bluuebunny/crossref_metadata_2025_split huggingface dataset:
Main Controlling Factors for the High Production of Tectono-Stratigraphic Reservoirs in Continental Down-Faulted Basin
Authors: Liu He , Li Junhui , Deng Hai , Chen Fangju , Li Yue 
Published: June 2020

Abstract
Huoduomoer structural zone is one of the most favorable oil and gas accumulation zones in Beier depression of Hailaer basin. However, the exploration in this zone has experienced a long and tortuous process, and the exploration is almost stagnant until the natural production capacity of well x1 has obtained daily output of 472m3, which has achieved a major breakthrough in the exploration of tectono-stratigraphic and stratigraphic unconformity reservoirs in this structural zone. Based on the comprehensive study of the subdivided layers of the structural belt, this paper holds that the Nantun Formation suffered from long-term denudation after deposition, the Nantun Formation at the high part of the uplift belt was denuded completely, and the remaining Nantun Formation at the periclinal area was the main target layer for exploration. Based on the analysis of the main controlling factors of hydrocarbon accumulation, it is considered that feldspar lithic sandstone and lithic sandstone mainly developed in the subaqueous distributary channel deposition of braided river delta front are easy to be leached and eroded, forming high-quality reservoir with secondary porosity near the unconformity surface, and the multi-direction oil and gas migration system is the key to the oil and gas accumulation; the stable and thick mudstone deposition in the large section provides a good sealing condition for traps.
Study on the Natural Gas Consumption and its Change Prediction
Authors: Ye Zhanghuang 
Published: June 2020

Abstract
The global total natural gas consumption has risen to 3.67 trillion cubic meters in 2017 according to BP statistics. It is predicted that natural gas will be “the first one” in all primary energy before 2040. The global natural gas demand is expected to reach 4.9 trillion cubic meters respectively in 2040, accounting for 26.9% in the total primary energy consumption. The natural gas consumption analysis shows that the total consumption in the top twelve natural gas consumption countries accounts for 64.5% of the global. The natural gas consumption in America and Russia exceeded one third of the world in 2015. The gas consumption in BRICS (Brazil, Russia, India, and China and South Africa) has risen dramatically since 1980s. After 1990s, the consumption in the Asia-Pacific region has been on the rise, and the cumulative increment took the first place from 1975 to 2015. The Asia-Pacific region is expected to be the new global consumption center after Europe and America. From the point of per capita consumption, North America, the Middle East and former Soviet Union with rich natural gas resources have exceeded to 2 tons of oil equivalent, nevertheless, the less-developed regions such as Asia-Africa-Latin America are below 0.5 ton of oil equivalent. The gas natural consumption in none-OECD countries exceeded that of OECD in 2007, and the gap has increased year by year. However, the per capita consumption of natural gas in OECD is 5.2 times of Non-OECD. The consumption pattern is mainly influenced by economy development, if natural gas production pattern by resource endowment.
Accuracy Analysis of RV Reducer Eccentric Shaft Follow-Up Grinder
Authors: Fan Jinwei , Tao Haohao , Wang Peitong 
Published: June 2020

Abstract
Eccentric shaft follow-up grinder is the core equipment in the process chain of eccentric shaft machining. In the process of grinding, the establishment of the kinematic model and the determination of the kinematic relationship of the C-X axis follow-up grinding directly affect the quality of the grinding process, and there are many error factors in the grinding process. It is very important to analyze the influence law of these factors on the quality of the workpiece. Through the mechanism of the error in the process of machining, which is caused by the change of X coordinate position, head frame rotation and wheel center eccentricity, the geometric relationship is established to solve the problem. The MATLAB simulation is carried out to find out the source of the error, so as to lay the foundation for the subsequent error compensation and achieve the purpose of improving the machining accuracy.
Research on Optimal Design and Practical Application of Electric Vehicle Wireless Charging Technology
Authors: Chen Nuo , Wang Zhen , Guo Yanan 
Published: June 2020

Abstract
Electric vehicles are a further development of wireless charging technology and a promising application area. This method can take into account the user’s charging satisfaction and the load pressure of the charging road, while meeting the requirements of power supply cost and power supply stability. This article introduces the research progress and application of wireless charging technology at home and abroad, then introduces the classification of wireless power transmission technology in detail, and then introduces the structure of the wireless power transmission system of electric vehicles in detail. Simulation results of the wireless charging technology of the car show that the advancement of charging technology will lead to the further development of new energy electric vehicles in the future. This article describes the development of new energy electric vehicle charging technology in recent years, and puts forward the development direction and development suggestions of new energy electric vehicle charging technology.
Research on Marine Diesel Engine Fault Diagnosis Based on the Manifold Learning and ELM
Authors: Shao Mingqi , Wang Jin , Wang Sibo 
Published: June 2020

Abstract
As the core equipment of marine power system, the operation state of marine diesel engine has a direct impact on the safe navigation of the whole ship. In order to extract fault features from vibration signals of diesel engine more comprehensively, a new fault diagnosis method is proposed based on the advantages of feature fusion and manifold learning algorithm in dealing with nonlinear data. The manifold learning method is used for feature extraction. Through this method, the vibration signal of diesel engine is extracted, and the feasibility and superiority of this method are verified from the perspective of three-dimensional visualization. The extracted features are input into the elm model to identify the working condition of marine diesel engine. Experimental results show that the proposed method can achieve real-time fault diagnosis with high classification accuracy.
Study on The Influence of Negative Temperature Gradient of U-shaped Girder of Rail Transit in Winter
Authors: Dong Xu , Sun Guofu , Xu Gangnian 
Published: June 2020

Abstract
To study the influence of negative temperature gradient of U-shaped girder of rail transit in winter season, a U-shaped rail transit girder was researched in Qingdao. The temperature self-stress of the mid-span section were observed for a 48-h period during the winter. The temperature stress were obtained which caused by vertical and transverse temperature gradient at maximum temperature difference time. The temperature effects caused by different temperature gradient models were analyzed and compared with actual results using a finite element model. The results show that, given the temperature effect, the compressive stress of the mid span section of the structure is small, the web and bottom slab have a greater longitudinal tensile stress which should be considered in the design.
Design of a Multimode OAM Vortex Electromagnetic Microstrip Array Antenna
Authors: Mao Pengrong , Gao Canguan 
Published: June 2020

Abstract
On the basis of the characteristics of electromagnetic wave orbital angular momentum can improve spectrum efficiency, this paper proposes a low profile, more OAM models design of antenna. The antenna subject selection is made of glass fiber epoxy resin substrate, using phased array feed technology under the condition of the limited antenna unit number achieved by each antenna feed different phase excitation. By adjusting the position of the feeding point, the matching of the input impedance of the antenna is improved and the optimal structure of the antenna is determined. The simulation results show that the antenna achieves good impedance matching at the center frequency of 2.45GHz and generates 7 kinds of vortex electromagnetic beams with different OAM modes. The antenna has the characteristics of small size, light weight and low profile, which provides a novel antenna structure for the design of communication terminal antenna array.
Design and Research of a New Type of Semi-Automatic Winding Seedling Packaging Machine
Authors: Jiang Keyue , Qiu Yukun , Qian Yizhen 
Published: June 2020

Abstract
The current seedling packaging industry has the problems of cumbersome packaging process and low packaging efficiency. This phenomenon does not correspond to the high throughput and efficient packaging efficiency of seedling network marketing under the background of the existing Internet big data era, and the slow efficiency is seriously hindered. The rapid development of the seedling industry. In response to this problem, this paper made in-depth research and found that the seedling packaging occasions are mostly outdoor, there are problems such as power supply inconvenience. This paper designed a semi-automatic seedling packaging machine driven by artificial power, which is powered by human footsteps. The four-bar mechanism transmits the foot power, the hand wheel on the machine rotates to realize the clamping and fixing of the seedlings, and finally the gear train of the machine cooperates with the timing belt to provide the bidirectional winding power, and the upper and lower gears in the device drive the incomplete gear mechanism. Provides non-equal speed movement to achieve the winding and cutting of seedling wrap film. The Samsung wheel reversing mechanism can convert the winding method to realize the fast and complete winding of some seedlings (10cm-30cm), effectively improve the packaging efficiency, and enable the seedling network dealers to better adapt to the contemporary network business model. And provide technical reference for the research and design of similar products.
Infrared and Visible Image Fusion Based on Gradient Reconstruction
Authors: Lei Zhen , Huang Yanyan , Cui Peizhi 
Published: June 2020

Abstract
A fusion method of infrared and visible image based on gradient reconstruction is proposed. Firstly, the structure tensor of infrared image and visible image is pre fused, and then the pre fused image is re fused based on gradient reconstruction and Poisson equation to get the final fusion image. The experimental results show that the method is effective, and the fusion image can synthesize better target feature information of infrared image and scene detail information of visible image, which has better performance than other image fusion methods
Research on Taper Detection Method of Roller for Belt Conveyor
Authors: Yu Cheng , Liu Yulang , Yang Qihua 
Published: June 2020

Abstract
The taper of the roller’s body is closely related to the self-correcting efficiency of belt deviation and the reliability of roller operation on belt conveyor. Due to the installation structure of roller, it is difficult to evaluate the taper of roller by manual multi-point detection and comprehensive analysis. In this paper, the taper correlation index is defined based on outer cylindrical surface of roller and designed the automatic detection method. The error processing model of data is established according to actual tooling conditions for testing and the realization scheme of sensor detection. The feasibility of the design method is verified by testing the standard roller.
Current Situation and Application Prospect of Energy Storage Technology
Authors: Liu Ping , Wu Fayuan , Tang Jinhui , Liu Xiaolei , Dai Xiaomin 
Published: June 2020

Abstract
The application of energy storage technology can improve the operational stability, safety and economy of the power grid, promote large-scale access to renewable energy, and increase the proportion of clean energy power generation. This paper reviews the various forms of energy storage technology, compares the characteristics of various energy storage technologies and their applications, analyzes the application status of energy storage technology, and prospects the application prospects of various energy storage technologies.
Research on the impact of different charge and discharge modes of electric vehicles on power grid load
Authors: Wen Wen , Wang Lifang , Zhu Mengdi , Peng Zhou , Yao Fangling 
Published: June 2020

Abstract
The rapid development of the economy has made the scarcity of traditional fossil energy increasingly prominent. At the same time, with the proposal of the beautiful China strategy, electric vehicles have become an important choice for people to travel. Different charging and discharging modes of electric vehicles have different impacts on the power grid load production. Reasonably controlling the impact of electric vehicle charging and discharging loads on the power grid, narrowing the peak-to-valley difference, and ensuring the reliability of grid operation have become urgent issues to be resolved. This paper selects electric private cars and electric buses that have a large effect on the power grid load as the research object, and uses qualitative and quantitative research methods to extract the main influencing factors of electric vehicle charge and discharge. A charge and discharge daily load calculation model for electric vehicles under three modes of disorderly charging, one-way ordered charging and bidirectional ordered charging and discharging was constructed, and a typical Tianjin electric vehicle charging behavior research sample was selected. Monte Carlo method was used to predict the daily load of Tianjin electric vehicles under three charging and discharging modes, and the results were analyzed and discussed, and the corresponding management inspiration was given.
Research on Construction Technology of Ultra-Low Energy Reconstruction of Existing Buildings
Authors: Zhao Shiyong , Qiang Wanming , Hao Yuhang , Fu Sujuan , Shi Yuanyuan 
Published: June 2020

Abstract
Taking the renovation project of the family building of the Hebei Academy of Building Research as an example. This paper studies the construction process and construction points of the ultra-low energy transformation process, and forms a complete and refined ultra-low energy consumption of existing buildings. Reconstruction of construction technology provides a reference for the promotion and application of ultra-low energy consumption technology in the energy-saving renovation of existing buildings.
Hyperspectral Image Classification of Convolutional Neural Network Combined with Valuable Samples
Authors: Hu Lixin , Luo Xiaobo , Wei Yufan 
Published: June 2020

Abstract
Aiming at the problem that the manual labeling of samples in the hyperspectral image classification is expensive and laborious, a large number of unlabeled samples are not effectively utilized and the classification results are not ideal. A method which can provide valuable samples and employ convolutional neural network to extract spectral spatial features for classification is proposed. Active learning method is used to construct a valuable training sample set by iteratively selecting the most uncertain samples through support vector machine which performs well in small sample classification, and labeling them. Then the 3D convolutional neural network is used to extract the spectral spatial features of hyperspectral image. The experimental results of the hyperspectral classification on Indian Pines and PaviaU datasets show that the proposed method (3D VS-CNN) is better than traditional classification methods.
Research on the Portable and Intelligent Photovoltaic Power Generation System Based on Microgrid
Authors: Gao Zhen , Xi Ziqiang , Liu Gege , Qin Yu , Zhang Zhitong , Liu Junzhe 
Published: June 2020

Abstract
A new design scheme of photovoltaic power generation system was proposed in the paper. The photovoltaic power generation technology was applied into an independent microgrid system, combined with intelligent grid technology and energy storage technology, and thus a portable and intelligent photovoltaic power generation system based on microgrid was constructed. The system was composed of solar power generation system, energy storage system, distribution apparatus and other parts. The photoelectric and line tracking methods were combined to make the battery panel conduct three-dimensional sun-chasing movement when it moves. The perturbation and observation method with variable step based on power prediction was raised so as to achieve maximum power point tracking. The battery energy management system was responsible for controlling the battery charging and discharging, as well as state detection, which ensured continuous and stable power supply of the load. The system could be expanded to build portable emergency power source, of great significance to rescue and relief work, military operation, field scientific investigation, navigation and so on.
Pedestrian Recognition Based On Improved Semantic Segmentation Neural Network
Authors: Guo Xiucai , Wang Yaodong 
Published: June 2020

Abstract
At present, the existing Re-ID methods can’t align the target and the target in the image that should to be detected, which has been affecting the recognition accuracy. Although using semantic segmentation method can solve this problem, it brings new problems. The region which is considered as background by semantic segmentation neural network and discarded is likely to contain feature representations that are helpful for recognition. In this paper, an improved semantic segmentation method is proposed to re-divide the foreground and background regions. In order to avoid the influence of semantic segmentation errors on recognition accuracy, a new method is used to combine background and foreground regions. Experiments show that the accuracy of Re-ID is 84.52%, which is 3.33% higher than before.
Research on Construction Technology of Multi Heterogeneous Data Resource Graph of Power Grid Corporation
Authors: Wang Liying , Tian Shi , Shen Liang , Cheng Zhihua , Zeng Ming , Li Yanbin 
Published: June 2020

Abstract
The development of new-generation artificial intelligence technologies such as deep learning, knowledge graphing, and enhanced learning is driving the “Internet + Smart Energy” into a new era of “Internet of Energy.” The data structure, type, and format of the data between the main body of the energy and power system, various departments of the enterprise, and various types of users are all constructed at different times using different standards. The data is huge and complex. Establishing a company-level data center for power grid companies to resolve the standardized management and fast and reliable exchange of heterogeneous data under massive data is an opportunity and a challenge for the company to build an energy Internet. As the core foundation of integrating heterogeneous data resources of power grid, data resource graph can provide effective support for the management of heterogeneous data of power grid enterprises under the energy Internet. From the multi-dimensional perspective of data modeling, resource management, data navigation, learning cognition, database, this paper focuses on the diversified and heterogeneous data resources of power grid companies, and explores from the specific technical aspects of data ontology modeling, data naming and identification, data relationship mining, data fusion and exchange technology, aiming to provide technical support and reference for power grid companies to build data resource graph.
An improved grid-connected pre-synchronization method for photovoltaic micro-grid
Authors: Zhou Zifu , Long Jun 
Published: June 2020

Abstract
Due to the obvious steady-state error that traditional grid-connected pre-synchronization regulation, current shock may occur when photovoltaic micro-grid is connected to the grid. To solve this problem, an improved pre-synchronization method with higher steady-state adjustment accuracy is designed by using the brain emotion control algorithm in the inverter control link. This method can reduces the transient shock of current when the micro-grid is connected to the grid. MATLAB / Simulink software is used to establish a simulation model, through which the correctness and feasibility of the proposed method are verified.
Study of Comparing Several Nonlinear Filtering Algorithms in Carrier-based Aircraft Positioning
Authors: Du Yajie , Zhao Jianjun , Yao Gang 
Published: June 2020

Abstract
In order to improve the positioning accuracy of the landing guidance radar to the carrier aircraft, the nonlinear filtering algorithm is used to estimate the positioning of the carrier aircraft. The main algorithms of nonlinear filtering, such as extended Kalman filter, unscented Kalman filter and particle filter, are analyzed and compared. A typical nonlinear model is simulated to verify the performance of these algorithms. The simulation results show that the estimation accuracy of the particle filter algorithm is better than the other two filter algorithms.
Ship Classification from SAR Images based on Sequence Input of Deep Neural Network
Authors: Zhu Hongliang , Lin Nan , Leung David 
Published: June 2020

Abstract
This article proposes an all brand new classification architecture for SAR images of the ship via deep learning. Compared with the most widely used conventional classification algorithm based on deep neural networks, we set a sequence of SAR images as input to the neural network, which is different from a single image as input in those kinds of conventional ones. Two central neural networks form the construction of this new classification architecture; the first is a convolutional neural network used to extract the features of each frame, and the second is the LSTM part, which is trained on the sequence to predict the labels. It is much more significant to enhance the connection among the SAR images primarily due to the limit of SAR data, which makes us combine all the SAR images to several sequences. The proposed new classification architecture is trained on the OpenSARShip[2] dataset captured by Sentinel-1 space-borne radar. Experiment results show that the classification architecture can get an accuracy of 99.24% in classifying the six kinds of targets, which is much more precise than any conventional methods before.
Application of statistical process control technology in operation optimization of thermal power units
Authors: Tian Penglu , Yuan Jun , Zhang Shaonan , Li Zhichao , Wei Qingbo 
Published: June 2020

Abstract
The reliability of power plant data becomes more and more important with the development of smart power plant based on big data and artificial intelligence technology. Statistical process control technology is widely used in product production process management, but it has never been involved in thermal power. In this paper, the statistical process control technology is applied to the thermal power industry. The application results show that the statistical process control technology can not only take the calculation results as the quantitative criteria for the operation conditions of the unit, but also help to select the comprehensive optimal conditions of the unit under the specific conditions, and implement the goal of improving the management level and economic benefits of the power plant.