bluuebunny/crossref_metadata_2025 huggingface dataset:
Method for Identifying Global Structural Risk Bottleneck of Regional Rail Transit Based on Sensitivity Analysis
Authors: Li He , Dong Wei , Sun Xinya , Sui Tao
Published: November 2020

The characteristics of multi-standard rail transit systems coexistence of regional rail transit increase the risk probability of rail transit network. At the same time, the interaction between multi-standard systems and the integrity of the rail transit network increase the risk impact area and the risk consequences. Therefore, the risk bottleneck identification for regional rail transit is of great significance to realize targeted protection and optimization of key risk points and effectively reduce the global risk of the transportation system. In view of the fact that the existing risk assessment methods of rail transit network mostly use index fusion, which cannot reflect the global structural risk and cannot effectively evaluate the global risk bottlenecks of the rail transit network, this paper proposes a method for identifying global structural risk bottlenecks of regional rail transit based on sensitivity analysis. First, an assessment index for the global structural risk of the rail transit network is established, and then sensitivity analysis is used to assess the impact of the failure and optimization of station or section on the global structural risk of the rail transit network, so as to provide decision support for the protection and optimization of the rail transit network risk bottlenecks. Finally, the regional rail transit in Chengdu-Chongqing area is taken as an example to verify the effectiveness of the method.
Piggery Ammonia Concentration Prediction Method Based on CNN-GRU
Authors: Wang Kai , Liu Chunhong , Duan Qingling
Published: November 2020

The ammonia concentration in piggery has a great impact on the healthy growth of pigs and breeding environment. It is of great significance to control the ammonia concentration in piggery and ensure the healthy growth of pigs by timely mastering the ammonia concentration variation trend. In order to predict the ammonia concentration in piggery, a method based on CNN(Convolutional Neural Networks) and GRU(Gated Recurrent Unit) was proposed. Firstly, the environmental data in piggery and the meteorological data outside were collected, fused and preprocessed. Then, a piggery ammonia concentration prediction model combined with CNN and GRU was established. As a result, the ammonia concentration in piggery was predicted. The result shows that the proposed method has good prediction performance. The MSE (Mean Square Error), RMSE (Root Mean Square Error) and MAE (Mean Absolute Error) is 0.0637, 0.2524 and 0.1845, respectively. The proposed method can provide support for the early warning and regulation of piggery environment.
Study on Deformation Failure Mechanism and Control Measures of Toppling Slope
Authors: Zheng Huifeng , Wu Guanye , Chen Yi , Ju Nengpan
Published: November 2020

Aiming at the large range and depth of toppling and cracked deformation occurred in a typical toppling slope during the excavation in Miaowei hydropower station on the Lancang River, through geological survey, the classification standard system for toppling deformation rock has been established based on the main characteristic indexes of rock mass, and the mechanism of the toppling and tensile deformation of the slope at Miaowei is revealed. Comprehensive rescue reinforcement measures were implemented to control the development of deformation and to maintained the stability of the slope, which included prestressed anchorage and systematic drainage. Numerical simulation was implemented to predict the deformation and guide the reinforcement. The numerical and monitoring results both show that the deformation has been effectively controlled and the slope is already in a stable state with the completion of reinforcement measures. The study on the deformation mechanism and the successful practice of treatment of typical toppling slope in Miaowei hydropower station provide a constructive reference for similar complicated slopes.
Temporal and Spatial Characteristics of Climate Dryness in Eastern Qinghai Province
Authors: Jing Yuanshu , Cudemus Leila , Chen Xuejiao
Published: November 2020

Agrometeorological drought is the most important meteorological disaster that restricts the development of agricultural areas in the east of Qinghai Province. It is very important to evaluate the climate dryness by studying its temporal and spatial characteristics. Based on the long-term meteorological data of 12 meteorological stations, the temporal and spatial distribution of precipitation and dryness in the study area was analyzed. The dryness degree of each year varied greatly, ranging from 1.5 to 3.1, showing a trend of increasing with time. The dryness of the study area was relatively small in the three months of July, August and September, and larger in the period from November to March. The intensity of drought in the middle of the study area is higher than that in other areas, while the duration of drought in the south is longer. The drought tendency rate of the 12 weather stations was - 30.962/10a. The results help to provide reference for spring wheat planting to cope with spring drought.
Risk Assessment of Snow Disaster in Guoluo Prefecture of Southern Qinghai Province Based on GIS
Authors: Lv Chenqing
Published: November 2020

We evaluated snow disaster risk in 44 towns of Guoluo Prefecture by combining the methods of Analytic Hierarchy Process (AHP) and cluster analysis. Data were gathered from meteorological stations in Qinghai and Sichuan Provinces with GIS and RS tools. We considered snow depth, the duration of snow days, the area ratio of snow as three indicators for such evaluation, we can say Guoluo Prefecture is a higher hazard area of snow disaster. From the spatial distribution, we can see that the mild grade areas are Huashixia town in Maduo county, Zhalinghu village and Dongqinggou village, Lajia town in Maqin county; the moderate and minor severe grade areas are distributed basically in every county. And the minor severe grade areas cover almost every town in Dari county and Gande county However, the severe grade areas only distribute in Sanrima village, Tehetu village of Dari County and Dangluo village of Maqin county.
Face Recognition Based on Deep Learning of Small Data Set
Authors: Yu Lichun , Liu Jinqing
Published: November 2020

Face recognition based on deep learning relies on large-scale label data, which limits the application of face recognition technology. To solve this problem, this paper proposes an improved VGGNet algorithm for face recognition. The improved algorithm requires less training data size, faster training speed, and the face recognition rate reaches more than 95%, which can meet the practical application requirements of most scenes.
An Hybrid Parallel Network Structure for Image Classification
Authors: Li Muhan , Jin Yijian
Published: November 2020

The image classification task is to divide certain image target into the specific class which they belong to. The deep neural network simplifies image classification by sending input image data into the neural network to learn feature extraction and having the output results automatically. Existing network structures have been able to achieve or exceed human capabilities in image classification tasks. However, these image classification technologies still have problems such as over-fitting network model, insufficient generalization abilities and long convergence time. Interference caused by complex environments may also cause the performance degradation. This paper proposes a hybrid parallel neural network structure for this kind of artificial intelligence task. By adopting the K-parallel connection CNN structure and using different scales of RNN/CNN structure mixed-layer modes, the effects of image’s size on different objects and different shooting angles can be reduced in image classification. Experiments on the datasets show that the proposed structure will have the advantage of accuracy and computational efficiency both in the validation datasets and the test sets.
Infrared Imaging Principle of the Front of the Vehicle
Authors: Zhou Zhen , Wang Yiwen , Gong Jianchun , Liu Lei
Published: November 2020

In recent years, with the progress of science and technology, infrared imaging is widely used in commercial and military, provide convenience for people’s life, the car in front of the infrared imaging improved the car in the way of low visibility in the form of security. Through the analysis of infrared imaging principle, this principle is applied to automobiles, and a simple infrared imaging system is designed for automobiles. This system is applied to the car to reduce the danger of the car in all kinds of bad environment and weather, and improve the driving safety of the car owner
A Study on the Composition and Communication of Chinese Character Images under the Context of Digital New Media
Authors: Liu Lin , Wang Yudi
Published: November 2020

Under the context of digital new media, the paper deals with the composition and dissemination of Chinese character images from three perspectives: the structure and communication of the character images, the presentation of character images and the modes of communication. Due to the computer technologies, Chinese characters could be presented on the screen with both pictures and sounds and become more intuitive and realistic. What’s more, the light effects and dynamic technique feature prominent in forming visual images of Chinese characters. In a word, the computer technologies help to realize the multi-dimensional and dynamic presentation of Chinese characters.
Geometric Drawing Method for Form-finding and Force-finding to Triangular Prism Tensegrity with End Surfaces not Paralleled
Authors: Shang Renjie , Zhao Yicheng , Yin Zhiqiang
Published: November 2020

The triangular prism tensegrity with arbitrary triangle bottom and end surfaces not paralleled is the most common type tensegrity structure. A geometric drawing method with four steps’ process for form-finding was given based on the properity of tensegrity structure, and the degree of freedom for form-finding was analysied. The force-finding method with ten steps’ process was given after form-finding, and the self-balancing internal forces was obtained by measuring the lengths of correspondant line segements. The geometric drawing method was carried out in CAD software by an example, and the example tensegrity structure obtained by the method was analysed by finite element method software, the correctness of the method was verified. The form-finding method is the geometric implementation of the force density method, and the process is intuitive and controllable, it is suitable and operational for triangular prism of tensegrity structures of any shape.
Alice: A LSTM Neural Network Based Short-Term Power Load Forecasting Approach in Distributed Cloud-edge Environment
Authors: Ding Zhengyang , Wang Jijun , Cheng Yiqing , He Chengxun
Published: November 2020

Load forecasting, as the baseline for decision-making, plays a key role in the management and control of the grid. Nevertheless, the rapid evolution of the smart grid has brought a dramatic increase in the volume of user-side data, traditional load forecasting approaches have to face the challenge of ensuring the accuracy of dynamic forecasting under the circumstance of the widespread application of big data. Meanwhile, the advance of the Industrial Internet of Things (IIoT) enables smart meters to acquire more plentiful data, which improves the accuracy of short-term load forecasting with appropriate utilization, but the gradual increase in the magnitude of data brought by IIoT technique has also left the computing equipment under great pressure. To address these challenges, in this paper, a Long Short-Term Memory(LSTM) network based short-term load forecasting approach deployed in the distributed cloud-edge environment, named Alice, is devised to deliver more precise results for the smart forecasting of power load. It adopts the LSTM network to perform the forecasting tasks and extends the whole system to the cloud-edge platform to implement parallel neural computing. Moreover, the Toeplitz Inverse Covariance-Based Clustering (TICC) algorithm is invited to enhance the efficiency of LSTM. Eventually, experimental evaluations on real dataset elaborate the superiority of the proposed Alice approach when compared to other state-of-the-art approaches.
Research on Optimization of Boiler Air Distribution System based on Deep Neural Network
Authors: Yuan Jun , Ren Xinyu , Xie Yingbai , Li Zhichao
Published: November 2020

The boiler air distribution system has an important influence on the stable operation of the thermal power unit. It directly affects the combustion efficiency, which in turn affects NOx emission of the boiler. However, boiler efficiency and NOX emission are a pair of contradictory goals, which will be one-sided if one is adjusted separately. In addition, thermal power units often face the impact of variable boundary conditions in operation. In this study, DNN-PSO modeling optimization was performed on air distribution system of a 1000MW double-tangential boiler. The deep neural network (DNN)is used to establish the boiler’s air distribution system model, and the particle swarm optimization algorithm (PSO) is used to optimize the opening of the secondary air baffle and the over fire air baffle. According to the on-site adjustment test based on the optimized guidance value, the NOX emission was reduced by 36.31mg/Nm3, and the boiler efficiency was increased by 0.09%, which proved the feasibility of using this model to guide the operation of the boiler air distribution system.
Measurement of Train Rim Thickness by Machine Learning
Authors: Song Bing , Wei Haiping , Cao Yu , Cheng Xu , Guo Xiwang
Published: November 2020

The train wheel rim thickness is always manually measured by using handheld devices or in a non-contact way by using laser and image techniques. To reduce the operating costs, this work studied some soft measurement methods with classical machine learning algorithms including neural network (NN), locally weighted linear regression (LWLR), and support vector machine (SVM). By analyzing the correlation between features, it can improve the efficiency of the model. Some approaches were used to optimize the number of hidden layer neurons in NN, parameters in LWLR and SVM. Experiments on real data are conducted, and the results show that the proposed methods can ensure high precision and accuracy, while NN has the highest accuracy.
Overall Framework Design of Integrated Manufacturing Center of Underground Laser Rapid Prototyping for Aeroengine Components Based on Cloud Computing and Internet of Things
Authors: Lv Xiaodong
Published: November 2020

This paper displaces an antiaircraft defence multi component integrated aeroengine manufacturing system which is designed for fast supply and timely repair of aeroengine in wartime. The robust control architecture is based on the global control of cloud computing and super expansion of the neural terminals of the Internet of things by fog computing. In order to improve the purpose of the whole system, we set up a system which can produce a variety of aeroengine components by the fog computing node with high autonomy. This relatively independent production system can receive intermittent commands from the cloud processor. For most of the time, each relatively independent laser rapid manufacturing unit runs the manufacturing task in the weak command environment. It only needs to send a decision from the cloud processor on the model and quantity of the aeroengine to be produced, and mark the changed parts with special requirements. Command encapsulation and encryption are carried out at the interface of the middle layer, and then sent down to the physical layer and the fog computing layer to realize macro command decryption and the production sequence of this batch of aeroengine production tasks configured to different number of laser manufacturing units.
A Lattice Attribute-Based Encryption Scheme for Cloud Storage Based on R-LWE Problem
Authors: Lu Sa , Jiang Rui , Pei Bei , Wu Songyang
Published: November 2020

Attribute-Based Encryption (ABE) is generally applied on Cloud Storage to ensure the security and efficient access control of uploaded data. However, with the development of quantum computing, Diffie-Hellman Problem and Discrete Logarithm Problem, which all ABE scheme based on, have been solved. Therefore, anti-quantum ABE schemes become a research hotspot. However, current anti-quantum ABE schemes cannot make attribute revocation. In order to solve these problems, we propose a lattice attribute-based encryption scheme for cloud storage based on R-LWE problem (L-ABE). Firstly, we construct public/secret key pairs based on the hardness of Ring Learning with Error problem (R-LWE) to achieve quantum attack resistance effectively. Secondly, our scheme can achieve attribute revocation to ensure fine-grained access control. Finally, we prove that our scheme can resist chosen plaintext attack.
Research on the Construction Scheme of Jiangsu Taihu Intelligent Tunnel Based on Cloud Platform
Authors: Lu Yi , Liu Yuchen , Meng Chunlei , Wang Xinke
Published: November 2020

Taihu underwater tunnel in Jiangsu province is an ultra-long and ultra-wide tunnel, both longer and wider than the Hong Kong-Zhuhai-Macao bridge. It is worth discussing how to guarantee the safety of underwater tunnel, give play to the application of intelligent transportation, make travellers get all-round comfortable service and managers get economical and efficient management. Starting from the cloud platform and taking Taihu tunnel as the background, this paper analyses the status quo of the tunnel at home and abroad, draws lessons from experience, and studies the structure and functions of the construction scheme of Taihu intelligent tunnel from the perspective of “safety, comfort and economy”.
Smart Wireless Wearable ECG to Measure Heart Function
Authors: Mamunur Rashid Md , Bakar Siddique Abu , Zhang Zhou , Li Zeyu , Li Zhangyong
Published: November 2020

Healthiness is one of the over-all contests for people. Modernized healthcare system is to furnish better healthcare services to human beings at any time, from somewhere and at any locations in a financial and pleasant manner: very beneficial and easy. By using mobile phone, healthcare device can be made on hand for all people, even for those dwelling in far-flung areas the usage of smartphone except a whole lot access to other kinds of communications. This proposed system graph is to measure and display essential ECG records for a correct description of fitness repute and fitness. Developments in exclusive wearable factors and assemblies, as nicely as in communication technological statistics have spread out for a new technological know-how of health care systems.
Analysis and Design of Intelligent Management and Control System for Relay Protection Based on Information Fusion Technology
Authors: Liu Yang , Zhu Wenqiang , Li Lisheng , Guo Jiang
Published: November 2020

Combined with the current problems of the large number of professional systems for relay protection and the inability to collaboratively share data. This paper analyzes the current application of relay protection information systems. Through analysis of four key relay protection systems including OCS (Operation Control System), Protection and Information System, Wave Recording System, and Traveling Wave System, the core technical parameters are sorted out, and the XML-based (Extensible Markup Language) data specification and model fusion method, introduced the overall architecture of the information fusion relay protection intelligent management and control system, and designed the application function of the intelligent management and control system to realize the information fusion and intercommunication of multi-source heterogeneous systems to improve Power grid coordinated control and emergency response capabilities.
Preliminary Analysis on Strategies of Experimental Design for Traditional Commercial Spaces in the Background of Internet Economy
Authors: Ma Hui , Zou Guangtian
Published: November 2020

Currently, the progress of economic globalization, informatization and networking is driven by the rapid development of the Internet economy. Advantages of the Internet economy such as low costs and high efficiency have resulted in a tremendous shock to traditional commerce, and a rapid decline in traditional retail. How to restrain such declining tendency? This paper has dissected discrepancies between Internet economy and traditional commerce, and their advantages and disadvantages are dissected in this paper, and the results emphasize that experience-based space designs must be applied to traditional commercial spaces in order to enhance the real experience of commodities. This paper presents how to make good experience-based space designs for traditional commerce under Internet economy, and puts forward experience-based design strategies from four aspects of situational participation, theme-based construction, personal experience of roles and emotional penetration. It is aimed at creating an experience-based commercial space with complementary advantages for online and offline commerce, integrated functions, diversified business patterns, and a comfortable consumption environment, as well as modern characteristics, through analysis and introduction of these four strategies.
Research of Virtual Reality Technology in Home Design
Authors: Phommaly Khamla , Yu Lasheng
Published: November 2020

This paper mainly discusses the application of virtual reality technology in home design. Through virtual reality technology, we can have more realistic experience and switch freely in each space, so that customers can feel the future home personally. Built by importing household design, real 3D model, combined with the virtual reality modelling language (VRML) generated with interactive link the prototype of the object, to quickly build furniture design based on the technology of web 3D virtual reality display system. System combined with rich interactive methods, adjust and contrast design, advance awareness the real effect of household is decorated, improve customer satisfaction; Combination scheme design, the system can also be used for virtual simulation practice. Engineering practice proved that the system development is simple, high efficiency and can greatly accelerate the household decoration engineering design schedule and save time cost, and has high value in engineering practice. This article provides a new Angle of view to parse the virtual reality technology in the application of home design
The Comparison Discussion on the Controlling Effect of Parasitic Accelerations Generated by Human Centrifuge by Different Controlling Methods
Authors: Li Yifeng , He Bin , Li Baohui , Jiang Ke , Wang Cong , Jin Zhao , Zhang Lihui , Wang Yi , Wei Xiaoyang , Wang Quan , Wang Haixia , Yang Jinghui
Published: November 2020

When simulating acceleration of pure Gz direction, when precision requirement of centrifuge Gz direction is provided, the max values of parasitic accelerations permitted to occur in other directions such as Gx, Gy directions are also provided in the meantime. The research is on account of motion pattern of three axial human centrifuge, introduces Euler recursion method and trapezoid method, designs computer simulations of different smoothing number of times and smoothing time on account of Euler recursion method and trapezoid method and compares simulation results, that is the controlling effects of parasitic accelerations generated by human centrifuge when making the simulation of pure Gz by the two controlling methods. Result shows: the two methods both can restrain the values of parasitic accelerations of x and y directions with effect, and torque demanded by system decreases after smoothing acceleration curves. Compared to Euler method, the computing amount of trapezoid method is larger, while the eliminating effect for parasitic accelerations is better, and it makes computing accuracy of result be higher. The study result can be as the important reference resource when selecting and researching controlling methods of the parasitic accelerations generated by human centrifuge.
Study on the Performance of Nuclear Security Basic System against Nuclear Electromagnetic Pulse
Authors: Cheng Jinxing , Wen Weiwei , Wu Youpeng , Wang Qingbo , Lu Xin , Chen Xianbo , Wu Yuhong , Fu Beihuang , Liu Qing , Qin Feng , Mao Congguang
Published: November 2020

With the extensive application of nuclear technology and the improvement of emergency forewarning level for nuclear terrorism, it is urgent to study the performance of nuclear security basic system against nuclear electromagnetic pulse. In this paper, a basic nuclear security system is designed, and the weak link of the nuclear electromagnetic pulse is analyzed and simulated. In addition, the weak link is tested through experiments. The theoretical analysis is in good agreement with the experimental results. The results of this paper can provide technical support for the reinforcement of nuclear security system against nuclear electromagnetic pulse.
Design and Implementation of Fully Integrated Automation Scheme Based on Heterogeneous Field-bus Network
Authors: Yan Xiaoling , Wang Liming , Yin Yang , Ouyang Jineng
Published: November 2020

In view of the current situation of coexistence of various fieldbus protocols, the paper presents an totally integrated automation scheme based on Ethernet. The Ethernet technology can integrate the information of different field devices in the enterprise, and realize the unified data management, communication, programming and configuration. The paper systematically expounds the concept of totally integrated automation, realize totally integrated automation scheme based on Ethernet communication technology by designing protocol conversion gateway and applying to serial server. The solution is very suitable for information integration in enterprise, as the information exchange is realized at the device level, and the hardware design costs low.
Research on the Control Method of UPS Inverter Circuit Considering Additional Filtering Branch
Authors: Liu Guofu , Liu Ximu , Wang Weiwei
Published: November 2020

Improving the electric power quality of the Uninterruptible Power Supply (UPS) is an important part of ensuring the reliability of the power system. In order to optimize the output voltage waveform of the UPS, a filtering branch can be added to the existing UPS inverter circuit. This paper studies the circuit control problem after adding the RLC filter branch in the UPS inverter circuit. Through the analysis of the inverter circuit directly considering the added filtering branch, the system state function of the circuit is constructed. A double closed-loop PI control strategy is designed to control the inverter circuit, and the effectiveness of the method is verified by simulation. Using the method in this paper, the output of the inverter circuit with the added filter branch can reach a stable state quickly. The research conclusions of this paper are helpful to improve the output power quality of UPS.
Reliability Assessment Method of Complex Electronic Equipment with Multivariate Competing Failure
Authors: Jia Zhanqiang , Yang Jianyong
Published: November 2020

This paper presents a generalized reliability assessment model for complex electronic equipment with multivariate competing failure. The key of multivariate competing failure model is separated into two parts, multi-degradation measure probability density function (MDM-PDF) and traumatic failure reliability function (TFRF) related to degradation level. Principal component analysis is used to solve the calculation problem of MDM-PDF; Logistic function and least square method are introduced to solve the problem of TFRF. Finally, a case study of sine-wave oscillation circuit is given to validate the effectiveness of the model.
Generalization of Convolutional Neural Networks for Searching for O-Star Spectra Using Generative Adversarial Networks
Authors: Zheng Zipeng , Qiu Bo
Published: November 2020

In the stellar spectral data released by LAMSOT, the O-star spectrum is very rare, and the total amount of O-star spectra that can be utilized is only 156. We recommend generating a simulated real spectrum to overcome the above limitations. Using the real O-star spectrum as the model spectral image, we propose a one-dimensional spectral generation confrontation network (1D SGAN) to create artificial spectra based on real data sets. We use a combination of real and artificial spectra to train a one-dimensional convolutional neural network (1D CNN) to create a classifier that classifies the stellar spectra into seven categories. We demonstrate that using the proposed balanced data set with 1D SGAN generated images improves the performance of the 1D CNN classifier compared to the same 1D CNN trained with only the original data set.
Soft Sensor Simulation of Minimum Energy Consumption of Joint Manipulator Drive System Based on Improved BP Neural Network
Authors: Ding Yunpeng , Zhu Xuejun , Sun Xuqiang , Zhang Ji , Chen Xu
Published: November 2020

The energy dissipation level of articulated mechanical arms directly affects the control stability of industrial robot systems. For a six-degree-of-freedom articulated robot driven by a DC servo motor and reduction gear, based on the Hamiltonian and Minimum theories, a model of the articulated manipulator drive system under load torque is established, and the expressions of optimal angular velocity and control current are obtained considering the viscous friction and coulomb factors. According to the analysis of actual parameter simulation experiments, it can be seen that the energy consumption of the joint manipulator drive system increases with the decrease of efficiency, the increase of the coulomb friction torque of the servo motor, and the increase of the load torque. Within the transit time, the total energy consumption of the drive system is smaller, so it is very important to obtain the transit time within the optimal area for the minimum energy consumption of the joint robotic arm drive system. At the same time, a soft neural network model based on the improved BP neural network built on the neural network toolbox for the energy consumption of the articulated mechanical arm is established. Finally, the experimental platform of servo motor drive system is built and used for the experiment of servo motor drive, and the purpose of closed-loop control is also achieved. Through experimental analysis, it can be seen that the proposed soft sensor model of joint minimum energy consumption based on improved BP neural network can more accurately realize the energy consumption prediction under unknown angular displacement and unknown load, and provide a theoretical basis for joint energy monitoring.
Study on Laminated Bus Bar for High-pulse Power Converter Module
Authors: Yin Binchuan , Du Litian , Peng Junrong
Published: November 2020

Aiming at the problems of high switching overvoltage of power semiconductor devices and unbalanced current of parallel power devices in high-pulse power converters, this paper proposes a laminated bus bar of symmetrical path on the basis of the theoretical analysis and key points of laminated bus bar. The finite element simulation software was used to analyze the stray inductance of laminated bus bars. The actual stray inductance and overvoltage of the converter commutation circuit were measured by single pulse experiment. The results show that the laminated bus bar of symmetrical path can effectively reduce stray inductance, suppress switching impulse overvoltage and improve the current balance of the parallel power devices. It is of great significance to analyze the performance of laminated bus bar of symmetrical path, and it can be used for high-pulse power conversion technologies.
Communication Specific Emitter Identification Based on Transfer Learning
Authors: Liu Hui , Hu Pengjiang , Liu Zhen
Published: November 2020

In the application of specific communication emitter identification(CSEI), the emitter slight features will change along with different times, places and conditions, which makes training samples and test samples obey different distribution and makes most machine learning algorithms not work well. To solve this problem, this paper introduced transfer learning to CSEI. Compared with traditional machine learning, transfer learning does not relax the assumption that the data is independent and distributed. It can explore useful knowledge from the data which is different from the target domain but similar to the source domain. It can also learn the classifier when the labeled samples in the same domain are insufficient. Extensive experiments show the effectiveness of the new method.
Inertial Navigation Method of Spacecraft Based on Geodesic Deviation Equation
Authors: He Zhenni , Fei Baojun , Du Jian
Published: November 2020

A new method of spacecraft inertial navigation is proposed in paper. The method uses the earth gravitational field model and the on-board accelerometer to measure data, so the real-time deviation of the spacecraft relative to the geodetic orbit is calculated. Based on the post-Newtonian approximate gravity theory of general relativity, the high precision geodesic deviation equation around the earth is derived, and the equation of the spacecraft relative to the geodesic orbit is transformed into orbital element space. The position of the spacecraft is determined by calculating the deviation between the spacecraft and the nearest geodetic orbit. Because the reference points are selected different in the adjacent following inertia system during navigation, the accumulation error of the traditional inertial navigation is avoided, and the navigation precision can be effectively improved.
The Strategy of Personal Customization and Method of Collecting Professional Dynamic Information
Authors: Li Bohan , Cai Yongxiang , Deng Shuying , He Zongyi
Published: November 2020

The need for personal customization in professional dynamic information collection requires crawling information that is published within specified time durations, extracting accurate and interest-focused information, and assuring the completeness of the information. By combining the technology of jsoup and Lucene as well as the extensibility research on Heritrix, this paper proposes a set of personal customization strategies and methods for professional dynamic information collection: analyze the composition of the URL link to filter out information beyond a specified time window according to different URL types; set up different cleaning templates to extract the attribute items for different styles of websites; establish user personalization blacklist to filter out the information with poor relevance to user interests; apply correction function to improve the robustness of the crawler and guarantee the completeness of the information. Using the collection part of the Dynamic Information Collecting System of Oil and Gas Resources project as a case verification, the results show that the strategies and methods can be used to achieve the three objectives: timeliness; accuracy and interest-focus; and completeness. The proposed strategies and methods may be applied to the construction of an industrial dynamic information collection system.
Quality Analysis and Research of Charging Facilities for Electric Vehicles
Authors: Wang Jiaojiao , Wei Qianqian , Li Chuan , Li Yang
Published: November 2020

With the development of new energy vehicles in recent years charging infrastructure industry is also in rapid development. In this study, to analyzethe the quality of charging infrastructure in its service life cycle, enterprises of charging facilities were visited and charging stations were researched on-site.This study also analysed the evaluation system, discussed the limiting factors in the process of charging infrastructure development.In this study, the quality development direction of future charging infrastructure is defined, and data support is provided for the high-quality development of charging infrastructure.
The Manufacture of GaN Powder in Plasma
Authors: Li Yafeng , Yang Wenzhi
Published: November 2020

In this paper, the preparation technology of GaN powder has been studied by using of plasma powder synthesis system, and several properties were improved such as: the morphology, the particle size, structure and optical properties. The result shows that, by applying for plasma method, high purity GaN powder was manufactured; the GaN has a good morphology and a regular spherical shape. The spherical ratio of the GaN powder was more than 95%; The GaN powder can be adjusted with different process parameters to achieve particle size control; The GaN powder has sharp diffraction peak and good crystallinity; The GaN powder has the structure of wurtzite and good luminescent properties.
Anti-plane Response of a Dike near Bi-material Interface to SH Waves
Authors: Ri Songchol , Wang Shuhong , Jang Paeksan , Wang Yue
Published: November 2020

In the present work, we study the scattering of SH waves by a dike embedded near the interface of bi-material half space. For this, a simple model is utilized to discuss the response of a dike near the interface. Complex function method, image principle, region-matching technique and Green function method are introduced to obtaine the total displacement fields along the free surface of the dike. The results are presented graphically considering the different material parameters. The results show that the displacement along the dike is greatly dependent upon the properties of bi-material interface.
Research on Coordination Control Strategy of LCC-MMC Hybrid HVDC Transmission System under Fault
Authors: Zhang Mingguang , Liu Zilin , Yang Chengming , Chang Jianhua
Published: November 2020

High voltage direct current based on modular multilevel converter (MMC-HVDC) has a good application prospect in engineering, but it is expensive and cannot handle DC faults and other disadvantages. So it is still not suitable for long-distance transmission. To solve these problems, this paper designs multi-terminal hybrid DC transmission system with a line commutated converter based on the rectifier side (LCC) and a modular multilevel converter based on the inverter side (MMC). Besides, for the asymmetric fault on the AC side of the system, the minimum trigger angle control strategy based on the rectifier side LCC and the maximum modulation ratio control strategy based on the inverter side MMC are proposed to improve the DC system transmission power and reduce the possibility of power transmission interruption. Finally, a model of hybrid DC transmission is built in PSCAD/EMTDC, the proposed strategy is verified its effectiveness.
Research on the Fault Location Method of Double-terminal MMC-HVDC Transmission Line without the Influence of Wave Velocity
Authors: Zhang Mingguang , Yang Chengming , Liu Zilin , Chang Jianhua
Published: November 2020

Due to its own advantages, MMC-HVDC transmission system has been widely used in power transmission and grid connection. According to the existing double-terminal traveling wave fault location method of MMC-HVDC transmission lines, a double-terminal traveling wave location method is proposed, which is not affected by wave velocity. The wavelet transform is performed on the voltage traveling wave signals at both ends to determine the time when the traveling wave reaches both ends of the line, and the distance of the fault point is calculated. It effectively reduces the influence of the uncertainty of traveling wave velocity on the positioning results and improves the positioning accuracy. The simulation of PSCAD and Matlab software proves the effectiveness and correctness of the method.
Research on Operation Control Strategy of Multi-Voltage DC Microgrid
Authors: Wang Jinhao , Chang Xiao , Li Shengwen , Zhang Ying , Li Huipeng , Wang Xu , Wang Tan
Published: November 2020

In order to reduce the use of power electronic devices, adapt to different loads connected to the DC microgrid, and improve the reliability and safety of power supply, this paper proposes a multi-voltage level DC microgrid control strategy. The basic structure and operation mode of multi-voltage level DC microgrid are introduced. The control strategies of photovoltaic power generation and hybrid energy storage are proposed. The model of bidirectional DC/DC converter is established and the control strategy of hierarchical control of DC bus voltage is proposed. A power balance control strategy is proposed for AC/DC bidirectional power converter to realize smooth AC-DC power transfer. Simulation analysis on Matlab platform verifies the feasibility of the control strategy.
Failure Rate Model of Electric Equipment Based on Meteorological Environment
Authors: Song Chen , Zhao Yan , Xue Kaijin , Li Yucai
Published: November 2020

With the development and progress of equipment status monitoring and fault diagnosis technology, the status maintenance based on equipment status evaluation is gradually popularized and applied. By monitoring the quantity of equipment state and diagnosing the equipment state, a reasonable method of equipment state evaluation can be used to determine whether the equipment needs maintenance or not. This paper proposes a method of power equipment failure rate model based on meteorological environment. This method firstly uses the fuzzy c-means algorithm(FCM) to conduct fuzzy clustering of meteorological environment sequences in the historical sample data and forecast meteorological sequences in the maintenance period. Then, on the basis of clustering analysis, the grey relational degree analysis is carried out on the same kind of meteorological feature sequence, so as to obtain the power equipment failure probability with meteorological conditions in the maintenance period. The results show that the proposed method can more accurately calculate the failure probability of the equipment, and it is of practical significance to reduce the influence of maintenance on the reliability of power grid operation.
Application of Blockchain in Energy and Power Business
Authors: Xue Zhen , Pan Xiaoting , Lv Zitong , Liu Tao
Published: November 2020

As a decentralized, open, transparent, fair and peer-to-peer distributed database technology, blockchain has the technical characteristics of anti-counterfeiting, anti tampering, traceability and efficiency improvement, which had attracted the attention of many industries including energy and power industry. This paper first analyzed the pain points such as data security sharing, power transaction security and power transaction mode and so on, in current energy and power business, expounded the role of blockchain in solving the above business pain points. Then designed an application framework of blockchain in power business, and illustrated power transaction and supply chain finance to describe the application of blockchain. Finally, prospected the application prospect of blockchain in power industry.
Research and Application of Power Grid Control System Based on Blockchain
Authors: Xuan Jiaxing , Zheng Shangzhuo , Lv Zitong , Du Yuexia , Pan Xiaoting
Published: November 2020

This paper systematically proposes a grid control method and application model based on the blockchain. The control platform system adopts a national-provincial two-level deployment scheme (the control system is a multi-node deployed cloud system). This method treats both the national cloud system and the provincial cloud system as nodes in the blockchain. The national cloud system is the leading role of the blockchain and is responsible for the maintenance of the entire network model structure and the update and release of smart contracts. When the model structure or data of any node changes, the provincial system synchronizes the information and updates the local model data. Each block stores the node’s model operation information (addition, deletion, modification, etc.) according to the time series. According to the information on the chain, the entire network model (node data) can be traced at any time.A blockchain-based model control system that treats both the national system and the provincial system as blockchain nodes. Through smart contracts, a model data chain containing the entire network model and model maintenance “ledgers” is created, and each node can synchronize information and obtain data in real time. Model data, across the entire network and at any time, can be traced through the “ledger”, which not only ensures data security and credibility, but also can be used for analysis, mining and business development. This method has good technical innovation and business practicability.
Simulation Study of the Influence of Stray Current on DC Bias of Power Transformer
Authors: Zhang Jingzhuo , Song Xinming , Xiao Li , Chen Long , Wu Guoxing , Cui Yuzhong , Lai Zhenyu , Li Qiyuan
Published: November 2020

The running of subway rail transit can generate stray currents. This is a current that causes severe corrosion of the buried metal near the subway, and also generates DC bias, which affects nearby power transformers. There are few studies related to the influence of DC bias created by stray current on power transformers. This makes it difficult to determine the impact of subway rail transit on the DC bias of nearby power transformers. To explain the effect of stray current on the DC bias of the power transformer, the characteristics, master sheets of stray current and the principle of DC bias of stray current are analyzed, and a power transformer model of stray current generating exciting current is established. The harmonic components in the stray current are simulated and analyzed. The simulation results show that the track insulation aging caused by subway operation will generate stray current, which will flow into the grounding grid and cause DC bias of the neutral grounding transformer, and then make the transformer core saturated. The amplitude of harmonic component and excitation current will increase with the increase of stray current.
Current Stress Optimisation Strategy for Three-phase Dual Active Bridge Converter during the Start-Up Process
Authors: Chen Guofu , Mu Xiaobin , Wang Xiang , Jiao Honglin , Hao Ruixiang , Zhu Wu
Published: November 2020

Three-phase dual active bridge (3p-DAB) converter is widely used in high-power bidirectional power transfer applications, due to its unique high power density and easy implementation of soft switching. In this paper, the start-up process of the 3p-DAB converter is studied. The cause of high current stress, especially in the case of heavy-load start-up is analysed, and a new start-up control strategy for the start-up process is proposed. The control strategy is helpful to reduce the current stress of the transformer and the switches by adjusting the duty-cycle and the phase shift angle coordinately without adding any other hardware circuits. Finally, based on a TMS320F28377D + XC6SLX25 controller, a 30kW 3p-DAB converter prototype with input voltage 650-750V and output voltage 400-500V is developed to verify the effectiveness of the proposed start-up strategy.
Design of High-Speed Quaternary D Flip-Flop Based on Multiple-valued Current-mode
Authors: Wu Haixia , Bai Yilong , Li Xiaoran , Wang Yiming
Published: November 2020

A new type of quaternary D flip-flop based on multiple-valued current-mode is presented for high-speed sequential circuit in VLSI systems. It employs master-slave mode and dynamic multiple-valued source-coupled logic. A distinguishable multiple-valued interval, fast switch speed and compact structure are obtained by combining source-coupled logic with differential-pair circuit. The performance evaluation is carried out with HSPICE using 0.18μm CMOS process. A performance comparison with those issued in some references is conducted. The delay in our design is about 74% reduced by comparison with the corresponding binary implementation. The circuitry proposed is simplicity, regularity, and modularity, so well suited for VLSI implementation. Quaternary logic seems to be a potential and feasible method of high-performance VLSI systems.