bluuebunny/crossref_metadata_2025 huggingface dataset:
PMSM Speed Sensorless System of Intercity Railway Track Inspection Trolley Based on FOSMO-MRAS Observer
Authors: Du Fang , Xu Feng , Wu Xiaoliang
Published: December 2022

For realizing the speed sensorless control system of the intercity railway track inspection trolley, reducing the manufacturing cost and volume weight of the track inspection trolley, and improving the performance of the three-phase permanent magnet synchronous motor (PMSM) control system inside the track inspection trolley, a new fractional sliding mode variable structure model reference adaptive (FOSMO-MRAS) method is proposed to construct the motor speed observer, and a new sliding mode approach law is constructed by using a hyperbolic tangent function instead of a traditional discontinuous switching function. The simulation results show that the speed sensorless control strategy of PMSM based on the FOSMO-MRAS observer has good dynamic and static performance. And the robustness and reliability of the system are improved.
Compensatory Fault-Tolerant Control Toward the Manipulator in a High-Throughput Preparation System
Authors: Liu Fuqiang , Zhao Bin , Ma Zuxing , Zhong Songyi
Published: December 2022

A Deviation-Division Fault-Tolerant Control (D-D FTC) scheme which can produce convergent compensating control inputs for the faulty yet partially controllable actuators in finite steps is proposed in this paper. Based on the D-D FTC scheme, the implementation of the robot manipulator in a high-throughput preparation system is derived. Moreover, the simulation is given to illustrate the effectiveness of the proposed scheme.
Detection Method Based on RFID Tag on the Metal Surface
Authors: Zhang Shuang , Gong Yuxin , Zhu Guokai
Published: December 2022

In radio frequency identification (RFID) technology, RFID tags’ work on the metal surface is greatly affected by the metal, and the read/write distance and read rate of the tag will be reduced along with the change of the distance between the tag and the metal surface. Aiming at this feature, this paper studies and designs two kinds of metal-resistant UHF RFID micro-strip tags with a center frequency of 915MHz according to the “resonant cavity principle” and HFSS simulation software. After optimization, the size of the tag antenna is reduced. Through the distance expression and experiment, we verify the maximum recognition distance between the reader, and the tag can reach 3.46m, which can solve the problem of conventional RFID tags by metal interference.
Load Regulation Method of Interaction Between Electric Vehicle and Power Grid Based on LSTM
Authors: Chen Wenfu , Zhang Jian , Li Siwei , Yuan Shuai , Cai Shaotang
Published: December 2022

In response to the problem of disorderly charging of scaled new energy vehicles, which causes an increase in the intermittency and randomness of the overall load and then leads to the instability of the distribution network, an edge-control-based load regulation method for scaled vehicle-network interaction is proposed. Firstly, the sequence of influencing factors is constructed, and the data is processed by using weighted Marxist distance to realize the accurate extraction of electric vehicle load power data. Secondly, feature extraction of the data by using Long Short-Term Memory (LSTM) to realize fast and accurate prediction of regional load. Then, an edge-side regulation model is constructed with the objective function of minimizing network loss and minimizing peak-to-valley difference and solved by the wolf pack algorithm. Then, the edge controller is used to control the tide of each pile-end management unit to realize the effective cooperative regulation of each station-pile-net. Finally, using the edge controller physical device with an example of the distribution network in a region of Tianjin, it is verified that the method has good prediction accuracy and ensures the reasonable deployment as well as stability of the distribution network.
A Control and Simulation Method for Space-based Opto-mechanical Structures Using Uniform Scanning
Authors: Chang Xia , Song Li , Wang Chun , Zhang Ai
Published: December 2022

To achieve high-precision imaging in the calibration area of a sub-satellite point, this paper proposes a method for assessing the scanning accuracy and how it affects the agility of the maneuvering process. In addition, simulations and experimental validation are also conducted using a position-velocity dual-loop control algorithm. The design is based on the control theory and the operating characteristics of the actual flexible scanning mechanism, the control law is designed using the control method based on the permanent magnet synchronous motor model, and the interference is simulated and analyzed. The results show that the design can combine the control performance indexes of practical applications and meet the requirements of in-orbit high-precision scanning, which can provide a reference for the subsequent development of space high-precision scanning control.
Optimal Scheduling of Integrated Energy Systems Considering Carbon Trading
Authors: Xu Tao , Cheng Cheng , Ren Fei , Zhang Weiwei
Published: December 2022

Under the background where the electricity market and the carbon market are booming, the operation and dispatch of the integrated energy system requires the introduction of a carbon trading mechanism that can help guide customers and system operators to optimize electricity consumption and dispatch plans. A mathematical model of the community-integrated energy system, including energy storage, gas turbine generation system, and flexible load, is constructed based on energy hubs. In the consideration of costs in operation and carbon trading of the system, a low carbon economic dispatch model is established for IES to achieve the optimization objective of minimizing the total cost. The simulation results show that the coupled electric and thermal dispatch and the participation and interaction of flexible electric and thermal loads can lower the load peak-to-valley difference and significantly reduce the system operation cost, and the flexible load participation and dispatch under the carbon trading system can effectively bring the system more environmental and economic benefits.
Research and application of forward three-dimensional design method of substation
Authors: Xu Wenzhe , Shi Jiabing , Sun Zhengzhu , Lv Shudong , Fang Junqi , Li Wenting , Lv Lei , Ni Yuxiang
Published: December 2022

During the operation of digital substations, they are vulnerable to the influence of different fault feature extraction, resulting in weak anti-interference in the detection process. To solve this problem, the singular value decomposition method is combined detection method to establish a prediction model. Firstly, the three-dimensional control mode model is established based on mathematical method to process the current signal with anti-interference; Secondly, the singular value method is used to optimize the current transmission process and denoise the fault signal feature extraction; Finally, the method of singular value decomposition is used to realize fault detection in substation operation.
Bearing fault diagnosis method based on refined composite multiscale fuzzy entropy
Authors: Li Yingli , Zhang Hongjie , Tong Yuanliang , Liu Wencai , Liu Jintao , Liu Wenbin
Published: December 2022

In this paper, a new fuzzy C-mean (FCM) clustering method based on refined composite multiscale fuzzy entropy (RCMFE) is proposed and applied to the bearing fault diagnosis of rotating machinery. The RCMFE adds multiscale processing, which can not only characterize the complex changes of time sequences at several different scales but also solve the problems of information loss caused by the process of coarse granulation and large fluctuation of entropy value when the scale becomes large. This method uses RCMFE to extract fault features, that are inputted into the Fuzzy C-mean clustering algorithm to achieve rolling bearing fault identification. Comparing the method with Multiscale Fuzzy Entropy (MFE) and Composite Multiscale Fuzzy Entropy (CMFE), the method used was experimentally proven to have better diagnostic results.
Steel Surface Defect Detection Based on Improved YOLOV5 Algorithm
Authors: Lu Yang , Qu Fuheng
Published: December 2022

When the traditional target detection method based on deep learning identifies steel surface defects, the recognition accuracy is low due to the imbalance of classification and regression tasks and the loss of feature information. To solve this problem, an improved YOLOV5 algorithm is proposed for steel surface defect detection. Firstly, the multi-branch prediction of regression and classification is decoupled, and three different outputs of regression, classification, and confidence are obtained through two different convolutions at the output end. Then, the features of different levels of the backbone network are adaptively weighted and fused, and the weighted coefficients of features of different depths are calculated by the softmax function, and then weighted and fused. Compared with the YOLOV5 algorithm, the experimental results show that the detection accuracy of the proposed algorithm is improved by 2.0%.
Study on Servo Control Method of Eye Movement Intention Based on Reinforcement Learning
Authors: Sun Xiangyang , Yu Jingsi , Wang Yi , Zhang Ning
Published: December 2022

Eye movement servo control has the advantage of non-contact and the eye movement is not affected by other limbs. By applying eye-tracking technology to rehabilitation research of people with movement disorders, the interaction between eye-tracking technology and computers will be gradually put into practice, which is equivalent to giving patients a pair of “invisible hands” that can give instructions freely. In this paper, a servo control method based on eye-movement coding technology is proposed to solve the problems of low accuracy, poor reliability, and insufficient human intention initiative in the field of eye-movement servo control of human-computer visual interaction. The human eye movement instruction is processed by coding and integrated with human eye movement intention to realize intelligent servo control of human eye intention. In order to improve the accuracy of eye movement servo control, this paper proposes an eye movement instruction coding processing method, which uses the trained AdaBoost fusion strong classifier algorithm and the landmark detector to detect the real-time algorithm in the video sequence to complete the eye location and blink determination. In this paper, an improved pupil location method based on multi-angle joint detection is proposed. The pupil location is completed by using the information of eye image points, and the digital coding model of eye command action is constructed, which provides an instruction base for eye movement servo control. In order to improve the reliability and initiative of eye-movement servo control, a reinforcement learning method combining eye-movement coded instruction and intention was proposed. By integrating the improved DDPG continuous control strategy reinforcement learning algorithm with eye movement intention instruction, the environmental status can be sensed in the human-computer interaction process and the optimal strategy of eye movement instruction selection can be learned.
Application of Fuzzy PID in Wheeled Robot
Authors: Luo Haocai , Zhang Changming
Published: December 2022

At this stage, wheeled robots are widely used in various fields. Usually, the gimbal is mounted above the wheeled robot as a platform for carrying other functional modules, and for the normal working environment of the module. We will use the traditional PID control algorithm to keep the gimbal relatively stable. However, in the face of complex terrain, the gimbal will be subject to huge disturbances from the chassis. The traditional PID algorithm has low robustness and cannot cope with this situation. In this paper, a fuzzy controller for the self-stabilization of the gimbal is added to the wheeled robot designed in the RoboMaster competition to maintain the stability of the gimbal under the condition of an uneven road to ensure that the gimbal has strong robustness. This robot uses STM32F427IH, the main control chip, and JetsonNanoA02, the host computer, with the FreeRTOS real-time operating system to complete the motion control of the robot.
Research on Compact Nanosecond High-voltage Pulse Source
Authors: Ding Jiandong , Cao Bing
Published: December 2022

With the application of pulse power technology in the fields of biomedical research, portable pulse source, and electromagnetic pulse radiation, the research of pulse sources puts forward new requirements such as compact structure, long pulse width, and high voltage resistance. The traditional pulse source has a long pulse period and short pulse width, which cannot meet the requirements of the high repetition frequency and high output power. In this paper, a nanosecond high-voltage pulse source is designed, which consists of a primary power supply, a pulse charging system, and a pulse shaping system. The DC power charges the Marx generator, while the Marx generator output is shaped by short-circuit sharpening switches. In this paper, PSpice simulation software is used to simulate the results: the pulse period is 1.4ns and the peak-to-peak voltage is 210kV.
Distributed Optical Fiber Strain Sensors Packaged with Polyurethane and GFRP
Authors: Xie Fumin , Mai Jiancong , Zhu Pingyu , Cheng Jianming
Published: December 2022

To apply optical fiber sensors in an extreme environment and fulfill the rapid curing requirement of the thermosetting packaging process on glass fiber reinforced polymers (GFRP) prepreg, a novel fabricating method is proposed in this paper. It packages optical fiber by pouring and brushing the waterborne polyurethane into dry weave GFRP clothes that have bare optical fibers on one side. A special mold with a slot for laying and fixing package materials is designed. The sample with the size of 20 mm × 80 mm × 1 mm is made by adopting the developed mold. The GFRP side of the sample was pasted on the carbon fiber beam with a constant section, and a static loading test was conducted. The strain of the cantilever beam was collected by the packaged distributed optical fiber sensor and demodulated by the OFDR system. According to the Ko theory, the measured strain was converted into the displacement of the cantilever beam. The displacement of the free end of the cantilever beam was compared with the position measured by the machine vision, and the error between the two was small. The experimental results show that the ultra-thin distributed optical fiber strain sensor obtained by rapid packaging can be used for the deformation monitoring of large structures such as wind turbine blades.
Fuzzy Direct Torque Control of Surface Permanent Magnet Synchronous Motor
Authors: Qin Yugui , Wang Kaiyuan , Luo Huiran
Published: December 2022

To solve the problems of large torque and flux ripple in direct torque control (DTC) of permanent magnet synchronous motors (PMSM), a fuzzy controller is used to replace hysteresis comparators and switching tables in the DTC. Different from the conventional fuzzy controller which only outputs the angle or amplitude of the voltage vector, the controller adjusts the angle and value of the voltage vector at the same time in the surface PMSM DTC system is proposed. The inputs and output of the fuzzy controller are: stator flux, torque error, angle and amplitude of voltage vector in stator flux coordinate system. The simulation results of proposed fuzzy control system work normally. Compared with conventional fuzzy control systems, stator flux and torque ripples are decreased and only when motor speed is negative, torque ripple is a little higher. To suppress torque ripple at negative speed, two membership functions of torque error are designed and the fuzzy control system can select the proper membership function according to motor speed. Simulation results show adaptive fuzzy control system can effectively reduce torque and flux ripple in four quadrants.
Integrated Analysis System for Dynamic Sealing Performance of Civil Aircraft Boarding Door
Authors: Zhang Shenghai
Published: December 2022

This paper introduces an integrated analysis system for the dynamic sealing performance of civil aircraft boarding doors. The analysis system mainly carries out virtual verification for the sealing performance of civil aircraft doors in various service environments, including the simulation module of fluid pressure temperature on the surface of aircraft doors. There are three subsystems: hatch fluid-structure coupling interpolation module and hatch dynamic sealing performance finite element simulation module. The system is used to simulate the sealing performance of civil aircraft boarding doors in complex dynamic environments such as under high and low temperatures and high and low pressures. The system can improve the evaluation mechanism of aircraft hatch dynamic sealing performance, and help to build a virtual simulation analysis and test verification system of hatch performance under the interaction of multiple environmental factors, so as to help overcome the bottleneck in the development of civil aircraft in China.
Effect Analysis of Step Input Smoothing Optimization on Hydraulic Excitation Suppression of Position Servo System
Authors: Mao Xuyao , Xiang Chao , Wu Di , Wu Yong , Lai Qiwei
Published: December 2022

Based on step input ramping optimization, a further optimization method is proposed by superimposing a sine signal to smooth the mutation of the step signal. This sine smoothing method has zero signal change rate and acceleration at the beginning and the end of the signal mutation. That is, the optimization has good smoothing characteristics. With the position servo system as the research object, the simulation model is established and the effect analysis of parameters such as rising time, friction, and external load is carried out. It can be concluded based on the analysis that the ramp and the sine smoothing optimizations are very effective in reducing hydraulic excitation, especially in suppressing the pressure pulsation of the system; meanwhile, it would cause a system response millisecond delay. Different optimization methods should be selected according to the specific application scenarios.
An Investigation on the Ground Impact of Electric Vehicle
Authors: Zhao Zhiwei , Liang Wangde , Yang Xiaohang , Cheng Hao , Ma Ying , Ju Hao , Zhang Yaming
Published: December 2022

Ground impact caused by road debris can result in very severe fire accidents of Electric Vehicles (EVs). To improve the mechanical safety of EVs, the test and verification conditions of Bottom scraping and Bottom supporting for ground impact safety of EVs are formulated through market safety accident investigation. Moreover, the assessment method and verification equipment are developed to satisfy the consumer’s demands. The investigations of ground impact show that whether the battery pack is at the lowest point has a great impact on the safety under the Bottom scraping condition, while the material of the Bottom guard plate has a great impact on the safety under the Bottom supporting test condition. Finally, 11 EVs are tested to evaluate the safety performance against ground impact by the scoring rule of multiple indicators. The results provide important guidance for the safety design of the ground impact of EVs.
Study on plant generator scheduling based on mixed integer model
Authors: Yang Jiaqi
Published: December 2022

Due to the outbreak of the new crown epidemic, the production plans of most factories have been affected to a certain extent, and there may be some changes in the production machinery and manpower arrangements of the factories. In this paper, we study how to arrange the dispatch strategy of generators under the condition of power demand in a specified time. Based on the minimum cost, a mixed integer model was established, which provided a solution for some factories to control the scheduling of machines on time during the outbreak of the epidemic. According to the established model, a factory is programmed to solve the problem, and the minimum power generation cost in a week is given 1589130 CNY. In special cases, the working generator set must set aside 20% of the power generation capacity margin to cope with the unexpected situation. At this time, the generator’s daily production cost is as small as 239870 CNY while giving the corresponding generator scheduling scheme. Finally, this paper does a sensitivity analysis of the total daily power generation cost when the power generation margin changes, and finds that the total daily cost of the generator is sensitive to the power generation margin.
Study on bi-layer optimal operation of new energy microgrid with P2G
Authors: Yuan Meng , Zhang Peng , Yuan Meng
Published: December 2022

To improve the utilization of new energy sources and reduce economic costs, a micro-grid dispatching model based on new energy prediction with P2G is proposed. This paper consists of two stages. The first stage is to optimize the model of support vector machine using particle swarm algorithm to predict the data of wind power and photovoltaic power generation based on several influence factors. The second stage is to use the data of wind power and PV output in the first stage and put them into the micro-grid model of this paper for optimal dispatching. This stage is solved by using CPLEX+YALMIP and divided into three scenarios for comparative analysis. The conclusion is that the micro-grid containing P2G has effectively improves the economy and the capacity of consuming renewable energy. The bi-layer optimization of this paper, with the first stage improving accuracy and the second stage optimizing dispatch, not only greatly promotes the smooth and reliable operation of micro-grids, but also reflects the systematic nature of micro-grid modelling.
Research on Optimization Allocation of Aircraft Repair Line Resources Based on BSWPA
Authors: Li Shenshen , Chen Jie , Li Na
Published: December 2022

This paper abstracts the aircraft overhaul operation process into a directed network. Based on the analysis of the network structure, the calculation method of the operation time is given. Under the premise that the total resources and types of resources have been determined, an aircraft repair line resource optimization allocation model has been established to achieve the shortest single-machine repair time and find the optimal quantity ratio of various resources. According to the characteristics of the optimal allocation of aircraft repair line resources, the Binary Smart Wolf Pack Algorithm is used to solve the problems. Finally, the model and solution method are verified by a numerical example.
Research on Automatic Replacement Tool of Linear Insulator for Live Working in distribution network
Authors: Feng Yu , Wu Shaolei , Wu Kai , Wang Bin , Gong Fuxing
Published: December 2022

Aiming at the problems of high risk, high labor intensity, and complex operation processes in the existing manual replacement of insulators, an automatic replacement tool for linear insulators was developed. The device can be used for the quick replacement of linear insulators under live working conditions. Firstly, a mechanical structure with high positioning accuracy and strong stability was designed according to the shape of the linear insulator and the simulation of the artificial live working process. Secondly, the static simulation of the clamping mechanism of the device was carried out. The results show that the strength of the clamping mechanism is high, and the maximum elastic deformation is 4.952 mm, which meets the requirement of the structure design. Finally, the relevant simulation test of the automatic replacement tool was carried out at the operation site. The experimental results show that the designed mechanical structure is light and convenient, which can quickly complete the automatic disassembly, installation, and fastening of linear insulators. The designed mechanical structure also effectively improves the efficiency of maintenance operations and has high promotion and application value.
Traffic analysis of two-layer coupled networks
Authors: Zhang Min
Published: December 2022

Since many systems in the real world are structured and characterized by multilayer networks, more and more scholars have started to investigate the coupling mechanism in multilayer network. In a network, a node’s betweenness centrality reflects the load better than the node degree metric. This paper suggest a new coupling method based on the betweenness centrality of nodes in the network. Connections are made from the middle position according to the order of node betweenness. The results demonstrate that Middle-betweenness coupling makes more even distribution of traffic in the network and an increase in network capacity, as well as an increase in network throughput, compared to Assortative coupling and Disassortative coupling.
Enabling Li3.75Si alloy coupled with Argyrodite Electrolyte with Desirable Performance for All-solid-state Batteries
Authors: Jia Linan , Guo Bangjun , Zhang Xi
Published: December 2022

With excellent safety and outstanding energy density, all-solid-state batteries is of a prospect for surpassing liquid Li+ batteries. Li6PS5Cl, exhibits desirable ductility and good Li+ conduction property, which is the most commonly used solid-state electrolyte. Herein, Li3.75Si alloys have been prepared by high energy milling technology as an anode to couple with NCM811 cathode and demonstrated an outstanding capacity. During the charging/discharging process, a microstructural defect surface was obtained, and a large impedance interface was verified by EIS tests.
Silicon-metal and silicon-metal oxides composite anodes material for lithium-ion batteries
Authors: Chen Xuming , Zhang Hanyi , Zhao Tianhao
Published: December 2022

Lithium-ion batteries (LIBs) with higher specific energy as well as longer cycling performance have been rapidly evolving in recent years. Silicon as a kind of anode material in LIBs is arousing more and more attention owned to its ultrahigh specific energy and abundant supply. However, the pulverization during lithiation and de-lithiation of silicon always causes a considerable reduction in capacity. Several investigations have been carried out to tackle this problem by using silicon composites with nanostructural design. This study focuses on the most recent research on Si-metal alloy and Si-metal oxide composites, which show significant promise for improving the cycle life of LIBs. Their nanostructures will also be examined to propose new research avenues for silicon-based anodes.
Cause analysis of corrosion and burst of water wall of utility boiler
Authors: Sun Yunfei , Chen Hao , Yun Feng
Published: December 2022

During the operation of a boiler in a power plant, the water wall tube burst and leaked. In order to find out the reason of tube rupture, a comprehensive experimental study was made on the sample with macro morphology, chemical composition, metallography, SEM and EDS. The results show that due to the high sulfur content in the combustion medium of the boiler, a large amount of sulfate containing sulfur elements will deposit on the outer wall of the water wall tube during the long-term operation. In the high temperature environment of the boiler, the thermal corrosion of sulfate deposit, that is, high temperature sulphur corrosion, is formed on the side of the water wall wall steel tube, which leads to the continuous thinning of the wall thickness. And finally, explosion leakage occurs under the action of the internal high-temperature and high-pressure medium.
A Reliability Improvement Technology of Transformer Internal Inspection Robot and Its Control System
Authors: Pan YueHong , Wang Lei , Wang XiaoDong , Fu Zhao , Hu Tao
Published: December 2022

The oil-immersed transformer internal inspection robot has played a good role in the inspection of large power transformers, effectively reducing the working intensity of staff and improving the automation level of power equipment inspection. However, in practical work, this kind of internal inspection robot often has various quality problems and a high failure rate. Aiming at the various complex environmental stresses faced by the internal detection robot, this paper analyzes the performance failure mechanism and completes the research on the reliability improvement method of the internal inspection robot and its control system, which effectively improves the reliability of the internal inspection manipulator.
A Flicker Source Location Method Based on Wide-Area Information
Authors: Wei Xiaowei , Li Wanxin , Xu Hao , Zheng Xiaoxiang , Chen Fang
Published: December 2022

The voltage fluctuation and flicker level are important indicators for evaluating power quality. Correct identification of flicker sources can effectively help to improve power quality. To solve the problems of insufficient accuracy and lack of propagation path analysis in current flicker source location research, a flicker source location method based on wide-area information is proposed. Based on the frequency-amplitude binary characterization, the main components of the voltage data from each bus node are used to determine the main frequency of the voltage fluctuation. By comprehensively comparing the voltage data of each node at the main frequency, the flicker source can be located. Simulations in PSCAD/EMTDC verify that the flicker source in the regional power grid is accurately detected and the flicker propagation path is identified by the proposed method.
Reactive Power Optimization of Active Distribution Network with Distributed Generation
Authors: Gong Jianfeng , Han Yiming , Zhang Bin , Jin Panlong , Xu Pengfei , Feng Xue
Published: December 2022

Taking an active distribution network with distributed generation as an example, this paper designs a reactive power optimization scheme for the operation of a power grid to reduce the node loss in the operation of an active distribution network. The objective function of voltage optimization is established with the minimum active power loss as the optimization objective. According to the stable operation requirements of an active distribution network, the constraint conditions for the objective function are designed. The improved particle swarm optimization algorithm is introduced to search the particles in the effective workspace of the distribution network. Optimal position of the particles is located in this way. According to the solution set, a reactive power convergence model is constructed. According to the operation state of the active distribution network, the switching times of power equipment are set. The output value of the distributed generation in the power grid is taken as the reactive power optimization target to realize the distribution network’s dynamic reactive power optimization. Taking a large power generation enterprise in the pilot area as the research object, the application experiment is designed. The practice proves that this approach can act in reducing the loss of the distribution network.
Application of Support Vector Machines for Breast Calcification Cluster Detection and Mass Classification
Authors: Huang Yucheng , Chen Guangshun , Chen Jiyun , Li Dalin , Liang Yanchun , Du Wei
Published: December 2022

Breast cancer has become “the most common cancer worldwide”, and it is an urgent problem in the medical field to improve the detection rate of breast cancer through early diagnosis and treatment. Based on the current research on medical image processing, our work selects breast images from the MIAS database for pre-processing, segmentation, texture feature extraction and classification, and conducts an in-depth investigation and experimental validation on the theoretical basis of support vector machine algorithm, kernel function selection, and key parameter optimization. The results show the effectiveness of support vector machines in detecting abnormal areas and classifying masses in breast images and provide research ideas for breast cancer diagnosis.
Epilepsy Detection Method Based on the Time-gated Feature Network
Authors: Wang Xiaoli , Jin Yuanshang , Han Qiuyue , Cui Jie , Lin Zechuan
Published: December 2022

Epilepsy is a nervous system disease, which is caused by abnormal discharge of brain neurons. The clinical manifestations are generalized seizures, clonus, loss of consciousness, and shock. An electroencephalogram (EEG) can accurately capture the changes in EEG activities. Therefore, EEG signals are used to detect seizures. In this paper, an epilepsy detection model based on a time-gated feature network (TFGN) is proposed. Firstly, the original EEG signal is preprocessed, and the preprocessed signal is sent into the TFGN detection model which integrates feature extraction, feature selection, and classification to obtain the detection results of epilepsy. Through the verification of data from different ages and channels, the detection accuracy of the TFGN detection model is higher than that of the traditional detection model, and the validity and comprehensiveness of the TFGN detection model are verified.
A Fourier Ptychographic Microscopy Reconstruction Method Based on SwinIR Physical Model
Authors: Wang Xiaoli , Piao Yan , Jin Yuanshang , Li Jie , Han Qiuyue , Yu Jinyang
Published: December 2022

Fourier ptychographic microscopy (FPM) computational imaging is a newly developed microscopic computational imaging technology in recent years, which can realize large field-of-view (FOV) and high-resolution microscopic imaging. In this paper, the SwinIR physical model is introduced to solve the problems of a slightly long reconstruction time and poor reconstruction effect of the FPM reconstruction algorithm based on physical learning. Different from the traditional CNN network structure, this physical model completes the reconstruction of images by introducing modular design and feature fusion. Through a series of simulation experiments on ideal images and real images, it is proved that the reference physical model has better reconstruction quality than the comparison algorithm.
Lightweight Task Coordination of LEO Satellite Cluster based on Distributed Reinforcement Learning
Authors: Qin Junxiang , Li Xuan , Ma Xiaotian , Yang Jun
Published: December 2022

Low earth orbit (LEO) mega-constellation is in the stage of rapid construction, which is expected to serve more regions and apply to more scenarios, such as regional navigation enhancement, emergency communication, collaborative detection, etc. For such typical regional tasks, the construction of temporary LEO satellite clusters is an effective way to improve the quality of temporary services. However, LEO satellites move too fast, and relying on ground-based manual control can no longer meet the mission requirements. The cluster task coordination based on reinforcement learning can effectively improve the autonomous performance of the cluster, but it is difficult to apply to satellites, especially LEO satellites with extremely limited resources. Based on this, this paper proposes a lightweight collaboration method for LEO satellite constellation based on distributed reinforcement learning, which optimizes resources on the premise of ensuring the independent realization of task requirements. In this paper, the Q-learning reinforcement learning algorithm is used to compare the performance of the centralized Q-learning algorithm and distributed AC algorithm. The experiment of the star cluster cooperative detection task shows that the convergence time of the proposed algorithm is 81.5% less than that of the centralized algorithm, and it can run on embedded raspberry pi. It shows that the algorithm is expected to be applied to cluster task coordination of LEO satellites.
Accuracy Analysis of Oblique Photogrammetry Measurement in 3D Modeling of Power Line Selection Design
Authors: Liang LiHeng , Yang ZhenGuo , Wang YaGuang , Jia GaoYi , Sun BaoZhong
Published: December 2022

The measurement of power line selection in the field is one of the key works of route design. The traditional manual measurement is inefficient, and ground objects are prone to losses and leakage, often resulting in frequent line changes. With the promotion of 3D real scene work, power line design has also entered the 3D era. In this study, taking the line design near Dengtai Village in Dalian as an example, the UAV is used to carry a multi-viewer camera to obtain three-dimensional information on the ground surface. The power supply line is generally selected in the field far away from residential areas. The characteristics of weak texture bring certain difficulties to the Oblique photogrammetry method. A few control points and checkpoints are arranged to control the accuracy of the ground model, and the accuracy analysis and evaluation are carried out. The results show that the UAV Oblique photography technology has obvious advantages in the process of three-dimensional model construction. The maximum errors of the model result in X, Y, and Z directions are -0.1820 m, -0.1200 m, and -0.3860 m, respectively, the mean square error in the plane is ± 0.0595 m, and the mean square error in elevation is ± 0.2198 m. The 3D model accuracy can meet the actual needs of 1:2000 mapping, thus verifying the feasibility and reliability of the UAV Oblique photography technology to build a high-precision real scene three-dimensional digital model in the application of power line selection measurement.
Refinement Bilateral Segmentation Network for Semantic Segmentation in Traffic Scenes
Authors: Lin Xin , Sun RongChun
Published: December 2022

Semantic segmentation technology in traffic scenes can help vehicles make accurate analyses and positioning of the road ahead. In traffic scenarios, the trade-off between real-time performance and the accuracy of semantic segmentation is particularly important. This paper proposes a lightweight deep convolutional network, which can be applied to traffic scenes to complete accurate semantic segmentation tasks, considering both real-time performance and accuracy. The Cross Channel Attention Fusion Mechanism proposed in this paper can better integrate the context information and improve accuracy. The Depth-wise Separable Pyramid Module proposed based on the feature pyramid idea can improve the segmentation accuracy and effectively trade off the real-time performance.
Fourier Ptychographic Microscopy Reconstruction Method Based on Residual Transfer Networks
Authors: Wang Xiaoli , Piao Yan , Li Jie , Yu Jinyang
Published: December 2022

Fourier ptychographic microscopy reconstruction mostly adopts the traditional alternating iterative phase recovery method and optimization method, which has high computational complexity, high redundancy of image acquisition data, low reconstruction quality and high time consumption. In this paper, the model of residual transfer networks based on Resnet152 is proposed for Fourier ptychographic microscopy reconstruction, the learning process of deep convolution neural network is introduced, and the image reconstruction method based on deep learning realizes the end-to-end reconstruction of low-resolution images to high-resolution images. Through comparative experiments and analysis, the residual network can overcome the gradient explosion, make the feature information more complete and efficient, and the incremental up-sampling reconstruction network has higher image quality, lower computational complexity and shorter running time.
Design and Implementation of an Imaging System Based on the sCMOS Sensor
Authors: Rong ZhiWei , Chen Lei
Published: December 2022

sCMOS sensor has broken through the technical bottleneck of high noises and low quantum efficiencies of traditional CMOS sensors. It has the advantages of high sensitivity, high dynamic ranges, low dark current, low readout noises, low power consumption, and high integration, and has gradually become the preferred detector for low-noise imaging systems. Therefore, this paper developed an imaging system with high sensitivity, a high frame rate, low noises, and low power consumption based on a sCMOS sensor. The system adopts a sCMOS image sensor GSENSE400BSI which is very suitable for the requirements of low noises and a high dynamic range in the scientific imaging field as the photosensitive element and XILINX SPARtan-6 FPGA as the control core. Two pieces of high-speed DDR3 are configured to realize ping-pong cache of image data. In the thermal vacuum experimental verification, the total power consumption of the imaging system in the imaging mode is less than 2.2W, and the temperature rise of the sensor is less than 0.1°C. During the in-orbit verification, the imaging system runs stably and the imaging status of the system is good. It has achieved effective monitoring of space targets and high-energy ray bursts and other astronomical phenomena. The image indicators meet the application requirements of commercial space-based telescopes.
Research on the Construction Method of Driving Conditions with Optimal Deviation Based on Fuzzy C-Means Clustering
Authors: Liu Dongmei , Zhang Jianqiang , Li Xuejun , Quan Linfei , Hu Xiaodong , Xing Kefan
Published: December 2022

To construct a driving condition that conforms to the actual situation, this paper firstly removes, interpolates, and smooths the original data, and obtains several kinematic segments according to the division standard of kinematic segments. Then, extract the feature parameters and analyze the principal components of the kinematic segments obtained by division, and retain the principal components that can describe most of the features. Finally, the FCM clustering method is used to analyze the retained principal components, and the congestion, relative congestion, and relative unblocked and unblocked conditions are obtained. Finally, the comprehensive driving conditions are synthesized by the deviation optimization method, and their rationality and scientificity are verified by simulation analysis.
Dual-flow Spatio-temporal Separation Network for Lip Reading
Authors: Huang An , Zhang Xueyi
Published: December 2022

Lip reading is a task of predicting the corresponding language information in a silent video, which has attracted a lot of attention in recent years. Its key is to capture temporal and spatial features from lip motion videos and decode them. In the past, lip reading methods based on deep learning mostly adopt the form of spatio-temporal series connection, which first extracts spatial features, and then carries out global time-domain modeling on this basis. The spatial information extracted by the current approach is insufficient. To get more abundant spatio-temporal video representation and fully integrate the features from different viewpoints, this paper proposes a novel lip motion feature extraction framework, Dual-flow Spatio-temporal Separation Network (DSSN). Specifically, we adopt an end-to-end double tower structure to model the temporal information and spatial information respectively, and carry out feature fusion through collaborative learning. Finally, we evaluate our proposed model on the OuluVS2 lip reading dataset. Experiments show that our method outperforms baseline models.
Study for Identity Losses in Image-to-Image Domain Translation with Cycle-Consistent Generative Adversarial Network
Authors: Liu Sizhe
Published: December 2022

The effect of identity loss in image-to-image domain translation using generative adversarial networks (GAN) remains largely uncertain given its wide application in many successful GAN architectures, e.g., CycleGAN. In this study, negative identity regularization and idempotence regularization are identified from several related studies, and a novel loss, positive identity loss which limits the generative model’s output on the input of positive samples from the source domain, is defined. Results from identity regularized GANs and those without are compared and analyzed. This study concludes that: 1) negative identity loss is helpful in regularizing CycleGAN’s tendency to apply inversible but non-identity transform on non-features such as coloration and background landscapes; 2) positive identity loss significantly increases resolution, details, and affinity with the original image on top of negative identity loss; 3) idempotence loss has positive but limited impacts on output image quality.
Research on Road Condition Sensing Technology based on Vision and Radar Information
Authors: Guo Yishan , Li Mingqiu , Li Mingqiu
Published: December 2022

In the process of intelligent vehicle driving, due to the complexity of the environment, a single sensor or multiple homogeneous sensors cannot completely perceive the traffic environment around the intelligent vehicle. Therefore, it is necessary to study the information fusion scheme of different sensors and make use of the advantages of each sensor to make up for the deficiency of a single sensor, so as to realize the function of cooperation and mutual compensation between multiple sensors. In this paper, millimeter-wave radar and camera are selected as sensors for an intelligent vehicle to sense the environment ahead. Firstly, in the case of time and space synchronization of the two types of signals, fusion based on the cross-ratio of detection frames is used to find the region of common interest of radar and camera for fusion. Then the fusion based on data association is adopted. The experimental results show that the method based on radar and camera data can effectively realize accurate target recognition and location, and can meet the requirements of real-time accuracy in the application of intelligent vehicles.
Research on UAV target detection and substation equipment status recognition technology based on computer vision
Authors: Yi Liu , Xin Yuchen , Chen Zuodong , Lin Jianwei , Liu Xiaowei
Published: December 2022

The use of computer vision-related technologies can more efficiently achieve target detection of UAVs and accurately identify the status of substation equipment. Therefore, this paper proposes research on UAV target detection and substation equipment status recognition technology based on computer vision. Taking key technical links such as image preprocessing based on computer vision technology, image feature extraction, and construction of UAV target detection coordinate system as breakthrough points, realizing UAV target detection work lays a solid foundation for the identification of substation equipment status. It lays the foundation and promotes the scientific and effective identification of the status of substation equipment. It provides a guarantee for improving the accuracy of UAV target detection and promoting the efficient and stable identification of substation equipment status.

CLC number: TN919.8 Document identification code: A.
Human Pose Estimation: Multi-stage Network Based on HRNet
Authors: Ji Xiaodong , Yang Qiaoning , Yang Xiuhui , Zheng Jiahao , Gong Mengyan
Published: December 2022

Multi-stage network uses stacked networks to enhance the feature extraction capability, and can gradually refine the keypoints with the information of previous stages’ output. Obviously, multi-stage networks are more suitable for human pose estimation. However, most current multi-stage networks use a codec structure as the backbone in which downsample will cause information loss. HRNet maintains high-resolution features to supply the information which is lost in down-sampling stage. In this regard, we propose a novel two-stage network with HRNet as the backbone and stacked codec structure. HRNet has more efficient feature extraction capability, and the stacked codec network can utilize the multi-scale features generated by HRNet more effectively. This method obtains a 1.2AP improvement compared to HRNet and a significant improvement compared to other two-stage networks.