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15 October 2022 Volume 35 Issue 10
  
    Analysis and Research of Electromagnetic Environment in Space Station Cabin Based on 5G Communication
    ZUO Wencheng,ZHAO Ziwen,XU Zhijiang,TAN Kangbo
    Electronic Science and Technology. 2022, 35(10):  1-7.  doi:10.16180/j.cnki.issn1007-7820.2022.10.001
    Abstract ( 49 )   HTML ( 5 )   PDF (3850KB) ( 25 )  
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    In view of the complex multipath effect of 5G communication in the space station cabin, this study proposes a method to analyze the electromagnetic environment and antenna coupling degree in the space station based on the equivalent space station model. By extracting the main characteristics of the space station, the cabin model is obtained. The typical 5G communication equipment is used as the transceiver system to detect the electromagnetic distribution in the cabin. The alternative scheme of reasonably arranging the communication equipment in the cabin is studied in different regions, and the coupling degree of the transceiver antenna in the working frequency band is studied. The results show that the communication transmitting equipment placed in the connecting area of three cabins has the best electromagnetic coverage in the space station, and the coupling degree can be obtained when the two antennas are placed vertically.

    Design of Heterogeneous and Low-Power Following Robot System
    WANG Qinghai,YANG Fangyan
    Electronic Science and Technology. 2022, 35(10):  8-14.  doi:10.16180/j.cnki.issn1007-7820.2022.10.002
    Abstract ( 46 )   HTML ( 5 )   PDF (3004KB) ( 12 )  
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    In the single-task mode, the service robot has a small application field and a low degree of intelligence. In the case of multitasking, the computing power cost of service robots is high, which leads to a significant increase in energy consumption and shortens the battery life.In view of the above problems, a low-power, multitask follow-up robot system based on the ROS platform is designed in this study,and the system can realize intelligent switching under two tasks of fixed-point cruise and visual follow-up.In terms of hardware, a low-energy heterogeneous computing platform is established to ensure that the same computing power is output while reducing energy consumption. In terms of software, according to the nature of the heterogeneous computing platform, the algorithm framework of the follow-up robot system is designed. The robot system uses the state transition control method based on Markov chain to realize the state switching of each module.The experimental results show that the proposed robot system can reduce energy consumption by 75%, and can realize the real-time switching between fixed-point cruise and target following in function.

    Research on Synchronous Rectification Technology of Multi-Output Flyback Switching Power Supply
    CHEN Zhuo,WANG Jingmei,LIU Yu
    Electronic Science and Technology. 2022, 35(10):  15-20.  doi:10.16180/j.cnki.issn1007-7820.2022.10.003
    Abstract ( 54 )   HTML ( 2 )   PDF (1989KB) ( 9 )  
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    In the flyback switching power supply, the traditional diode rectification method has large rectification loss, low efficiency, and poor cross-regulation characteristics of multiple outputs. To solve this problem, synchronous rectification technology is used to investigate the multi-output flyback switching power supply. The synchronous rectification technology of flyback converter and its driving method are analyzed, and chip UCC24610 based on the drain-source voltage is selected to design a three-output flyback switching power supply prototype. In order to adjust each output of the prototype, the method of weighted voltage feedback control is introduced in this study. The comparison between the proposed prototype and the diode rectifier prototype show that the full load efficiency of the former is 7.6% higher than that of the latter. Experimental results indicate that the synchronous rectification technology effectively improves the output voltage accuracy of the prototype and improves the multi-output cross-regulation characteristics.

    WiFi/PDR Fusion Real-Time Localization Algorithm Based on Region Constraint
    HU Wenqiang,HU Jianpeng
    Electronic Science and Technology. 2022, 35(10):  21-26.  doi:10.16180/j.cnki.issn1007-7820.2022.10.004
    Abstract ( 34 )   HTML ( 2 )   PDF (1245KB) ( 9 )  
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    In view of the problems of high algorithm complexity and large computation in the practical application of indoor positioning system, a WiFi/PDR integrated positioning system based on EKF is designed and implemented. In the WiFi fingerprint positioning part, a fingerprint matching method based on an adaptive sliding window is proposed. The search window is obtained by calculating the RSSI Euclidean distance in the neighboring state to dynamically adjust the matching range of the fingerprint library, thereby achieving rapid convergence of the positioning results. In the fusion localization stage, the system characteristics of EKF and PDR are combined to solve the time registration problem. Based on the WiFi data update, the EKF algorithm is used for data fusion, and the PDR directly outputs the positioning result when the fusion data is not synchronized. Experimental results show that the positioning system has good operating effects and stability. The average positioning error of the proposed method is 2.27 m in the actual positioning scene, and the positioning accuracy can reach 3 m in 80% of the cases.

    Software Design for Calibration of Gas Flow Standard Facility with Master Meter Method
    YU Zihan,JIAN Xianzhong
    Electronic Science and Technology. 2022, 35(10):  27-32.  doi:10.16180/j.cnki.issn1007-7820.2022.10.005
    Abstract ( 45 )   HTML ( 4 )   PDF (1542KB) ( 6 )  
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    This study introduces a calibration software system applied to the gas flow standard facility with master meter method. In view of the complicated design of programming software such as MFC and C#, this study uses configuration software with simpler programming as the development environment, and designs a set of calibration software to realize the functions of data collection, process visualization display, calibration data storage, calibration report generation and calibration historical data query during the gas flow calibration process of the standard meter method. The actual environment test shows that the software can be competent to monitor the flow calibration. The error of the calibrated value is within ±0.2%, and the repeatability is below 0.02%, which is consistent with the previous calibration certificate data and meets the 0.2-level accuracy turbine flowmeter national standard. After the uncertainty evaluation, the system uncertainty is below 0.4%, which meets the requirements of the standard facility.

    Design of WeChat Mini Program for Lost and Found Based on Image Recognition
    ZHANG Yangfan,HAO Yuxin,LI Yinfeng,TIAN Xinyu,ZHENG Chunhong,LI Zehao
    Electronic Science and Technology. 2022, 35(10):  33-38.  doi:10.16180/j.cnki.issn1007-7820.2022.10.006
    Abstract ( 64 )   HTML ( 3 )   PDF (2111KB) ( 8 )  
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    In view of the scattered distribution of lost and found information on campus, the difficulty of the owner’s inquiry, and the low success rate of item retrieval, this study uses image character recognition technology to develop a set of WeChat-based lost and found applets. This program can recognize the card number, name, and other text information in the lost property picture of the certificate, and fill in the form automatically. When the uploaded lost property information matches the school database personnel information, the system will notify the owner to claim the item via SMS and WeChat. The system has been put into operation on campus, which has improved the release efficiency of lost and found information and increased the success rate of lost property recovery.

    Automated Extraction Method for Liver Capsule Feature Maps
    NIU Guangli,LIU Xiang,SONG Jialin,TANG Xian
    Electronic Science and Technology. 2022, 35(10):  39-44.  doi:10.16180/j.cnki.issn1007-7820.2022.10.007
    Abstract ( 35 )   HTML ( 1 )   PDF (2260KB) ( 5 )  
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    In order to automatically extract the feature maps of the liver capsule and its upper and lower tissues, and realize automatic feature learning, the study proposes to use frequency domain processing and image morphology processing to preprocess the image, and proposes a two-way cross receptive field strategy based on the moving average method, and feature screening and analysis are carried out through the receptive field mapping area. The logarithmic energy function is used to identify and locate the target block, so as to realize the extraction and analysis of the liver parenchymal lesion features, liver capsule, muscle fat layer texture feature data, and obtain the liver capsule and its upper and lower tissue feature maps according to the data analysis. Based on the relative positions of the proposed feature regions, a block correction mechanism is proposed to correct the mischecked blocks to make them more robust. The experiments show that during the extraction of the liver envelope and its upper and lower tissue feature maps in the ultrasound images of cirrhosis, the present extraction mechanism achieves 100% accuracy in the normal, mild and moderate stages of feature extraction, and 84.6% accuracy is achieved in the severe disease stage.

    Garbage Detection and Classification Based on YOLO Neural Network
    ZHANG Wei,LIU Na,JIANG Yang,LI Qingdu
    Electronic Science and Technology. 2022, 35(10):  45-50.  doi:10.16180/j.cnki.issn1007-7820.2022.10.008
    Abstract ( 61 )   HTML ( 3 )   PDF (1231KB) ( 20 )  
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    In view of the problems of low efficiency of manual garbage sorting, heavy tasks and harsh environment, this study proposes a YOLO-based target detection method to realize garbage detection and classification. The model is adjusted through making a specific dataset, using K-means clustering algorithm and Mish activation function. According to the characteristics of the convolutional neural network, the CBAM attention module is embedded in front of each detection head of the YOLO model, combined with PANet to enhance the feature integration ability to improve the accuracy of small target detection. The experimental results show that the garbage detection and classification method proposed in this study can accurately and quickly identify garbage. Compared with YOLOv4, the map value of the proposed model on the garbage data set has increased by 2.81%. The recognition accuracy of Cans can reach 94.56%, and the accuracy of PlasticBottle has increased by 6.36%.

    Image-Splicing Forgery Detection Based on Noise Consistency Under Geometric Constraints
    LU Dongsheng,ZHANG Yujin,ZHU Hai,JIANG Yuewu
    Electronic Science and Technology. 2022, 35(10):  51-58.  doi:10.16180/j.cnki.issn1007-7820.2022.10.009
    Abstract ( 26 )   HTML ( 2 )   PDF (2619KB) ( 4 )  
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    When the noise level estimation method based on image block is applied to splicing image localization, it will cause the segmentation edge to be jagged and reduce the accuracy of edge positioning. In view of the problem, this study proposes an image splicing detection algorithm based on geometric constraints and noise consistency analysis. Statistical-based noise level estimation and K-means algorithm are used to achieve preliminary detection and positioning for each image block. The point set at the edge of the initial splicing area is extracted, and each point is used as the center to search for the square range on the edge map in turn to splice the edge of the area. Subsequently, the geometric constraint filtering algorithm is used to select the suspected tampering edge points to locate the tampering area. Compared with the existing algorithm, when the correct detection rate is the same on Columbia, the proposed method can reduce the error detection rate by 12.7% and reduce the complexity of the algorithm.

    Copy-Move Forgery Detection Algorithm Based on Non-Local Self-Correlation
    WU Xu,LIU Xiang
    Electronic Science and Technology. 2022, 35(10):  59-64.  doi:10.16180/j.cnki.issn1007-7820.2022.10.010
    Abstract ( 22 )   HTML ( 1 )   PDF (3103KB) ( 4 )  
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    On account of the problem that forgery target and source of digital image copy-move manipulation cannot be distinguished, this study improves the similarity matching algorithm and uses non-local self-attention mechanism to solve the classification problem of copy-move forgery source and target areas, under the premise that manipulated regions are detected. The overall framework is a dual-branch detection network. The main branch uses the classic U-net to segment the pixel of forgery regions, and the auxiliary branch uses the siamese network to extract features and calculate the autocorrelation to separate the forgery targets and source area pixels. Finally, three-categories results can be predicted by end-to-end training after fusing two branches. The experiment result shows that the pixel-level classification accuracy of the proposed algorithm when detecting the localized target area reaches 80.47%, and the F1 value and accuracy are better than the compared algorithm. The visualization results and robustness experiments also show that the proposed algorithm has excellent generalization performance.

    Pattern Recognition and Segmentation Method of Wellbore Trajectory Based on Characteristic Parameters
    LIU Weixing,YANG Jinxian
    Electronic Science and Technology. 2022, 35(10):  65-71.  doi:10.16180/j.cnki.issn1007-7820.2022.10.011
    Abstract ( 24 )   HTML ( 1 )   PDF (858KB) ( 6 )  
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    In view of the problem that the wellbore trajectory fitting deviates from the true drilling trajectory caused by the changeable wellbore trajectory shape and the single inclination mode, this study proposes a method of wellbore trajectory segmentation and pattern recognition based on characteristic parameters. On the basis of sufficient theory, the cubic b-spline function of well inclination and azimuth with well depth is established, and the curve characteristic parameters which can determine the adjacent shape of a certain point of the well trajectory are obtained. According to the characteristic parameters, and combined with the characteristic parameters of various models, the wellbore pattern recognition evaluation index and segmentation index are constructed, and the wellbore trajectory model that best matches the actual drilling is selected. In order to verify the effectiveness of this method, a prototype is designed to simulate the actual drilling experiment. The results show that the wellbore trajectory pattern recognition and segmenting method based on characteristic parameters can significantly improve the accuracy of wellbore trajectory fitting.

    Application of Improved Particle Swarm Optimization Algorithm in Multi-Energy Complementary Microgrid
    ZHAO Jian,YUAN Boxun,NI Lingfan,LIN Shunfu,WANG Wei
    Electronic Science and Technology. 2022, 35(10):  72-78.  doi:10.16180/j.cnki.issn1007-7820.2022.10.012
    Abstract ( 29 )   HTML ( 3 )   PDF (1860KB) ( 6 )  
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    The multi-energy complementary microgrid system has multi-dimensional variables and multiple constraints, which leads to the complex and high-cost calculation of the system comprehensive annual cost. In the calculation process, because the system needs power balance, it is easy to cause the problem that the output of various equipment exceeds the specified limit. In view of this problem, an improved particle swarm optimization algorithm is proposed. The algorithm comprehensively considers the power balance of electricity-heat-cooling multiple loads in the system, and introduces a secondary limit on the basis of the particle swarm algorithm. The algorithm pulls the equipment output beyond the power limit back to the constraint boundary, and dynamically optimizes the reduction coefficient of the equipment output to avoid the over-limit problem caused by the internal power balance of the system. Through the analysis of examples, the genetic algorithm, the algorithm before the improvement, and the algorithm after the improvement are applied to the multi-energy complementary microgrid system, and the equipment output and the comprehensive annualized cost in different scenarios are compared and analyzed. The experimental results prove the effectiveness and universal applicability of the proposed algorithm.

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