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15 June 2023 Volume 36 Issue 6
  
    Sliding Mode Control of Pipe Welding Robot Based on Extended State Observer
    LIU Wenjing,ZHANG Guobao,LIU Yuheng
    Electronic Science and Technology. 2023, 36(6):  1-7.  doi:10.16180/j.cnki.issn1007-7820.2023.06.001
    Abstract ( 100 )   HTML ( 8 )   PDF (888KB) ( 29 )  
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    In view of the nonlinear problem of backlash caused by the gear transmission structure in the automatic pipe pile welding machine, an improved sliding mode controller design method based on the extended state observer is proposed. Firstly, the nonlinear and time-varying backlash model is equivalent to a global linearization model, and it is proved that the upper limit of the modeling error is bounded. For the situation with nonlinear input backlash and unknown external disturbance, a sliding mode controller and an improved sliding mode controller based on extended state observer are designed, respectively. The former can track the input signal asymptotically and stably, and has strong anti-interference ability, but it has large chattering. The latter uses the extended state observer to detect the unknown disturbance and directly compensates to the controller, which not only ensures the tracking error within the expected accuracy range, but also reduces chattering. The simulation results show that compared with the traditional sliding mode controller, the improved sliding mode controller system based on the extended state observer reaches the sliding mode surface faster and chatters less.

    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
    Abstract ( 151 )   HTML ( 4 )   PDF (1641KB) ( 27 )  
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    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.

    Design of A High Frequency Vehicle Small Loop Antenna with Auto-Tuning Characteristic
    ZHAN Fei,YAN Yongmou
    Electronic Science and Technology. 2023, 36(6):  16-20.  doi:10.16180/j.cnki.issn1007-7820.2023.06.003
    Abstract ( 94 )   HTML ( 8 )   PDF (1531KB) ( 23 )  
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    For the problem that the shortwave communication antenna is hard to realize broadband operation and inconvenient to transport on a set of equipment, an auto-tuning small loop antenna suitable for high frequency communication of near vertical incident skywave technique is proposed. The antenna is installed on the top of the vehicle, and the main body is composed of coupling loop, radiation loop and auto-tuning unit. Two different tuning methods are skillfully introduced, and the two matching networks are integrated and automatically controlled. The antenna has the advantages of simple physical structure, convenient carrying and high radiation efficiency. The simulation and test results show that the standing wave ratio of the loop antenna is less than 2 in the whole high frequency band from 3 to 30 MHz, the maximum gain of the loop antenna at 25 MHz can reach 2.7 dBi, and the maximum radial direction is in the vertical, which meets the requirements of shortwave near vertical incidence skywave communication, and becomes an important part of the high frequency communication system.

    Impedance Control Method for Underwater Gripper Compliant Grasping
    LU Liang,LIANG Chengyuan,WANG Hao,YANG Xin
    Electronic Science and Technology. 2023, 36(6):  21-26.  doi:10.16180/j.cnki.issn1007-7820.2023.06.004
    Abstract ( 58 )   HTML ( 3 )   PDF (1291KB) ( 17 )  
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    In view of the underwater manipulator system with more uncertainty and random interference, the effect of the underwater environment on the dynamic model and impedance controller is analyzed, and an impedance controller based on environmental parameter identification is constructed to solve the force tracking problem of underwater compliant grasping. The environmental stiffness is identified online by recursive least squares with the introduction of a forgetting factor, so as to correct the reference position. The steady-state error of the contact force is reduced, and real-time and accurate force tracking is achieved. Simulation with the MATLAB/Simulink are carried out. It is shown that the controller can quickly achieve tracking of the desired force and real-time estimation of contact stiffness under the introduction of continuous external interference force and desired force adjustment, and has good robustness. Finally, experiments prove that the controller has fast and stable force tracking performance in real underwater compliant grasping tasks. Furthermore, the average steady-state force tracking deviation is about 0.014 N, and the maximum force tracking deviation is about 0.138 N.

    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
    Abstract ( 175 )   HTML ( 7 )   PDF (3210KB) ( 37 )  
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    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.

    A Research on the Spacing Measurement Between Two Trains Located at A Curved Track by Machine Vision Technology
    WANG Huimin,BI Jiazhen,SHEN Tuo,ZHANG Xuanxiong
    Electronic Science and Technology. 2023, 36(6):  34-40.  doi:10.16180/j.cnki.issn1007-7820.2023.06.006
    Abstract ( 121 )   HTML ( 4 )   PDF (2189KB) ( 17 )  
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    Real-time detection of the distance between trains is an important way to ensure the safety of rail transit and improve train capacity. In particular, the distance measurement between trains on curved rails is difficult to distance measurement. In order to calculate and optimize the real-time distance measurement formula of the train at the curve, a method of distance measurement of the train at the curve based on machine vision is proposed. In this method, monocular camera is used for track image acquisition, OpenCV algorithm is used to process and analyze the acquired images, and neural network method is used to fit the track line of curved rail, realizing the dynamic extraction of track feature points. The distance formula between trains can be calculated and optimized by building a mathematical model. The experimental results show that the overall error rate of the testing system is less than 9.11% when the duration interval is 40~50 ms. The method for the spacing measurement can be integrated together with other information in the collected images for the information fusion and referred as an important condition in the rail system for a train running.

    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
    Abstract ( 120 )   HTML ( 4 )   PDF (2447KB) ( 15 )  
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    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.

    Simulation and Analysis of A Low Power RF Energy Acquisition System
    LI Shuai,YANG Jian,WANG Tao,HUANG Xin,MA Shifeng
    Electronic Science and Technology. 2023, 36(6):  50-56.  doi:10.16180/j.cnki.issn1007-7820.2023.06.008
    Abstract ( 76 )   HTML ( 2 )   PDF (2157KB) ( 19 )  
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    In view of the low conversion efficiency of RF-DC in traditional radio frequency energy acquisition system, a low power radio frequency energy acquisition system with an overall conversion efficiency greater than 50% in the range of 5~10 dBm incident power is designed in this study. Based on the single-stage Villard rectifier voltage doubling circuit structure, the doubling order is increased to seven, which effectively improves the output voltage and power of the system, thus improving the conversion efficiency of the system. The system is designed and simulated by ADS radio frequency software. When the parameters of echo loss S11 meet the design requirements, the circuit is imported into Altuim Designer for physical production. The output voltage of the system load resistance at different incident powers is measured, and the rectifier conversion efficiency at corresponding powers is calculated. The simulation results and experimental data show that the overall conversion efficiency of the system can reach more than 50% when the incident power is 5~10 dBm, and the maximum conversion efficiency is 54.1% when the incident power is 10 dBm. Compared with the radio frequency energy acquisition system at the same frequency point,the system designed in this study has a higher output voltage under the condition of the same level of load resistance and input power, which improves the conversion efficiency of RF-DC.

    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
    Abstract ( 262 )   HTML ( 3 )   PDF (1515KB) ( 26 )  
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    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.

    A Method of Facial Mask Segmentation Based on CA-Net
    LI Keran,CHEN Sheng,KE Panpan
    Electronic Science and Technology. 2023, 36(6):  64-71.  doi:10.16180/j.cnki.issn1007-7820.2023.06.010
    Abstract ( 76 )   HTML ( 8 )   PDF (2093KB) ( 32 )  
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    Wearing medical masks of various materials and types will lead to different prevention and control the effect of virus spread. Segmentation to masks in image data sets will benefit analyzing the differences in prevention and control effects of different types of masks. Currently, there are many facial mask detection algorithms, but there is a lack of further segmentation. Therefore, this study proposes a facial mask segmentation method based on image processing and deep learning. An improved contrast-limited adaptive histogram equalization preprocessing method is proposed to reduce the poor effect of traditional preprocessing caused by dark part of the image through brightness adaptive adjustment. SSD network is used for mask pre-detection, and CA- Net is used for mask segmentation. With U-Net as the backbone network, CA-Net adds spatial attention module, channel attention module and scale attention module to realize the comprehensive attention guidance of space, channel and scale of feature map at the same time. The segmentation result is processed by binary image closing operation to get the final segmentation results. The Dice evaluation of preliminarily segmentation index can reach to 79.18%±3.44%, and the Dice coefficient is increased to 84.03%±2.81% by adding preprocessing and post-processing operations, indicating that the proposed method could significantly improve the visual segmentation results.

    Face Recognition with Occlusion Based on Improved GD-HASLR Algorithm
    XU Tiantian,XI Zhihong
    Electronic Science and Technology. 2023, 36(6):  72-79.  doi:10.16180/j.cnki.issn1007-7820.2023.06.011
    Abstract ( 57 )   HTML ( 3 )   PDF (1758KB) ( 17 )  
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    When the number of training samples is reduced, the recognition result of occlusion face recognition algorithm will also decrease. To solve this problem, an improved GD-HASLR algorithm is proposed. Firstly, the algorithm obtains the generalized gradient direction of the face image, and calculates the gradient size and gradient direction of the face image from the first order to the third order. Then, after mapping with the mapping function, the gradient direction vector is obtained, which is used as the input of the hierarchical sparse low-rank model, and the representation coefficient and error of the image are obtained. In this study, a restarted fast algorithm with shrinkage threshold-II is adopted to solve the sparse representation coefficient. Finally, the residuals of the first order to the third order test samples are calculated respectively, and the category with the highest frequency or the lowest average grade is selected as the classification result. Experimental results on AR and Extended Yale B databases show that compared with GD-HASLR and other methods, the recognition effect of the improved method proposed in this study is better.

    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
    Abstract ( 213 )   HTML ( 7 )   PDF (915KB) ( 54 )  
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    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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