bluuebunny/crossref_metadata_2025_split huggingface dataset:
Establishment and Analysis of Passingness Evaluation Index of off-Road Vehicle Based on PCA
Authors: Xu Rundong , Wang Wei 
Published: March 2020

Abstract
The cross-country passing ability of vehicles refers to the ability to pass complex terrain and soft ground with a certain average speed under rated load.For quantitative investigation off-road vehicle through indicators, this article from the perspective of the terrain, the first seven terrain factors determined by access to information, the second of ASTER GDEM elevation data to spatial analysis, get 7 class data, finally using the principal component analysis (PCA) to 7 kinds of terrain factor has carried on the correlation analysis and factor analysis, reflect the off-road vehicle is established evaluation index of complex terrain through sexual - integrated terrain index Tr.The results show that the comprehensive terrain index Tr can account for 87.623% of the total variance of the original variable, and can integrate a single terrain factor.
Research on Temperature Calculation Method of Electrical Equipment Based on IR Data Compensation
Authors: He Dongxu , Zhang Shi , Chen Liming , Ying E , He Long , Yang Na , Zhang Ruiming , Xia Minglei , Liu Hefeng 
Published: March 2020

Abstract
The real-time monitoring of electrical equipment temperature is a work worthy of in-depth study. In this paper, based on MLX90640 chip, the temperature calculation method of electrical equipment based on IR data compensation is studied, and the necessity of IR compensation is proved by the experimental data results before and after IR compensation. The advantages of this method are proved by the measurement results of MLX90640. The calculation method of electrical equipment temperature in this paper provides a certain guarantee for the safe operation of electrical equipment.
Non-intrusive load monitoring and power quality optimization technology of major power customer basing on RFID
Authors: Zhang Jiaming , Cheng Yingying , Du Jie , Zhou Feng , Xiao Ji , Chang Shiliang 
Published: March 2020

Abstract
The upgrading of industry and manufacturing industry has put forward higher requirements on the economy and reliability of electricity consumption, this situation urges the major power customers to pay more attention to optimize their power quality. For this purpose, this paper proposed Non-intrusive load monitoring and power quality optimization technology of large power customer basing on RFID, from the viewpoint of the comprehensiveness and integrity of power quality optimization, realized non-interve monitoring of main electrical equipment and transformer, further researched optimization method of power quality on major power customers, and formulated detailed implementation strategy. The correctness and validity of the proposed results were verified via field tests.
Reliability Study of Wind Turbine Power Converter with Multiple Wind Speed
Authors: Zhang Jingxuan , Sun Hexu , Lv Dianshun , Dong Zhiran , Gao Ziang 
Published: March 2020

Abstract
Power converter is a significant device in the wind turbine systems (WTS). This paper proposes a novel reliability evaluation strategy for the power converter of wind turbine with multiple wind speed, which named discrete state probability analysis method. Using the data of a wind farm wind speed and ambient temperature in Zhangcheng area of Hebei province. In addition, including the parameter of the wind turbine generator and the power converter. The results show that the reliability of the wind turbine power converter is affected significantly by multiple wind speed. The effect of the proposed method is demonstrated by the calculating example.
Study on the Effect of Coupling Materials on the Ultrasonic Signals Detection of Partial Discharge
Authors: Li Jie , Shi Wei , Zhang Pipei , Wang Peng , Wang Jiangwei , Yan Shisong , Si Wenxu 
Published: March 2020

Abstract
This paper studied the effect of different coupling agents on ultrasonic detection of partial discharge. Water-based ultrasonic coupling agents, medical coupling agents and silica gel coupling materials were compared with commonly used high-vacuum silicone greases to analyse the different response by using different coupling materials to detect the ultrasonic signals with different frequency and amplitude. It is found that the ultrasonic sensor has a better response when applied to medical coupling agents under the frequency 20kHz and 80kHz, the frequency response is better when applied to water-based ultrasonic coupling agents under the frequency 20kHz, 40kHz and 80kHz,but the both two coupling agents have the disadvantage of low viscosity. The frequency response under 40 kHz of sensor is better than other frequencies when applied to silica gel, but this material has the difficulty to achieve full coupling. The high-vacuum silicone gel with higher viscosity is preferred in the consideration of different application scenarios in the field. The silicone gel with the thickness of 0.5mm is also well recommended when the sensor is fixed by an external magnetic base and meet the test accuracy.
Peak Load Forecasting for Electrical Bus based on Limited Historical Data under Complex Meteorological Condition
Authors: Zhu Heyan , Yu Changyong , He Qingkui , Song Kun , Liu Jingbo , Xu Yanlu , Lu Tianqi 
Published: March 2020

Abstract
The historical data of peak load for electrical bus are limited and fluctuated violently. The fluctuation ability of peak load for electrical bus is nonlinear and randomly. So its prediction accuracy is low. In order to improve the accuracy of peak load forecasting for electrical bus, a peak load forecasting for electrical bus method based on limited historical data under complex weather conditions is proposed. Firstly, the influence of natural meteorology, society and other factors on peak load fluctuation for electrical bus is analysed; Secondly, based on the reduction of redundancy between features of potential feature set, the feature importance ranking is obtained by conditional mutual information (CMI). Then, according to the improved particle swarm optimization extreme learning machine suitable for small sample training, the forward feature selection is performed to determine the optimal feature subset. Finally, based on the optimal feature subset, the optimal peak load forecasting model is established.
Multi-source partial discharge detection and rapid localization of switchgear based on comprehensive diagnosis method
Authors: Wang Jianxin , Zhang Zhichong , Zhang Zhaoguang , Si Wenxu 
Published: March 2020

Abstract
Partial discharge detection is an effective method to find potential insulation defects in switchgear. At present, the switchgear is mainly composed of busbars, circuit breakers, grounding knives, cables and other components, which leads to multiple faults and simultaneous discharges in the partial discharge detection process of the switchgear. In order to realize the partial discharge detection and rapid location of the switchgear, based on the introduction of the detection methods and location principles of ultrasonic, transient ground voltage and UHF partial discharge, this paper proposes to use ultrasonic, transient ground voltage and UHF detection technology to diagnose and analyse the multi-source partial discharge of the switchgear and realize the detection of partial discharge; the multi-source partial discharge of the switchgear is realized by the rapid localization method combining the UHF time difference method and the flat surface method. Through partial discharge detection and localization analysis of a 35kV switchgear, the feasibility of multi-source partial discharge diagnosis and rapid localization method is verified, which provides a basis for on-site inspection personnel to realize multi-source partial discharge detection and localization of switchgear.
Improvement of Short-distance Subsidy Policy for Airport Taxi Based on Cluster Analysis
Authors: Yang Tao 
Published: March 2020

Abstract
The income of airport taxis is related to the mileage. Due to the difference in passenger destinations, the mileage is long and short, and the taxi driver cannot pick or refuse to load. Therefore, the difference between short-haul passengers and long-haul passengers is significant. Based on such realistic problems, a relatively reasonable priority policy has been proposed to balance the income of taxi drivers. Under the existing policy based on the short-distance ticket of Shanghai Pudong Airport, combined with the large number of drop-off point data of taxis, the data is pre-processed and then visually analyzed on Bigemap, and then cluster analysis is carried out in matlab environment. The mileage distribution makes a more reasonable division of short-distance long-distance definition and proposes new ideas for solving the problem.
Distribution Network Low Voltage Prediction Method Based on Least Squares Support Vector Machine
Authors: Yao Zhiyang , Jin Qingren , Min Guo , Chen Weidong 
Published: March 2020

Abstract
Due to the lack of a direct functional relationship between voltage and voltage related parameters in the distribution network, it is difficult to scientifically carry out low voltage prediction. Therefore, a low voltage prediction method based on least squares support vector machine is proposed. The method uses the parameters related to low voltage and voltage in the distribution network as the basic data, constructs the optimal problem equation, forms the decision function, uses the decision function to predict the predicted samples, and outputs the lowest voltage value at the end of the low voltage side of the distribution transformer. Finally, the voltage value is analyzed and the low voltage of the distribution network is predicted. The actual distribution network data is used to simulate and verify the proposed method. The results show that the predicted value and the actual value error meet the requirements of estimation accuracy. It is demonstrated that the low-voltage prediction method based on least squares support vector machine is practical.
Analysis on the Reason of Low Voltage Problem and the Effectiveness of Voltage Regulation in a Distribution Area
Authors: Guo Min , Jin Qingren , Yao Zhiyang , Chen Weidong 
Published: March 2020

Abstract
For the problem of low voltage, this paper took a 10kV low voltage line as the research object, summarized and classified the causes of low voltage on the line, analyzed the real reason for the problem of low voltage which combined with the actual situation of the line as the class, put forward many management suggestions. Combined with the actual situation of the line, line automatic voltage regulator would be installed. For automatic voltage regulator, its effectiveness was analyzed from the principle in this paper, 10kV line simulation model was established, this paper gave the simulation analysis of the effect of the line overload on the terminal user’s voltage and the different control effects brought by the installation location of the voltage regulator, the research results provide a scientific basis for the management of the low voltage problem.
Study on Stability Control Strategy Based on Island Micro-Grid of Small Nuclear Power Plants
Authors: Jiang Bo , Zhang Zhong , Xie Xintao , Kang Yong 
Published: March 2020

Abstract
For the island microgrid with limited load capacity, especially after the nuclear power generator set is connected, it is very important to control the grid safely and stably. This paper is aimed at the island micro-grid after the nuclear power generator set is connected. Firstly, the influence of the nuclear power plant on the topology of the power grid after it is connected to the grid is analyzed. Then, through the development of a topology analysis strategy, effective grid conditions are obtained. And the related stability control strategy is proposed that he corresponding CASE is triggered when the grid is faulty, such as generator trip, grid disconnection, generator/transformer overload, etc., to unload the range to ensure smooth operation of the grid. Simulation analysis shows the effectiveness of the proposed stability control strategy.
An Effective Sharpsat Solution Method Based on Learnt Clause Minimization Approach
Authors: Chen Xi , Du Weikang , Xu Yingjie , Ma Mingdian 
Published: March 2020

Abstract
The problem of satisfiability of the propositional logic formula (SAT problem) in computer science is an important and difficult problem. Learning clauses often contain redundant literal in CDCL SAT solving, which may have a negative impact on the performance of the solver. To overcome this shortcoming, we show a new sharpSAT solver based on learning clause minimization is proposed. By recoding the CNF formula to reduce the storage space, and applying Boolean constraint propagation to eliminate redundant literals in the learning clause, the algorithm reduces the time cost. The complexity is compared with the existing solver. The experimental results show that the solver has significant application value, reduces the time of instance solution, and increases the number of maximum solvable instances.
Review of the Basic Technology of Big Data on Analysis and Storage Applied in Power Grids
Authors: Qian Lin , Yu Jun , Zhu Guangxin , Xie Ruocheng , Chen Zhengbo , Wang Lin , Pang Hengmao , Mei Zhu , Xu Mingjie , Chen Haiyang 
Published: March 2020

Abstract
With the era of big data coming, the amount of data generated by humans has grown exponentially, and people have become aware of the importance of data. This paper introduces the concept of big data and big data technology firstly, and then describes the mature technology of big data analysis: Hadoop and Spark. And Taking HBase as an example, the basic theory of big data storage technology is analyzed. The paper is designed to understand the concept of big data and current developments, explain the basic technologies of big data storage and analysis to provide a reference for more accurate cognition.
Trend Analysis of Small Sample Operation and Maintenance Data Based on Function Fitting
Authors: Bo Yang , Jun Wei , Runzhen Yan , Ce Li , Yintie Zhang 
Published: March 2020

Abstract
After years of informatization construction, the State Grid Corporation’s data centers have reached a very large scale in the headquarters and provincial company’s network companies, providing good support for the deployment of various business systems. Compared with the rapid development of the data center infrastructure construction, the data center-related operation and maintenance management work concept is relatively lagging behind, the data center generates a large amount of operation and maintenance data every day, and relevant analysis and processing work of the data was ignored. In response to the overall requirements of the State Grid Corporation to build a ubiquitous power Internet of Things, the operation and maintenance of the computer room has been upgraded to a new level, and the operation and maintenance work will be transformed from the traditional lag problem solving problem to the forward-looking work of predicting the operation and maintenance risk in advance. Through the analysis and processing of operation and maintenance data, this paper establishes the functional relationship between operation and maintenance indicator data and time, so as to predict the events that may cause system downtime in the future.
Anomaly Detection Method for Operation and Maintenance Data Based on One-Class Learning
Authors: Duan Junhong , Yang Bo , Wei Xiang , Liu Ning , Zhang Yintie 
Published: March 2020

Abstract
Due to frequent changes in system services, the amount of data collected in a certain state is insufficient, which causes problems such as insufficiency of normal sample data, scarcity of fault sample data, and lack of prior knowledge. Aiming at the problem of anomaly detection of small sample operation and maintenance data lacking negative samples, this paper proposes an operation and maintenance data anomaly detection method based on one-class learning, which uses SVDD (support vector data description) method to eliminate abnormal data in the collected operation and maintenance data. Then, we can better analyze the subsequent data. The experiments show that the proposed method is reasonable and effective.
Monte Carlo Localization for an Autonomous Underwater Vehicle with a Low-Cost Sonar
Authors: Jiang Keyong , Chen Ling , Yang Aolei , Hu Huosheng 
Published: March 2020

Abstract
This paper proposes a Monto Carlo based localization (MCL) algorithm for autonomous underwater vehicle (AUV) with a low-cost mechanical scanning imaging sonar (MSIS). As MSIS has a slow-sampling characteristic, its scan is distorted by the vehicle motion during the scan interval and the sonar readings are sparse. Our contribution is introducing this two-stage approach to overcome the shortages of MSIS to achieve accurate localization: 1) the scan formation module is devised to eliminate the motion induced distortion of sonar scan; 2) MCL is applied to estimate the AUV pose accurately by the Dead Reckoning (DR) result and the formed sonar scan. Results of simulation verify that the proposed algorithm performs well in terms of effectiveness and accuracy.
Research on Discovery of Radio Communication Relationship Based on Correlation Analysis
Authors: Liu Changkun , Wu Xinrong , Yao Changhua , Guo Jibin , Fan Haoren , pan Ting , Wei Kefeng 
Published: March 2020

Abstract
As the medium of wireless communication, the physical characteristics of electromagnetic spectrum signals and the connection between signals also potentially reflect the intelligence information related to the communication intention of communication individuals. For military communications, spec-trum management, communication security and other fields, it is of great significance to mine and analyze the communication behavior of communication individuals from spectrum data. This paper proposes a method for mining the communication relation-ship between stations in massive spectrum signals based on association analysis. Firstly, we improved the peak density clustering algorithm and used it to study the distribution rules and statistical information of spectrum signals. Then, we carried out correlation analysis on the time range of clustering data to mine of the communication relationship. The experimental results show that this method can effectively discover the communication relationship from chaotic and missing spectrum signals, which lays a foundation for further discovering and studying the commu-nication network structure between radio stations and provides ideas for the analysis of spectrum data.
Study on the Temporal and Spatial Patterns of Environmental Quality in China and Its Influencing Factors Based on Two Perspectives of Pollution and Absorption
Authors: Zhao Qingwen , Li Hong 
Published: March 2020

Abstract
Based on the two perspectives of environmental pollution and environmental absorption, combined with the regional differences of environmental quality influencing factors, SDM model is used to analyse the influencing factors and spatial effects of environmental quality in China and all regions. The research shows that the spatial agglomeration characteristics of environmental quality are obvious, and the problem of regional imbalance is prominent. The environmental quality and economic development in the eastern region are gradually harmonized, but population agglomeration has a greater negative impact on the environment. The development model of high investment, high energy consumption, high pollution and low efficiency in the central and western regions has become a constraint to improve environmental quality.
Coupling Coordination of Coordinated Development Level Between Resource and Environment
Authors: Gao Hua , Han Qian 
Published: March 2020

Abstract
Environmental problems are drawing more and more attention from all sectors. Considering China’s current development background, it is very important to research the coordinated development level of resources and environment. This paper constructs the coupling index system of resource and environment. Then, we analyze the spatio-temporal situation and its influencing factors of the coordinated development in 26 provincial capitals and 4 municipalities in 2005, 2010 and 2015. It is concluded that the spatial distribution of the coupling coordination degree in China is unbalanced. The coupling coordination degree shows the characteristics of decreasing first and then improving. In general, this paper provides theoretical guidance and method support for quantitative analysis of the horizontal coupling coordination degree between resource and environmental development.
Research on reducing carbon emissions from logistics
Authors: Pei Xiaobing , Sun Zhiwei 
Published: March 2020

Abstract
The Earth is warming at an unprecedented rate. The carbon emissions generated by logistics and transportation have caused a lot of impact on the environment. It is extremely urgent to take certain actions to alleviate the energy consumption and carbon dioxide emissions of logistics and transportation. It is recommended to use other heuristic algorithms to optimize the path and distribution order to reduce the carbon emissions of the logistics and transportation industry while ensuring that the goods are delivered as required.
Technology of Vibration Energy Harvester and Its Application in Vertical Axis Wind Turbine
Authors: Mo Qiuyun , Liu Weihao , Liao Zhiqiang , Jiang Li , Guan Huisen 
Published: March 2020

Abstract
With the continuous development of mechanical design theory, materials and machining technology, the energy utilization rate of traditional machinery has been approaching the limit. The exhaustion of energy forces mechanical designers to make breakthroughs in the efficient use of energy. Therefore, the technology of energy harvester based on mechanical vibration has been well developed. Based on piezoelectric, electromagnetic, electrostatic, piezoelectric-electromagnetic coupling, and four types of vibration energy harvesting technologies principle and the typical research achievements, systematic analysis of various kinds of vibration energy harvesting technologies features, development and application of the technical difficulties and constraints, the last small Vertical axis wind turbine, for example, analysis of vibration energy harvesting technologies applied in the actual mechanical feasibility and implementation scheme, thus provided for the research and application of vibration energy harvesting equipment development direction and technical guidance.
Study on the Temporal and Spatial Evolution of the Total-Factor Water Efficiency in the Yangtze-River Economic Belt
Authors: Zou Shengrui , Song Min 
Published: March 2020

Abstract
Based on the SBM-Malmquist model of unexpected output, the paper estimates and decomposes the total-factor water efficiency (TFWE) of 11 provinces and cities in Yangtze-river Economic Belt from 2000 to 2017. The study finds that: (i) TWFE in the Yangtze-river Economic Belt has been significantly improved during the sample time, which has an average value of 0.70, the highest value of 0.91 in 2017 and the lowest value of 0.56 in 2006; (ii) provinces or cities from the eastern region of Yangtze-river Economic Belt including Shanghai, Zhejiang and Jiangsu, tend to have higher efficiency than the central and western regions at the same time; (iii) the index of technical change (Tech) obtained by further decomposition of the efficiency is the main contributing factor of efficiency improvement.