2023, 36(1):  1-6.  doi:10.16180/j.cnki.issn1007-7820.2023.01.001

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Density reconstruction of non-axisymmetric object from few projected data needs to be studied in high-energy flash radiography. The existing kinds of TV algorithms which exploits the idea of compressed sensing consider the local similarity of images, but they don’t consider the non-local similarity. In view of these problems, this study proposes a total variational reconstruction technique TV-GSR based on group sparse regularization. This technology integrates the group sparse model into the TV framework, and considers the local similarity and non-local self-similarity of the object image, making full use of the prior sparse information of the image. Besides, the proposed technology also uses the four-point symmetry of up, down, left and right of object to reduce the size of image reconstruction. Thus, the reconstruction accuracy increases and the reconstruction speed accelerates. Simulation experiments show that the proposed TV-GSR algorithm improves the reconstruction accuracy of images in noiseless and noisy scenarios, and has good effects on high-energy flash images and CT images with rich texture details, and is universal.

Study on Wire Arc Additive Manufacturing Forming Based on Image Processing and Numerical Simulation

LIU Meihong,HONG Enhang,LI Zhenhua,TENG Baoren

Electronic Science and Technology. 2023, 36(1):  7-14.  doi:10.16180/j.cnki.issn1007-7820.2023.01.002

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To solve the selection problem of welding mode (CMT or CMT + Pulse) and additive strategy (unidirectional or reciprocating path) provided by Fronius CMT TPS3200 welding power supply, under the same linear energy density, based on the high-quality forming of single-track single-layer welding bead with different modes, the variation law of layer width and layer height toward single-track multi-layers is studied, and single-track 10-layers bead forming is evaluated by combining image processing and numerical simulation. It is found that the weld bead forming of CMT+Pulse mode and CMT mode tend to reach stability from the fourth and third layer, respectively. In order to select optimal scanning strategy, the reciprocating path for bead forming is better than the unidirectional path based on the aspect of numerical simulation and evaluation of top weld bead forming. Under the reciprocating path, the weld bead forming of CMT mode is better than CMT+Pulse mode. The results show that the CMT mode preferred to achieve the heat dissipation stability condition, and combined with the optimal reciprocating path, it has advantages in welding bead forming, which lays the foundation for subsequent arc additive materials.

Fault Section Location of Distribution Network with DG Based on Improved Whale Algorithm

XU Lili,YANG Chao,ZENG Haoran

Electronic Science and Technology. 2023, 36(1):  15-20.  doi:10.16180/j.cnki.issn1007-7820.2023.01.003

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In view of the problems of slow convergence speed and low positioning accuracy of whale optimization algorithm, a fault section location method based on improved whale algorithm for distribution network with distributed generation is proposed in this study. A mathematical model suitable for fault location of multi-source distribution network is constructed. The adaptive inertia weight strategy is used to optimize the whale algorithm, and the improved whale algorithm is used to solve the location model. The simulation results of a 33-node distribution network with distributed power supply show that in the case of single and multiple faults in the distribution network, the improved whale algorithm can quickly and accurately locate the faulty section, and has good fault-tolerant performance. Compared with the traditional whale algorithm, the improved whale algorithm has faster convergence speed, higher positioning accuracy, which improves the reliability of positioning.

PI Formation Tracking Control for Distributed Heterogeneous Swarm Systems

TANG Kai,ZHANG Wei,WANG Weike,HU Zhi

Electronic Science and Technology. 2023, 36(1):  21-27.  doi:10.16180/j.cnki.issn1007-7820.2023.01.004

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The homogeneous swarm system is limited in function because of its single component. The individual composition of the heterogeneous cluster system is diverse, so the functions of the homogeneous cluster system can be extended. In view of the problem of formation tracking control in heterogeneous swarm system, based on leader-follower model, a distributed PI formation tracking control protocol is designed under the directed communication topology. The expected time-varying formation is designed, and the followers keep the expected formation while tracking the leader, so that all the agents in the system can reach the expected position. Considering that the real system is often affected by the external unknown disturbance and some uncertain factors, based on the Lyapunov stability theory, some sufficient conditions are given to ensure the tracking error of the system to be uniformly bounded, and the robustness analysis is carried out. The simulation verification is carried out according to the designed control protocol and control conditions. The results show that the designed PI formation tracking control strategy can effectively solve the formation tracking control problem of heterogeneous cluster systems.

Research Progress of Body Posture Estimation in Ball Games

ZHANG Manjie,YANG Fangyan,JI Yunfeng

Electronic Science and Technology. 2023, 36(1):  28-37.  doi:10.16180/j.cnki.issn1007-7820.2023.01.005

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Human pose estimation usually uses a single RGB image to locate the key points of human body to estimate the position of human body and joint points. Ball games are usually regarded as fast sports, and errors cannot be avoided in judging the technical legitimacy of players by subjective observation. Therefore,based on the estimation of human body posture, the athlete posture analysis technology is used to assist training and penalty. This method effectively avoids the traditional system positioning the athlete posture due to human subjective judgment error. At present, the research of human pose estimation can be divided into traditional algorithm and deep learning algorithm. Based on the deep learning algorithm, it can be divided into single person pose detection and multi person pose detection.Through the construction of neural network,human pose estimation based on deep learning algorithm uses machine learning method to extract image features and read image information,and perform performance comparison and analysis on mainstream data sets for human pose estimation. The application of human body posture estimation in ball games can provide scientific reference for athletes' daily training, and also ensure the fairness and justice of athletes in the game to the greatest extent.

The Recommendation Algorithm of Extreme Deep Factorization Machine Merged with Attention Network

WU Tong,YU Lianzhi

Electronic Science and Technology. 2023, 36(1):  38-43.  doi:10.16180/j.cnki.issn1007-7820.2023.01.006

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Recommender system can find information that satisfies the user's individual needs from huge amount of information. With the development of deep learning, deep learning has been widely applied in recommender systems. CTR prediction plays an important role in recommender system and has been widely used in many fields such as personalized recommendation, information retrieval, online advertising and so on. For the issue of large and sparse data in recommender system, this study merges xDeepFM model with attention network, and proposes a new CTR prediction model based on deep learning, which is called Atte-xDeepFM model. This model can solve the issue of feature scarcity, effectively learn the interactions relationship between features, and does not need to manually extract useful information in feature engineering. The comparative experiments on Avazu and Criteo data sets prove the effectiveness of the proposed model. Compared with the algorithm model commonly used in CTR prediction, the proposed model has better recommendation effect.

Realization of A Virtual Try-on System for 3D Glasses

WANG Xiaofeng,FU Dongxiang

Electronic Science and Technology. 2023, 36(1):  44-50.  doi:10.16180/j.cnki.issn1007-7820.2023.01.007

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In order to solve the problem that the mirror legs shade the face in the process of trying on 3D glasses on face image, this study proposes a virtual trying on system of 3D glasses based on face image. The three-dimensional model of the face shape is used to blank the mirror leg and solve the occlusion problem of the mirror leg. The key points of the input face image are detected, and the convex hull of the face shape is obtained by combining the Graham scanning method, and the three-dimensional model of the face shape is constructed by the translation scanning method. Additionally, according to the positioning of key points on the face image and the transformation of the 3D glasses model after pose estimation, the glasses model is worn on the face image. The experimental results show that the method achieves virtual try-on effect for multi-view face images, and solves the problem of occlusion of temples in the process of face images from multiple viewing angles. The average occlusion accuracy of the blanking leg during virtual trial is 94.5%, and the occlusion accuracy is high.

Research on Internet of Vehicles Navigation Technology Based on BDS and Edge Computing

ZHOU Qiping,HE Wei,JIA Lei,GUO Junkai,ZHAO Jianguo

Electronic Science and Technology. 2023, 36(1):  51-59.  doi:10.16180/j.cnki.issn1007-7820.2023.01.008

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With the continuous growth of vehicle ownership and the popularization of internet of vehicles applications, vehicle terminals generate large amounts of data messages that need to be processed in real time. In the scene of high-speed vehicle movement, the traditional internet of vehicles navigation system has a transmission delay due to vehicle differential positioning data, which results in a certain deviation in vehicle positioning results and cannot obtain high-precision positioning results in time. Based on this, this study proposes a technology solution for car networking navigation based on BDS positioning and edge computing. An improved genetic algorithm is used to allocate resources for terminal positioning requests, which effectively reduces the service delay of the entire edge network. The optimized unscented Kalman filter algorithm based on edge node is used to improve the positioning accuracy of the car network node. Experiments results show that the method proposed can provide real-time accurate, low-latency and high-precision positioning services for large-scale internet of vehicles terminals, and has high practical application value.

Harmonic Detection Technology Based on Improved Wavelet Threshold Denoising and CEEMDAN-HT Fusion

WANG Yumei,ZHENG Yi

Electronic Science and Technology. 2023, 36(1):  60-66.  doi:10.16180/j.cnki.issn1007-7820.2023.01.009

Abstract ( 170 )   HTML ( 74 )   PDF (1262KB) ( 22 )  

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In view of the low accuracy of CEEMDAN harmonic detection of adaptive noise caused by power grid environmental noise, a harmonic detection technology based on improved wavelet threshold denoising and CEEMDAN-HT fusion is proposed in this study. The threshold value is adaptively adjusted by the correction factor T_j, the soft and hard characteristics of the threshold function are adjusted by the adjustable parameter τ, and the improved wavelet threshold denoising method is applied to the preprocessing of harmonic signals. The preprocessed signal is decomposed by CEEMDAN, which can effectively suppress the mode aliasing binding. Relatedness criterion is used to remove false components, and the Hilbert transform is used to demodulate the components containing harmonic characteristics, and the amplitude-frequency information is accurately extracted. MATLAB simulation results show that the fusion algorithm of improved wavelet threshold denoising and CEEMDAN-HT controls the average error of steady-state harmonic detection below 1%, and the average error of transient harmonic detection below 2.1%, showing good anti-noise performance.

Research on Improved FTA Clock Synchronization Algorithm in RTEthernet

ZHANG Yuhui,ZHANG Fengdeng,ZHANG Haitao

Electronic Science and Technology. 2023, 36(1):  67-74.  doi:10.16180/j.cnki.issn1007-7820.2023.01.010

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In view of the problems that node clock drift, network link delay and poor synchronization ability in Ethernet, this study constructs a clock synchronization system model based on the communication principle of RTEthernet protocol. By studying the composition and working principle of RTEthernet, three factors affecting the time synchronization precision of real-time Ethernet-drift rate, network transmission delay and clock Byzantine fault are considered. Based on this, the original FTA clock synchronization algorithm is analyzed, and it is found that its fault tolerance performance is obviously reduced when Byzantine faults increase. The idea of " fault-tolerant midpoint " is introduced to improve it and RTE-FTM algorithm is proposed. Through the CANoe simulation platform, two Byzantine faults and no Byzantine faults in the system (seven nodes) are compared and analyzed, and the precision loss rate of the system is reduced by 3.1%, which verifies the convergence and effectiveness of the algorithm.

An Improved CNN Method for Bearing Acoustic Fault Diagnosis

HUANG Yajing,LIAO Aihua,YU Miao,LI Xiaolong,HU Dingyu

Electronic Science and Technology. 2023, 36(1):  75-80.  doi:10.16180/j.cnki.issn1007-7820.2023.01.011

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In view of the difficulty to collect bearing vibration signals in complex machinery and the poor accuracy of traditional fault diagnosis methods under cross working speed conditions, a rolling bearing acoustic fault diagnosis method is proposed based on TEO-CNN. Teager energy operator of raw acoustic signals is taken as the input of TEO-CNN model, the CNN is employed to extract the abstract features from inputs, and the global average pooling layer and the fully connected layer are combined to recognize the bearing health status. TEO-CNN is verified on bearing acoustic experimental data sets, and cross working speed conditions are simulated by constructing different bearing acoustic data sets. Experimental results show that compared with traditional convolutional neural networks and machine learning models, the proposed TEO-CNN shows obvious superiority, and the prediction accuracy is always higher than 95% under cross working speed conditions.

Improved Output Feedback Predictive Control for Perturbed LPV Systems

WANG Ping,ZHAO Min

Electronic Science and Technology. 2023, 36(1):  81-87.  doi:10.16180/j.cnki.issn1007-7820.2023.01.012

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An improved robust predictive control method is proposed for a class of multicellular descriptive LPV systems with bounded state disturbances, and an output feedback controller is designed to ensure the asymptotic stability of the systems. To offset the bounded state disturbance, the controller considered the undisturbed LPV system, and based on the off-line state observer, the linear matrix inequality is used to solve the minimum-maximum optimization problem in the infinite time domain of predictive control. Then the off-line state observer is adopted to obtain the difference between the estimated values of the disturbed LPV system and the undisturbed LPV system, and the feedback gain of the guaranteed performance is determined, so as to obtain the optimal offset that makes the disturbed LPV system asymptotically stable, which is combined with the undisturbed system control law as the optimal control law and applied to the actual system. The experimental results show that the improved robust predictive control method can obtain better control performance, and improve the stability of the system and the efficiency of solving optimization problems. The simulation experiments verifies the effectiveness of the proposed algorithm.

Parameter Optimization Design Method of Coupled Inductor Zeta Converter

XU Bangxian,LIU Xiaobo,HAN Xiangmin,QIU Zhi,TANG Hui,FAN Jinwei

Electronic Science and Technology. 2023, 36(1):  88-94.  doi:10.16180/j.cnki.issn1007-7820.2023.01.013

Abstract ( 249 )   HTML ( 74 )   PDF (914KB) ( 27 )  

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An improved robust predictive control method is proposed for a class of multicellular descriptive LPV systems with bounded state disturbances, and an output feedback controller is designed to ensure the asymptotic stability of the systems. To offset the bounded state disturbance, the controller considered the undisturbed LPV system, and based on the off-line state observer, the LMI is used to solve the minimum-maximum optimization problem in the infinite time domain of predictive control. Then the off-line state observer is used to obtain the difference between the estimated values of the disturbed LPV system and the undisturbed LPV system, and the feedback gain of the guaranteed performance is determined, so as to obtain the optimal offset that makes the disturbed LPV system asymptotically stable, which is combined with the undisturbed system control law as the optimal control law and applied to the actual system. The experimental results show that the improved robust predictive control method can obtain better control performance, and improve the stability of the system and the efficiency of solving optimization problems. Simulation experiments also verify the effectiveness of the proposed algorithm.