Table of Content

15 May 2023 Volume 36 Issue 5

  

Short-Term Wind Speed Prediction Based on EMD-GWO-SVR Combined Model

LIN Lin,WANG Wanxiong

Electronic Science and Technology. 2023, 36(5):  1-8.  doi:10.16180/j.cnki.issn1007-7820.2023.05.001

Abstract ( 201 )   HTML ( 76 )   PDF (1228KB) ( 136 )  

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Wind speed prediction is of great significance to wind power plant scheduling and control. In view of the randomness and intermittence of wind speed series, an EMD-GWO-SVR combined prediction model is proposed in this study. Empirical mode decomposition is performed on the original sequence, and grey wolf optimization algorithm is used to optimize the parameters of the support vector regression model. Then, the optimized parameters are substituted into the support vector regression model, and the decomposed eigenmode function and residual term are predicted, respectively. The predicted results are added together to predict the wind speed. Taking the historical meteorological data of Jiuquan in Gansu province as an example, six forecasting models including BP neural network, SVR, PSO-SVR, GWO-SVR, EMD-PSO-SVR and EMD-GWO-SVR, are established to forecast the wind speed. The simulation results show that the prediction accuracy of the proposed EMD-GWO-SVR model is 61.759 8% higher than that of SVR, and the evaluation values of MAE, MAPE and RMSE error indexes are significantly lower than those of the other five models.

Integrated Control Strategy of Wind Turbine Inertia Support and Primary Frequency Regulation

ZHU Jiawen,CHEN Zhuo,LIU Renzhi,LIU Bolin,CHEN Xiangping

Electronic Science and Technology. 2023, 36(5):  9-15.  doi:10.16180/j.cnki.issn1007-7820.2023.05.002

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In response to the problem of reduced system inertia and insufficient frequency regulation capacity due to large-scale wind power connection to the grid, an integrated control strategy scheme for wind turbine inertia support and primary frequency regulation is proposed. In this scheme, the load reduction control of wind turbine is adjusted based on the characteristics of wind turbine slurry distance angle, and the reserve capacity required for wind turbine frequency modulation is reserved, which further solves the combination problem between the frequency change of the power grid and the virtual moment of inertia in the load reduction mode. In addition, the wind turbine speed protection is considered to set the static adjustment coefficient, and combined with the inertia support control, to achieve the wind turbine integrated frequency control strategy. The co-simulation model including wind farm is built in MATLAB/Simulink platform. The results show that the wind turbine can quickly provide virtual rotational inertia support to the grid, reduce the rate of change of the initial grid frequency perturbation, and regulate the output power according to the adjusted static regulation differential coefficients to improve the frequency stability of the wind power connected to the grid, which verifies the rationality of the proposed control strategy.

PI Approximate Engineering Design of DC-DC Conversion Compensation Network

WU Fuzhuan,XIANG Naihuang,ZHOU Yuanhao,CHEN Mengna

Electronic Science and Technology. 2023, 36(5):  16-22.  doi:10.16180/j.cnki.issn1007-7820.2023.05.003

Abstract ( 124 )   HTML ( 6 )   PDF (805KB) ( 33 )  

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In view of the blindness of the trial-and-error method in the design of DC-DC transform compensation network and the complexity of theoretical analysis, based on the state space average method, this study takes Buck as an example to model the DC-DC transformation system. Under the condition that the amplitude margin and phase margin are satisfied, the relationship between the compensation network k_p, k_i and the system parameter duty ratio D, inductance L and capacitance C is derived, and on this basis, an engineering approximation method is proposed. The proposed method is verified by PSIM simulation and a prototype platform based on DSP. The results show that the results obtained by this engineering approximation method are basically consistent with the theoretical analysis method, that is, the traditional control method, no matter in the case of voltage single closed loop or in the case of voltage outer loop and current inner loop. This engineering approximation method avoids the blindness of trial and error and the complexity of traditional control methods, which is the complexity of traditional control methods, and provides a quick method and idea for the rapid design of compensation networks in actual projects.

An Improved Average Current Control Method for Single-Phase Totem Pole Rectifier

XIA Yuanshuai,XIE Ming,YANG Yang,YAO Lei

Electronic Science and Technology. 2023, 36(5):  23-27.  doi:10.16180/j.cnki.issn1007-7820.2023.05.004

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In order to effectively suppress the harmonic pollution caused by power electronic equipment to the power grid and solve the problem of energy shortage, high-efficiency AC/DC PFC converter has attracted extensive attention. In order to solve the problems of conversion efficiency and current zero-crossing distortion of totem pole PFC converter, the diode in traditional topology is replaced by power switching tube, and an improved average current control strategy based on CCM mode is proposed. The control strategy improves the control mode of high-frequency bridge arm, reduces diode freewheeling loss and improves the conversion efficiency of the converter by introducing complementary PWM. The working principle and control strategy of totem pole topology circuit are described in detail, and the proposed strategy is simulated based on MATLAB/Simulink platform. On this basis, a prototype is designed and built. The experimental results show that the conversion efficiency of the proposed method is improved by 1.5%, and the current has no obvious zero-crossing peak, which proves the effectiveness and feasibility of the proposed improved control strategy.

CNAS Recognition Criteria Automatic Benchmarking System Based on Natural Language Processing

LIU Yuwei,CAO Min,FENG Haojia

Electronic Science and Technology. 2023, 36(5):  28-33.  doi:10.16180/j.cnki.issn1007-7820.2023.05.005

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During the CNAS review process, manual benchmarking of non-conformance items and its compliance clauses has the disadvantages of time-consuming, labor-intensive, and inaccurate benchmarking. In view of the above problems, this study proposes a multi-level model automatic benchmarking method based on natural language processing. By studying the linguistic characteristics of the description of non-conforming items, the Bi-LSTM network of the attention mechanism is used to classify non-conforming items. Under this classification, the SimCSE network model based on corpus expansion and transfer learning is used to calculate similar non-conforming items and extract the corresponding basis clauses, which effectively solves the problems such as inaccurate benchmarking.Through simulation experiments, the benchmarking accuracy rate of the proposed method can reach 74.4%, and the semantic matching calculation time is greatly improved when compared with the DSSM model, and the memory consumption and the highest matching speed are also been significantly improved.

Abnormal Data Detection and SOC Estimation Algorithm for Lithium Battery Considering Measured Outliers

WANG Changsong,CHEN Hui,WANG Licheng,QU Feng

Electronic Science and Technology. 2023, 36(5):  34-40.  doi:10.16180/j.cnki.issn1007-7820.2023.05.006

Abstract ( 214 )   HTML ( 2 )   PDF (1077KB) ( 41 )  

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In view of the problem of outliers in sensor measurement in lithium battery, a chi-square detector and corresponding filtering algorithm are designed to eliminate the influence of outliers on lithium battery state of charge estimation in this study. The second-order RC equivalent circuit is selected to describe the battery dynamic model, and the parameters of the battery model are identified by Kalman filter in an off-line way. Considering the existence of outliers in sensor data, the chi-square detector is used to detect the outliers in real-time. When outliers are detected, an improved SOC estimation algorithm that only depends on the model is proposed according to the idea of zero-order preservation, which can resist the measured outliers well. Under FUDS condition, the experimental simulation shows that the designed outlier detector and the improved SOC estimation algorithm can accurately detect the occurrence of outliers, and the estimation error of SOC is guaranteed within 2%, reflecting good estimation performance.

Bipartite Formation Control of Swarm Systems Based on Output Feedback

TANG Kai,ZHANG Wei,HU Zhi,WANG Weike

Electronic Science and Technology. 2023, 36(5):  41-46.  doi:10.16180/j.cnki.issn1007-7820.2023.05.007

Abstract ( 73 )   HTML ( 1 )   PDF (1242KB) ( 33 )  

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The swarm system is a specific system composed of multiple agents interacting with information locally. Part of agents’ state is difficult to available or even undetectable in practical applications, and the relationship between agents can be cooperative or competitive. In this study, a bipartite formation control protocol for distributed swarm systems based on output feedback is designed under the signed network topology. This strategy takes the output state between neighboring agents as the feedback information without relying on the global information of the communication topology. Considering that the real systems are often affected by external disturbances, some sufficient conditions that the control protocol can guarantee the system error is finally uniformly bounded are established based on Lyapunov stability theory. After analyzing the robustness of the protocol, the residual set of the final uniformly convergent errors is given. According to the designed control protocol and formation conditions, simulation is carried out to verify the effectiveness of the protocol, and the time for the system to reach stability under different initial ranges is given.

An Extended Dimension Kalman Filter Method Based on Additive Hidden Variables

LIN Zhipeng,SUN Xiaohui,WEN Chenglin

Electronic Science and Technology. 2023, 36(5):  47-54.  doi:10.16180/j.cnki.issn1007-7820.2023.05.008

Abstract ( 98 )   HTML ( 3 )   PDF (929KB) ( 37 )  

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The performance of Kalman filters designed for nonlinear systems often degrades with the increase of nonlinear degree. In order to make up for the shortcomings of extended Kalman filter and unscented Kalman filter in the online process, this study proposes an extended dimension Kalman filter method based on hidden variable for a class of strongly nonlinear systems composed of the accumulation of linear and non-linear terms. In this method, the nonlinear term is defined as the hidden variable of the original system, and the linear dynamic correlation model about the hidden variable is established. The hidden variable is extended to the original state variable of the system, so as to establish the linear system model based on the original variable and hidden variable. Finally, the high-order extended dimension Kalman filter of this kind of system is designed. Through MATLAB simulation, the effectiveness and accuracy of the performance of the designed filter are verified.

UAV Detection Based on Slim-YOLOv4 with Embedded Device

ZHENG Yuheng,FU Dongxiang

Electronic Science and Technology. 2023, 36(5):  55-61.  doi:10.16180/j.cnki.issn1007-7820.2023.05.009

Abstract ( 153 )   HTML ( 4 )   PDF (3131KB) ( 49 )  

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In order to realize real-time detection of UAV on resource-constrained embedded devices, this study proposes a lightweight detection network, Slim-YOLOv4, based on YOLOv4. In this network, Ghostnet is used to replace the main feature extraction part of the original YOLOv4, the 3×3 convolution in the feature fusion part is replaced by the deep detachability convolution and the activation function in the deep detachability convolution is optimized to reduce the number of parameters and computation of the network and accelerate the convergence of the network. The experimental results show that the accuracy of the Slim-YOLOv4 is 91.6%, which is 1.6% lower than that of the original YOLOv4, but the weight file of original YOLOv4 is up to 250 MB. On the premise of not affecting the robustness, the weight file size of Slim-YOLOv4 is only 42 MB, which is better than the 108 MB of Fan-RCNN model and 53 MB of Mobilenetv3 model. The number of images processed per second by the proposed method reaches 31.2 frames·s^-1 on PCS and 37.6 frames·s^-1 on embedded devices, proving that the proposed method can be deployed on embedded devices for real-time detection of UAVs.

Underwater Occlusion Target Detection Algorithm Based on Attention Mechanism

SHI Jianke,QIAO Meiying,LI Bingfeng,ZHAO Yan

Electronic Science and Technology. 2023, 36(5):  62-70.  doi:10.16180/j.cnki.issn1007-7820.2023.05.010

Abstract ( 243 )   HTML ( 6 )   PDF (4296KB) ( 46 )  

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In view of the problems of foreground occlusion and background blur in underwater target detection task, an underwater target detection algorithm based on attention mechanism is proposed. Firstly, the image enhancement algorithms are used to improve the image quality. Then, based on the similarity function of the non-local neural network, the concatenation similarity function with logical reasoning capability is fused to enhance the expression ability of the network to the global context features. Additionally, the improved non-local neural network is combined with the triplet attention to make up for the channel features lost by the non-local neural network. Finally, the dilated convolution module is used to replace the pooling operation in triplet attention to reduce the loss of fine-grained information. Experiments show that the proposed algorithm increases the detection accuracy of baseline method from 65.66% to 68.55% on the data set provided by the 2020 National Underwater Target Detection Contest, which proves the effectiveness of the proposed algorithm.

Study on the Characteristics of Ignition Discharge of A Small Penning Ion Source by Increasing Magnetic Field

ZHANG Jinghao,ZHANG Xuanxiong,Christian Wolf,Michael Wick

Electronic Science and Technology. 2023, 36(5):  71-79.  doi:10.16180/j.cnki.issn1007-7820.2023.05.011

Abstract ( 168 )   HTML ( 1 )   PDF (5268KB) ( 40 )  

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During the miniaturization of Penning ion source, there are some problems such as the increase of ignition voltage, breakdown of insulating material between cathode and anode and unstable discharge. In order to promote the miniaturization of the internal structure of the Penning ion source, the stable discharge of the Penning ion source is achieved by increasing the magnetic field under the constant electric field, the voltage drop discharge is achieved, the service life of the insulating material is extended, and the stable discharge is achieved. In addition, COMSOL Multiphysics software is used to simulate the distribution of electric field and magnetic field inside the improved ion source, and to simulate and analyze the motion and ionization of electrons in different regions. Based on this, a physical model of ignition based on constant electric field and magnetic field is established. The results of comparison between the model and the actual ignition experiment show that the improved small Penning ion source can realize stable discharge only by increasing the magnetic field to 156.29 mT under the condition of constant voltage of 0.8kV.

Control Strategy of Ammonia Desulfurization Based on Smith Predictive Fuzzy PID

ZHU Mingji,ZHANG Huilin,MA Lixin

Electronic Science and Technology. 2023, 36(5):  80-87.  doi:10.16180/j.cnki.issn1007-7820.2023.05.012

Abstract ( 148 )   HTML ( 4 )   PDF (1056KB) ( 40 )  

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The ammonia desulfurization system has the problems of large lag, nonlinearity and poor real-time load tracking. Smith predictive controller has been designed to solve these problems, which improves the real-time performance of the system by compensating the delay time. However, the PID parameters of system are always set by cut-and-try method, which results in poor stability of the system. In this study, a fuzzy PID parameters adaptive adjustment method is proposed. The adjustment values of parameters of the PID controller are obtained by the fuzzy algorithm, and the PID parameters are adjusted adaptively, so that the SNOx concentration is controlled near the preset value. Different from the traditional step signal judgment control effect, the proposed method uses real-time load data to simulate the model, and the data simulation results prove the feasibility of Smith calculation fuzzy PID controller. When the system is stable, the error between SNOx concentration and the preset value is within 0.5 ppm, and adjustment time is greatly shortened. These results show that the proposed method improves the real-time tracking performance of the ammonia desulfurization control system, and realizes the fast, accurate and stable desulfurization control performance.

Research on the Index Strategy of Deck Operation Station Selection Based on Simulation Optimization

BIAN Dapeng,WANG Yeting,PENG Yaxin,TANG Haoquan

Electronic Science and Technology. 2023, 36(5):  88-94.  doi:10.16180/j.cnki.issn1007-7820.2023.05.013

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Under certain conditions of deck resource allocation, resource allocation strategy affects the operational efficiency of aircraft carrier. This study proposes the deck station allocation problem. Starting from the calculation models of dispatching time and queuing time, a dynamic station allocation strategy based on station index is proposed. The strategy determines a suitable station allocation scheme dynamically according to the current operation conditions. Using genetic algorithm to search for the best weight of station parameters, where the objective is to minimize the deck operation duration. Through simulation experiments, the superiority of the proposed strategy is verified by comparing it with other common strategies in the evaluation index of deck operation duration. Using the proposed strategy can obtain better deck operation duration, and improve the sorties rate of the shipborne aircraft.