bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three-dimensional visualization of secondary system based on digital twin
Authors: Gan Xing , Xiong Zaibao , Du Shaofei , Wu Zhongcheng , Geng Xiaohong , Gao Yu , Guo Yi’nan 
Published: August 2021

Abstract
The digital twin technology has become mature and has entered the stage of popularization and application, but the research on digital twin technology of substation secondary system has not been carried out systematically. This paper provides the idea of digital twin digital analog integration application of secondary system, which realizes the information interconnection of three-dimensional model, loop relationship model and transmission data model. Through the correspondence between physical model such as optical cable and field reality, the physical loop information and corresponding virtual loop information can be viewed more intuitively. Combined with the multi-dimensional data-driven model technology, the correlation information of the secondary physical loop and the logic loop is dynamically displayed in 3D visualization, to provide technical support for the operation and maintenance.
Least squares support vector machine for state of charge estimation of lithium-ion battery using gray wolf optimizer
Authors: Wang Qiao , Ye Min , Wei Meng , Wu Chenguang , Ma Yuchuan 
Published: August 2021

Abstract
An accurate SOC estimation can ensure the effective and normal operation of the battery. To this end, a method for estimating the SOC of lithium-ion battery based on least squares support vector machine (LSSVM) is proposed, and the gray wolf optimizer (GWO) algorithm is used to further optimize the model parameters to overcome the non-linearity and unevenness of the actual working condition. Influence of interference factors, and then obtain accurate SOC estimation results. The optimized LSSVM is verified by collected data at different temperatures, the results shows the proposed optimization model is greatly improved compared to before optimization, the model accuracy is improved by about 35%.
Active power improvement of three-phase grid-connected inverter under unbalanced grid faults
Authors: Zhang Ye , Tian Muqin , Song Jiancheng 
Published: August 2021

Abstract
Unbalanced grid voltage causes fault-phase over-current, affects the life span of devices and even leads to control system instability. The conventional current limiting strategy reduces the output power of grid-connected inverter. In order to increase the active power injected by the grid-connected inverter into the grid, this paper proposes a new current limiting strategy. On the premise of ensuring that the DC side voltage fluctuation and grid-connected current harmonics meet the grid standards, the fault-phase current and the normal phase current are respectively limited. The simulation results verify the proposed strategy can effectively improves the active power output of the grid-connected inverter.
Design of voltage stability monitoring simulation system for PV grid-connected system
Authors: Li Sheng , Cao Zhiyang , Cui Jian , Yu Jiawei , Bao Wenqi 
Published: August 2021

Abstract
Voltage stability monitoring simulation system for photovoltaic (PV) grid-connected system is designed, taking the classic three-node power system model with a PV power station for example. The voltage instability theory and application researches for the monitoring simulation system are carried, and the frame, communication protocol and software functions of the voltage stability monitoring system are discussed. The monitoring simulation system can realize two-computer communication and joint debugging, which can not only monitor the basic operational aspects, but also be used to view the voltage equilibrium point curves and voltage response curves as the operating point is affected by various disturbances. And the system load margin index calculation, load shedding and other voltage stability remote control methods are provided to maintain or improve voltage stability. The monitoring simulation system provides a reference scheme for the application of voltage stability theory in practical engineering.
Design of Ka-band broadband low-noise amplifier using 100nm gate-length GaN on silicon technology
Authors: Zou Yu , Chen Zhijian , Lai Junkai , Li Bin , Wu Zhaohui , Lin Xiaoling 
Published: August 2021

Abstract
Due to the high breakdown voltage and better linearity of gallium nitride (GaN) high electron mobility transistor (HEMT), GaN based RF front-end is widely researched and studied. In this paper, a Ka-band cascode low-noise amplifier (LNA) designed with 100nm gate-length GaN-on-silicon technology is presented. With novel methods such as the introduction of high-pass filters and standing wave filtering capacitors, the LNA achieves a stable gain of 21-22.8dB and a noise figure (NF) of 0.9-1.3dB from 22GHz to 38GHz. The input and output return loss are better than-10dB in band of concern. This LNA occupies an area of 2.3mm × 0.9mm and consumes 265-mW DC power. Compared with silicon-on-insulator (SOI), indium phosphide (InP) and gallium arsenide (GaAs) LNAs, the proposed GaN LNA exhibits better performance of linearity, as well as competitive gain and NF.
Improving the cam profile of the spring operating mechanism of vacuum circuit breaker based on energy matching
Authors: Li Fuqiang , Wang Shufen , Li Yuguang , Sun Zhenzhen 
Published: August 2021

Abstract
High-voltage circuit breakers are important protection and control equipment in power systems. In order to understand the mechanical characteristics of vacuum circuit breaker, the mathematical relationship between the released energy of closing spring, the stored energy of opening spring and overtravel spring and the rotation angle of output crank arm is studied. The characteristic curve between the released energy of closing spring and the rotation angle of output crank arm and the characteristic curve between the stored energy of opening spring and overtravel spring and the rotation angle of output crank arm are drawn by MATLAB. In order to improve the matching of energy release and energy storage characteristic curves, a method of improving cam profile is proposed. The dynamics simulation model of spring operating mechanism of high voltage circuit breaker is established and the original cam and adjusted cam are imported into the dynamics simulation model of mechanism. The simulation results show that the adjusted cam improves the closing speed of vacuum circuit breaker. This helps to reduce the stress on the parts of the vacuum circuit breaker and increase the service life of the vacuum circuit breaker.
A double closed loop control algorithm based on current mode in full bridge circuit
Authors: Xu Chengbo , Chen Jing , Li Zhihua , Xiao Chun 
Published: August 2021

Abstract
In order to improve the problems of large output current and voltage ripples and slow system response when the full-bridge circuit is working. This paper proposes a double closed-loop control algorithm based on current mode. Use fuzzy controller to optimize the parameters of voltage outer loop PID controller. The genetic controller is used to optimize the parameters of the current inner loop PID controller. After the dual closed-loop structure of the current control mode is optimized for the traditional PID controller, the overshoot is reduced, the system response speed is accelerated and the current ripple and voltage ripple are also greatly reduced. The simulation verifies the effectiveness of the designed double closed-loop control algorithm.
Kinematics analysis of transmission mechanism of electronic jacquard machine based on virtual prototype and vector method
Authors: Guo Shuai , Zhang Chi , Wu Xiaoguang , Zhang Chengjun 
Published: August 2021

Abstract
Aiming at the problem that the electronic transmission mechanism of the electronic jacquard machine is difficult to design, a kinematic analysis of the mechanical transmission mechanism of the electronic jacquard machine is proposed to clarify the kinematic performance of the electronic transmission mechanism. Based on the vector method, the kinematics mathematical model of the mechanical transmission mechanism of the electronic jacquard machine was established, and the matrix of the displacement, velocity and acceleration curve of the pulling blade was obtained. After the parameters are selected, the correctness of the mathematical model is verified through virtual prototype modeling and simulation. Through simulation analysis and verification, it is found that the numerical calculation results of the solution matrix are consistent with the simulation results of the virtual prototype model, and the peak error does not exceed 0.42%, which provides a certain theoretical basis for the study of electronic jacquard transmission mechanism.
Application of smart substation site management system based on 3D digitization
Authors: Xiong Zaibao , Gan Xing , Li Yunwei , Ding Ding , Geng Xiaohong , Gao Yu 
Published: August 2021

Abstract
In order to standardize the construction of smart construction site of substation, meet the requirements of observable, measurable and controllable whole process of project technology, safety, quality, progress and procurement, and realize the goal of lean management and control, this paper expounds the concept of smart construction site from four aspects: Framework Construction of smart construction site, platform and module construction of smart construction site, mechanism construction and pilot application. This paper puts forward an overall scheme of smart substation construction site based on 5g technology, which combines big data, artificial intelligence, state perception and video recognition technology to solve the multi-dimensional management requirements of safety, quality and progress during construction. The intelligent site visualization platform is established and integrated with 3D model to realize 3D visualization display of site information.
Research on factors influencing the positioning accuracy of four-quadrant detector
Authors: Li Dongkang , Zhang Yanmei 
Published: August 2021

Abstract
In order to analyze the positioning accuracy of the four-quadrant detector, this paper deeply studies the positioning principle of the four-quadrant detector, establishes the mathematical model of azimuth standard deviation based on Gaussian facula, and deeply analyzes the influence of each factor on the positioning accuracy from the three influencing factors of facula position, facula radius and signal-to-noise ratio. The results show that the positioning accuracy can be effectively improved by improving the signal-to-noise ratio, using smaller light spot and making the light spot as close to the center of the detector as possible.
Research on application of tower sharing in overhead transmission line in China
Authors: Zhang Zhuoqun , Tao Hanxun , Wen Weibin , Tian Weiguang , Liu Quan 
Published: August 2021

Abstract
As a social public infrastructure, overhead transmission lines were mainly used to transmit high load electrical energy and communication information. It was an important lifeline project, and had the characteristics of extensive spatial distribution, large number, and safe operation and so on. Transmission lines had a certain technical reserve and good feasibility in shared tower technology, in line with the communication and sensing industry of shared application and development. The results demonstrated that shared transmission line can support the application of different OPGW cables, acre station and micro base station for multiple vendors, and different sensing devices. It was showed very good economic benefit and social benefit in different shared application scenarios.
Research on DC side power decoupling control of photovoltaic inverters
Authors: Zhu Longji , Wang Shuying 
Published: August 2021

Abstract
Inverter is a vital component in photovoltaic power generation system, and it is related to the performance and efficiency of photovoltaic power generation. When the inverter is connected to the grid, the instantaneous power on the DC side and the AC side is unbalanced, and the instantaneous power pulsation of double frequency will be generated on the DC side, which directly affects the current stability and power utilization rate of the inverter on the DC side. This paper proposes a Power Decoupling Circuit (PDC) based on a single-phase photovoltaic inverter. This circuit uses a closed-loop feedforward power decoupling control strategy to compensate for the unbalanced pulsating power on both sides of the inverter. Eliminate low-frequency harmonics on the DC side, achieve the purpose of power decoupling, stabilize the DC side voltage of the photovoltaic inverter, and improve the performance and efficiency of photovoltaic power generation.
Analysis and evaluation of short-term wind power interval forecast error based on K-means clustering
Authors: Li Songshan , Ma Zhicheng , Zhang Xiaoying , Wang Kun , Zhou Qiang , Zhang Jinping , Chen Wei 
Published: August 2021

Abstract
The intermittency, volatility and randomness of wind power will inevitably affect the accuracy of wind power prediction. In order to improve the accuracy of wind power interval prediction and evaluation, a method of wind power interval prediction and evaluation based on K-means clustering is proposed. First, use K-means clustering to classify wind power prediction error data; second, combine the climate type to more accurately divide and process historical data, and apply multiple linear regression models to establish preliminary prediction models corresponding to each subset; Finally, according to the distribution characteristics of forecast errors, the results of wind power forecasting are analyzed and evaluated with interval coverage and interval average bandwidth as indicators. Comparing the K-means clustering algorithm with the BP neural network algorithm, the results show that the method proposed in this paper can better capture the characteristics of wind power error data, and can obtain more accurate wind power interval prediction and evaluation results.
Study of overtaking method of intelligent vehicle under vehicle road coordination
Authors: Wang Yifei , Yin Kaiyang 
Published: August 2021

Abstract
Aiming at the safe overtaking in the autonomous driving of the intelligent vehicle, the overtaking method of intelligent vehicle under vehicle road coordination is advanced. First, according to the current vehicle movement state and the surrounding environment, the overtaking behaviour decision is proposed. Second, with the support of vehicle-road collaboration technology, the principle of the overtaking method is analysed. The position and speed of the associated vehicles within the real-time range are collected with the Road Side Unit (RSU). The RSU communicates with the autonomous vehicle in two-way, and vehicle selects overtaking behaviour. Finally, the validity of this method is verified by the cases, the overtaking method includes overtaking in the borrowing lane, the extended overtaking lane and the emergency lane. The research results of this study not only provide a basis for the method of the safe overtaking in the process of the intelligent vehicle autonomous driving, but also lay a foundation for the intelligent transportation system (ITS).
Quality spectra fluctuation modeling for manufacturing process based on deep transfer learning
Authors: Hu Sheng , Li Zhe , Zhang Shoujing 
Published: August 2021

Abstract
It is difficult to characterize and monitor the quality fluctuation caused by multi-correlation parameters in manufacturing process. Motivated by the powerful ability of digital images to characterize process states, this paper presents a quality spectra fluctuation modeling method based on deep transfer learning. Firstly, through the multi-parameter correlation of spectra pixels, the quality spectra is constructed to characterize quality fluctuation. Then, a deep residual network transfer learning model is used to identify the types of quality fluctuation. Finally, the effectiveness analysis of proposed model is demonstrated by the Tennessee Eastman process.
Analysis and application of manufacturing data driven by digital twins
Authors: Gao Xiyu , Liu Peng , Zhang Qixun , Gao Dawei , Huang Xin 
Published: August 2021

Abstract
This article introduces the importance of data processing to the production process and the application of data in the digital twin workshop. Then the overall process of data processing is introduced. First, several typical data acquisition methods are listed, feed the collected data to the digital twin model, and then extract the model data for integration and convert it into the same XML text format. Perform data cleaning and data analysis on it, and then use the DBN in deep learning to extract and classify the data to complete the real-time matching and transmission of production information to employees. Finally, the future development direction of the data analysis will be briefly summarized.
Research on evaluation of intensive economic benefits of equipment manufacturing enterprises
Authors: Wu Huiyuan 
Published: August 2021

Abstract
Intensive economic benefit is the result that the total factor productivity is improved by improving the utilization efficiency and combination quality of asset elements and human elements, and the increased output exceeds the total input of asset elements and human elements. In order to analytical study of smart manufacturing level and intensive economic benefit, by taking Liaoning Equipment Manufacturing Enterprise as the research object this paper establishes production function model and total factor productivity model of relationship between input and output of Liaoning Equipment Manufacturing Enterprise. Meanwhile by establishment grows model of total factor productivity it realizes measure of smart manufacturing level and intensive economic benefit of Liaoning Equipment Manufacturing Enterprise. Final by contrastive analysis total factor productivity and increase economic efficiency of contribution rate of equipment manufacturing enterprise this paper puts forward feasible countermeasures and suggestions to increase total factor productivity and realize intensive management of Liaoning Equipment Manufacturing Enterprise.
Research on wind turbine system reliability modeling and preventive maintenance policy considering performance degradation and shock
Authors: Li Haiyan , Li Yaping , Chen Zhen 
Published: August 2021

Abstract
With the development of the wind turbine industry, the operation and maintenance of wind turbines has gradually become one of the main concerns of the wind turbine industry. In view of the wind turbine system’s vulnerability to external environment, this paper considers the performance degradation and external shocks of the unit to establish a reliability model and develop preventive maintenance policy. First, Markov chain is used for degradation modeling, and unit is divided into different health states; Homogeneous Poisson process is used for shock modeling, assuming that the shock is cumulative. The impact of shocks on unit degradation was described as the unit in different states had different state transition matrices, and then establish the state reliability. According to the state probability of the unit, formulate the corresponding preventive maintenance policy. Finally, a generator in a wind turbine system is taken as an example, the influence of external shocks on unit performance degradation is explained. Meanwhile, the preventive maintenance strategy proposed in this paper is compared with the maintenance policy with fixed maintenance threshold, and the advantages of the reliability model and maintenance strategy proposed in this paper are illustrated.
Integrated modelling of automobile maintenance expert system based on knowledge graph
Authors: Liu Gen , Hong Ge , Huang Mengdie , Xia Tangbin , Chen Zheng 
Published: August 2021

Abstract
Using online information resources to build knowledge bases to provide knowledge answering services would help auto companies or third-party platforms to gain competitive advantages. Therefore, a construction plan of automobile maintenance expert system based on knowledge graph was proposed by integrated modelling. In terms of the entity recognition algorithm, the BM LSTM (Boyer-Moore Long Short-Term Memory) algorithm was proposed by integrating hidden Markov model, Conditional Random Field (CRF), Bi-directional Long Short-Term Memory (BiLSTM), BiLSTM-CRF and Lattice LSTM, which improved the accuracy index F1-score. In terms of the text quality evaluation algorithm, a secondary text quality evaluation system was designed. It evaluated the matching quality of the problem based on the word toolkit Synonyms and Levenshtein Distance algorithm. And it evaluated the quality of the answer text based on the TF-IDF (Term Frequency-Inverse Document Frequency) similarity algorithm and centered on completeness, accuracy, reliability, and argument strength. Finally, experiments are carried out on the proposed model and algorithm to prove its effectiveness.
Prospects for Power Systems with High Proportion of Renewable Energy Considering the Coordination of Source-grid
Authors: Ling Xu , Yu Haiyang , Wang Yuan , Wu Yaowu , Liang Shuhao , Hu Zhigang 
Published: August 2021

Abstract
In the future, the spatiotemporal distribution of a high proportion of renewable energy will bring unprecedented challenges to power system, and the basic form and operation of power system will have great changes. On the basis of investigating the research status in China and abroad, this paper expounds the scientific problems faced by the planning of Power Systems with High Proportion of Renewable Energy (PSHPRE) considering the coordination of source-grid, and put forward the basic ideas and framework of research from four aspects: overview of the development of PSHPRE, power planning in PSHPRE and coordinated planning of source-grid in PSHPRE. Finally, the prospects for Power Systems with High Proportion of Renewable Energy considering the coordination of source-grid are presented.
A Comparison of Top-down Load Forecasting and Bottom-up Load Forecasting in Distribution Network
Authors: Mu Zeyu , Hayinaer  , Tueraili  , Song Bin 
Published: August 2021

Abstract
In this paper, the electricity load of a certain region is taken as the research object. Firstly, the back propagation neural network (BP) model is used to predict the macro load of the region from top to bottom. Then, on the premise of comprehensive consideration of the region’s meteorological, economic, large user registration and other causes, the power grid of the region is divided. On this basis the differential integration moving average autoregressive (ARIMA) model is used to carry out the bottom-up micro load forecasting: First, the load forecasting of each cell is carried out, and then the prediction results are summarized in proportion to obtain the overall prediction results of the region. Through the comparative analysis of the two load forecasting results, it is found that although the two forecasting errors are fewer than 9%, the bottom-up load forecasting method which combines grid partition and fine classification has a prediction error of fewer than 5 %. The results show that the bottom-up load forecasting method is better.