Table of Content

15 February 2020 Volume 33 Issue 2

  

Response of High-Altitude Electromagnetic Pulse to New Energy Rechargeable Cable

XIE Xutong,LU Hongmin,HU Kuan,SONG Bingxin,MENG Xiaojiao

Electronic Science and Technology. 2020, 33(2):  1-5.  doi:10.16180/j.cnki.issn1007-7820.2020.02.001

Abstract ( 294 )   HTML ( 7 )   PDF (1036KB) ( 49 )  

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With the development of new energy technology, the application of multi-frequency devices and high-voltage wire harness makes the electromagnetic compatibility of new energy vehicles become more and more complicated. It is of great engineering value to study the complex electromagnetic environment effect and protection of the new energy charging cable of special vehicle. In this paper, a new energy charging cable was selected, and the electromagnetic interference source and the charging cable model were established by using the three-dimensional electromagnetic field simulation software (CST). Based on the field-line coupling principle, the electromagnetic response of recharged cables in hybrid armored vehicles irradiated by high altitude nuclear electromagnetic pulse was simulated and analyzed. The simulation results showed that the larger the cross-sectional area of the same cable, the greater the coupling current of the cable port. Under the same interference pulse, the peak time and the beginning attenuation time of the coupling current at different cable ports were different, and the cable layout affected the coupling current at the cable port. The coupling current of cable impedance matching was much larger than that of load impedance mismatch, and the high altitude nuclear electromagnetic pulse response of new energy charging cable was in good agreement with that of traditional SYV-50-3 coaxial cable.

Research of ECG Detection Technology Based on Improved Differential Threshold Algorithm

ZHANG Xiaojun,WU Zhilu

Electronic Science and Technology. 2020, 33(2):  6-13.  doi:10.16180/j.cnki.issn1007-7820.2020.02.002

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Aiming at the limitation of fixed threshold in differential threshold algorithm, an algorithm based on adaptive peak threshold and R wave interval threshold was proposed. The algorithm automatically selected the peak threshold based on the characteristics of the ECG signal, and selected the R-wave interval threshold to improve the adaptability and accuracy of the algorithm. In this study, the ECG signal in the MIT-BIH arrhythmia database was used as the experimental sample. The combination of bandpass filtering and wavelet threshold filtering were utilized to complete the denoising of ECG signals. The ECG signals were detected by the improved differential adaptive threshold algorithm. The experimental results showed that the algorithm could improve the detection accuracy of R wave of ECG signal to 99.57%. The algorithm effectively reduced the occurrence of false detections and missed inspections, and accurately calculated heart rate, heart rate variability, physical fatigue, mental fatigue and common arrhythmia classification.

Research on Flux Weakening Control Technology of Interior Permanent Magnet Synchronous Motor

SHI Xun,YI Yingping,WANG Xiaoli

Electronic Science and Technology. 2020, 33(2):  14-19.  doi:10.16180/j.cnki.issn1007-7820.2020.02.003

Abstract ( 404 )   HTML ( 7 )   PDF (1154KB) ( 61 )  

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In order to meet the speed and torque requirements of interior permanent magnet synchronous motor used in electric vehicles under different working conditions, a control strategy based on standardized mathematical model combining with on-line calculation method of Maximum Torque Per Ampere control and voltage feedback method of flux-weakening control was designed. Taking a 2.8 kW permanent magnet synchronous motor as the research object, the control strategy was simulated by using MATLAB/Simulink, and the experimental platform of flux-weakening control system was established. Simulation and experimental results demonstrated that the control strategy had good robustness and faster torque response speed, which could meet the requirements of motor speed and torque under different working conditions.

Behavior Modeling of Class-D Power Amplifier Based on Encoder-Decoder Model

ZHAO Yihe,SHAO Jie,CHENG Yongliang

Electronic Science and Technology. 2020, 33(2):  20-24.  doi:10.16180/j.cnki.issn1007-7820.2020.02.004

Abstract ( 244 )   HTML ( 1 )   PDF (1012KB) ( 40 )  

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Class D power amplifiers have excellent transmission efficiency and are classified as power amplifiers. Their output signals have large nonlinear distortion. The behavior modeling of calss-D power amplifier should take into account both nonlinearity and memory characteristics. This study introduced wavelet transform into the encoder-decoder neural network model, and proposed sequence to sequence wavelet neural network model. In this paper, the encoder-decoder model and sequence to sequence wavelet model based on gated recurrent unit were used in the behavior modeling of class-D power amplifier. Experiments results demonstrated that the proposed behavior model of class-D power amplifier had higher precision in time and frequency domain than the traditional Voterra-Laguerre model.

Research on Face Detection Algorithm Based on Video

WANG Xin,WU Wei,ZENG Zhao

Electronic Science and Technology. 2020, 33(2):  25-31.  doi:10.16180/j.cnki.issn1007-7820.2020.02.005

Abstract ( 288 )   HTML ( 4 )   PDF (1014KB) ( 32 )  

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Aiming at the shortcomings of the traditional AdaBoost algorithm in detecting high false detection rate in video, an improved face detection algorithm combining motion analysis and skin color detection was proposed. The proposed method extracted motion prospects through motion detection, and selected the skin color model to obtain the similarity of the face skin color, and further narrowed the detection range by using the geometric features. The face candidate region was detected in real time detection the improved AdaBoost algorithm which was added with new Haarfeatures and improved weight update mode.The experimental results showed that compared with the traditional AdaBoost method and the AdaBoost method with skin color detection, the false detection rate of this method was reduced by 18.68% and 8.79% respectively, and the detection time was shortened by about 800 ms and 250 ms, respectively.

Parameter Identification and State of Charge Estimation of Lithium Ion Battery Model for Electric Vehicles

JIANG Qin,ZHANG Xuanxiong

Electronic Science and Technology. 2020, 33(2):  32-36.  doi:10.16180/j.cnki.issn1007-7820.2020.02.006

Abstract ( 386 )   HTML ( 1 )   PDF (920KB) ( 59 )  

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For the problems of low accuracy and poor real-time performance in on-line estimation of lithium-ion battery charging state for electric vehicles, an effective method for accurate on-line estimation of charging state was established. The method of MAFF-RLS and EKF was used to estimate the state of charge for lithium-ion battery. The equivalent circuit model of lithium-ion battery was established, and the MAFF-RLS was applied to the parameter identification for the equivalent circuit model, which could effectively identify model parameters online. Based on the model parameter identification, the identified model parameters are used as the input of the state of charge estimation, and the EKF was used to estimate the real-time state of charge of the power battery. The experimental simulation showed that the combination of MAFF-RLS and EKF could improve the estimation accuracy of the state of charge, and the estimation error was within 2%.

Digital Image Source Forensics Based on Image Noise Residual

HUANG Mingying

Electronic Science and Technology. 2020, 33(2):  37-42.  doi:10.16180/j.cnki.issn1007-7820.2020.02.007

Abstract ( 292 )   HTML ( 6 )   PDF (841KB) ( 56 )  

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There are some problems with the image source forensics algorithm using the support vector machine, such as the large training set (about thousands) and the high dimension feature. To solve these problems, a forensic algorithm was proposed, which required only a small number (about 10) of training images, and only extracted the residual of the image noise as the unique feature of the image. The algorithm firstly used the wavelet filter to extract the image noise, and then extracted the residual of the image noise using the regression model. Finally, the Gaussian distribution model was established for the noise residual, and the source evidence was obtained according to different types of images with different model parameters. The experimental results showed that under the condition of FPR of 1.2%, the TPR of the proposed algorithm for natural images was 95.33%, and the TPR for computer-generated graphics was 96.44%.

An Identification Method of Coins Denomination Based on Image Detection

MA Xudong,YUAN Ruibo

Electronic Science and Technology. 2020, 33(2):  43-47.  doi:10.16180/j.cnki.issn1007-7820.2020.02.008

Abstract ( 1073 )   HTML ( 68 )   PDF (929KB) ( 174 )  

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In order to realize accurate recognition of multiple coin denominations at the same time, a recognition method of coins denomination based on image detection was proposed in this paper. Firstly, median filtering, threshold segmentation and morphological operations were gradually used to extract ROI of coins in grayscale image to realize rough coins positioning. Then, the smallest rectangles outside ROI were taken as the research area to extract the images from the original image. The extracted images were transformed from RGB color space to HSV color space, so the 5-dime coins could be identified through the difference of color features. Finally,SSIM image quality evaluation method was used to detect and identify the 1-dime coins and 1-yuan coins in the remaining ROI. The result showed that the identification method of coins denomination could accurately identify multiple coins at the same time without accurately obtaining the coin size.

Study on Near-infrared Quantitative Analysis of Blood Glucose

HU Jie,WANG Kai,WANG Yagang,LI Wenshuai

Electronic Science and Technology. 2020, 33(2):  48-53.  doi:10.16180/j.cnki.issn1007-7820.2020.02.009

Abstract ( 422 )   HTML ( 4 )   PDF (1061KB) ( 31 )  

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In order to solve the problem of traditional invasive blood glucose detection, the noninvasive blood glucose detection technology by near infrared spectroscopy was studied. The near infrared spectra of glucose solution were measured by TALYS ASP531 near infrared spectrometer of ABB Company. The selected modeling band was 5500~6500 cm ^-1 and the calibration model between spectral data and corresponding concentration was established by partial least squares method. According to the experimental results, the determination coefficient of the calibration model reached 0.98399, the root mean square deviation was 1.023 26 mmol·L ^-1, and the error distribution was -1.3~1.7 mmol·L ^-1. The results demonstrated the feasibility of non-invasive detection of human blood glucose concentration by near-infrared, and provided a reliable basis for the study of near-infrared blood glucose detection.

Implementation of a Collaborative Filtering Algorithm Based on Improved Similarity

XU Fengxiang

Electronic Science and Technology. 2020, 33(2):  54-59.  doi:10.16180/j.cnki.issn1007-7820.2020.02.010

Abstract ( 231 )   HTML ( 2 )   PDF (867KB) ( 32 )  

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When calculating the similarity, the collaborative filtering algorithm assigns similar weights to all users or items, which will lead to deviations in the similarity calculation. Aiming at this problem, an improved similarity algorithm was proposed to fix the error. Firstly, when calculating the similarity between users, the active user influence factor was added by the number of active users, and when calculating the similarity between items. When calculating the similarity between items, the hot item influence factor was added according to the popularity of the item, then similarity was maximum normalized. Finally, the rating of movies was predicted by using similarity matrix. The experimental results showed that the improved similarity algorithm was more accurate in rating prediction, and the average absolute error was stable at around 0.72.

PCB Board Common Sorting Algorithm Based on Convolutional Neural Network

WANG Zhengjun,YAO Yiming,CHEN Long

Electronic Science and Technology. 2020, 33(2):  60-65.  doi:10.16180/j.cnki.issn1007-7820.2020.02.011

Abstract ( 335 )   HTML ( 4 )   PDF (1037KB) ( 33 )  

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The feature points of the traditional PCB board sorting algorithm are manually extracted, and the pose calculation method is single, which has the disadvantages of complex pretreatment steps, high sample requirements, low pose accuracy and low applicability. To solve the above problems, a general sorting algorithm for PCB board based on convolution neural network was proposed in this paper. An improved CaffeNet network model was constructed to automatically learn the deep features of PCB boards in a large number of image data, completed the automatic recognition and classification of PCB boards. The modified RANSACS algorithm was used to improve the accuracy of feature point matching of ORB algorithm, and the least square method was conducted to calculate the angle difference between the image of the board and the image to be matched, so as to realize the rapid positioning of all kinds of PCB boards. The result showed that the sorting accuracy of the algorithm reached 99.35%, which had good accuracy and sorting efficiency.

Parameters Estimation for Multi-Component Polynomial Phase Signal by Combining RPRG and ICCD with RANSAC

CHENG Yongliang,SHAO Jie,ZHAO Yihe

Electronic Science and Technology. 2020, 33(2):  66-70.  doi:10.16180/j.cnki.issn1007-7820.2020.02.012

Abstract ( 300 )   HTML ( 0 )   PDF (673KB) ( 37 )  

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The detection and parameter estimation of multi-component polynomial phase signals is a major difficulty in polynomial phase signal processing. Time-frequency analysis method can characterize the instantaneous frequency of polynomial phase signals by time-frequency distribution. The coefficients of the extracted instantaneous frequencies can be obtained by polynomial fitting. Finally, the parameters of the polynomial phase signal can be obtained through a simple transformation. In this study, the multi-component polynomial phase signal was separated by RPRG+ICCD to obtain the instantaneous frequency of each component, and then RANSAC was used for polynomial fitting. Finally, the parameter estimation of the polynomial phase signal was realized. The experimental results demonstrated that the proposed method could achieve the separation and parameter estimation of multi-component polynomial phase signals overlapping in the time-frequency domain.

Research on Substation Intelligent Operation and Inspection Management System Based on GIS Technology

ZHU Liang,ZHOU Yong,CHEN Jia,WU Yeyang,ZHANG Jing

Electronic Science and Technology. 2020, 33(2):  71-74.  doi:10.16180/j.cnki.issn1007-7820.2020.02.013

Abstract ( 262 )   HTML ( 2 )   PDF (669KB) ( 30 )  

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Aiming at the demand of substation intelligent operation and inspection management, this paper studied the substation intelligent operation and inspection management system based on GIS technology. The system used the basic framework of WebGIS technology as the platform of operation and inspection management. On this basis, it completed the three-tier system platform of data layer, service layer and platform layer. Web server and FlexRIA control were used to realize the comprehensive integration of intelligent operation and inspection management system and GIS technology, and realized the omni-directional perception of substation operation and inspection management information. On the physical hardware, the distributed deployment of servers was adopted, and the effective interconnection between Web servers and Agent servers was realized by using DCN network. The information resources of power system and GIS map were integrated in an all-round way. The utilization efficiency of hardware resources and the response speed of the system were improved by means of all-round cooperation. The content of this paper was to realize the intelligent operation and inspection management of substations. It was of great significance to complete the assumption of ubiquitous power Internet of things.

Study on Electric Field Effect of Multilayer Ferromagnetic Two-Dimensional Materials

CHEN Jing

Electronic Science and Technology. 2020, 33(2):  75-78.  doi:10.16180/j.cnki.issn1007-7820.2020.02.014

Abstract ( 209 )   HTML ( 0 )   PDF (901KB) ( 26 )  

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The emergence of two-dimensional (2D) materials had drawn great attention due to its fascinating physical properties and potential applications for future nanoelectronic devices. Two-dimensional ferromagnetism in Cr₂Ge₂Te₆ (CGT) had been demonstrated, however, for two-dimensional CGT, there had been a lack of research on electron transport properties and electric field effects. Therefore, CGT ferromagnetic sheeted with a thickness of only a few nanometers had been prepared and identified, which provided a very important piece for the van der Waals structure composed of various 2D materials. We further demonstrated the large modulation of the channel resistance of 2D CGT devices by the electric field effect. The experimental results illustrate the gate voltage tunability of 2D CGT and the potential of ferromagnetic 2D material CGT as a new functional quantum material for future use.