bluuebunny/crossref_metadata_2025_split huggingface dataset:
Curve tracking and comparison during electricity spot trading based on judgment methods for curve similarity
Authors: Zhang Shuai , Chen Shijun , Ma Guangwen , Zhu Yanmei , Tao Chunhua 
Published: August 2021

Abstract
Accurate tracking of load curves during transactions in the electricity generation process and timely identification and adjustment of aberrant electricity prices are key to ensuring profits from bidding in the production of enterprises. By selecting three judgement methods for curve similarity, i.e. Euclidean metric, correlation coefficient and mean square error (COE-MSE), and discrete Fréchet distance, this study tracked and compared an electricity generation curve, a transaction curve, and a bidding and declaration curve of a hydropower station where reservoirs have strong regulating capacity in a river basin in the Sichuan Province power grid. The advantages and disadvantages of the three methods were analysed and compared. The results demonstrate that the COE-MSE and discrete Fréchet distance can meet the requirements of electricity generation according to the transaction results when electricity generation enterprises participate in electricity spot trading. Furthermore, the discrete Fréchet distance shows advantages in identifying eigenvalues and tracking trends of the curves.
Analysis of Fault Waveforms of Key Electrical Parameters in Hybrid Multi-terminal DC System
Authors: Liu Hengmen , Zhan Xin , Hu Haoyu , Liang Yiwen , Liu Zhong , Shi Shenxing , Dong Xinzhou 
Published: August 2021

Abstract
LCC-VSC hybrid multi terminal HVDC system combines the advantages of traditional HVDC and flexible HVDC technology, and becomes one of the new directions of HVDC development. In this paper, taking the Baihetan Jiangsu HVDC transmission project as an example, under the appropriate simplified model, the critical electrical stresses of the DC side faults of a typical LCC-VSC hybrid multi-terminal DC system are analyzed. The simulation results verify the correctness of the simplified analysis in this paper.
Application of Knowledge Mapping Technology in Power System
Authors: Gong Lihua , Liu Kunpeng , Tian Nuo , Wang Xiaoyi , Wang Jiajia , Zhu Jinpeng 
Published: August 2021

Abstract
In order to improve the identification ability of power system topology, the application of knowledge mapping technology in power system is proposed. Based on the division of structured, semi-structured and unstructured, the power system data is extracted. The neo4j graph database is used to store the extracted data, and the cypher statement of NEO4J is used to complete the construction of power system knowledge map. On this basis, the power system topology is identified based on the results of semantic segmentation. The results show that in the simulation environment, the topology recognition rate can reach 100%. In the actual environment, the topology recognition rate increases with the increase of the amount of data, up to 100%
Research on parameters matching and optimization method of power transmission system for electric logistics vehicle
Authors: Wang Zongze , Zhao Keli , Su Lida 
Published: August 2021

Abstract
As a main way of logistics transportation, electric logistics vehicle is beneficial to logistics industry and save energy. Parameters matching and optimization method of power transmission system for electric logistics vehicle is studied in this article. Data processing rules and principles are created for CHTC-LT working condition. Working condition and genetic algorithm are used for parameters matching and transmission ratio optimization of power transmission system. Driving range of electric logistics vehicle could be improved.
Optimal two-stage dispatching strategy of multi-element integrated power station considering demand response characteristics
Authors: Wu Jingting 
Published: August 2021

Abstract
In order to analyse the influence of the storage power station on the regional distribution network under the background of multi-element integration, and reduce the negative impact of charging and discharging load on the power network, based on the general model of multiple integration, considering the demand response characteristics, the load model of data centre, the model of energy storage station and the model of distributed new energy are established. The whole life cycle economic benefit model of energy storage system is established considering the energy storage arbitrage income, the government electricity price subsidy income, the delay of power network upgrading and the whole life cycle cost. Based on the two-stage optimization model, a “Maximum net profit-minimum fluctuation” charging and discharging strategy model is established for the energy storage power plant under the background of multi-element integration. The objective of this method is to minimize the load fluctuation in the distribution network based on the maximum net income of the energy storage system. Finally, the simulation results show the effectiveness of the proposed method.
Study of the effect of the cross-sectional area of a loaded plunger spool on the outlet flow of a plunger pump
Authors: Yao Shi , Xing Keli , Jin Xiajie 
Published: August 2021

Abstract
In this paper, a simulation model of the K3VDT63 axial piston pump variable is established using AMESim simulation software, and the new load plunger spool is studied and analysed on this simulation model. The load plunger spool of the studied axial plunger pump variable regulator was tested and the corresponding test data were obtained, and the obtained test characteristic curve and the characteristic simulation curve were compared and analysed.
Study of Intelligent Identification Method for Drilling Condition and Lithology in Underground Coal Mine Based on Deep Learning
Authors: G Chen , Z Q Bi , X Chen 
Published: August 2021

Abstract
It is important to accurately master the downhole drilling parameter information and drilling formation lithology for the sake of efficient and reasonable gas extraction, hole arrangement and construction safety. According to different detection information, an identification & interpretation model for drilling engineering parameters and a lithology identification & interpretation model in while-drilling azimuthal Gamma logging were established. Next, the drilling conditions were judged and the lithology was discriminated. However, this method relied heavily upon the professional quality and working experience of workers. By numerically simulating the influence laws of azimuthal Gamma logging on the amplitude values of detection data under different borehole sizes, a more suitable method was chosen and applied to the automatic lithology explanation and identification during the logging. An object identification method combining deep convolutional neural network (CNN) and multi-weight multi-task learning mechanism was established, followed by the residual network design, in an effort to elevate the network training rate.
Study on the Strategy of Improving the Primary Frequency Regulation Capability by Adaptive Parameters of Turbine Governor
Authors: Qi Zheng , Zhang Kunjun , Geng Yunfeng , Wang Guanhong , Chen Gang , Shi huabo 
Published: August 2021

Abstract
Many studies have shown the inverse regulation characteristics of water hammer effect inherent in the hydropower system and the unreasonable parameter configuration of the governor result in the generation of the ultra-low frequency oscillation. The main research work of this paper is above two points. Based on the detailed analysis of the influence of each parameter of the speed regulating system on the frequency characteristics of primary frequency regulation, combining with the improved particle swarm optimization algorithm, a self-adaptive parameter configuration technology on PID governor of hydraulic turbine regulation system is presented, the PID parameters can be adjusted continuously according to the rotation speed deviation. And the simulation analysis is carried out. The effectiveness of the adaptive PID parameter method to improve the primary frequency regulation ability is verified.
Experimental and Numerical Study of Erosion Wear of Fan Blades in Microgrid
Authors: Zhou Ruyao , Duan Hangbo , Ye Hao , Wang Tong , Zhou Hongxiang , Yao Yan , Liang Xiaoyu 
Published: August 2021

Abstract
As one of the most important components of wind turbines, the fan blade is prone to erosion being exposed to multiphase flow environment, which affects the operation efficiency of wind turbines. In order to reduce the loss caused by the erosion of the fan blade, the erosion rate tests of the fan blade were carried out in this paper. The relevant function values of the simulation mathematical model were calculated from the test results, which were verified by a simplified two-dimensional case. Additionly, a numerical simulation of the three-dimensional full-size gas-solid two-phase flow around the fan blade was conducted, and then the variations of a single blade erosion rate with different wind speeds, sand sizes and impact angles were studied. The results showed that the sample erosion rate was increased with wind speeds and impact angles. The blade tip region was the most susceptible area to erosion, of which protection should be strengthened.
Reliability Evaluation of Cyber Physical Distribution System considering EPON
Authors: Shuyuan ZHANG , Guiping LI 
Published: August 2021

Abstract
As cyber-physics highly coupled distribution system, the influence of communication network on the reliability of power supply can not be ignored. Based on the EPON redundant protection network, this paper analyzes the influence of the loss of cyber link effectiveness on the self-healing control process in the process of power distribution network failure. With the help of the region adjacency matrix, combined with the cyber system failure model, the classification algorithm of the region after failure is given, and a reliability evaluation method coveannular different cyber system failure modes is proposed. Finally, the feasibility of this method is verified by a case study, and the influence of EPON cyber element failure rate and EPON networking mode on the reliability indices is compared and analyzed.
Research on probability estimation of critical threshold kernel density of icing tension for transmission lines with different tower types
Authors: Su Jiang , Jianrong Wu 
Published: August 2021

Abstract
Tension sensor plays an important role in anti-icing work of transmission line, but in the process of back calculating ice thickness, it needs to accurately calculate important parameters such as vertical span, horizontal stress and vertical load, which leads to cumbersome work procedures. Therefore, in this paper, the wavelet decomposition algorithm is used to correct the tension value during non-icing period. The results show that the modified tension value can effectively improve the accuracy of icing thickness calculation by 28.88%; secondly, the pulling force values under the conditions of icing ratio of 0.3 and 0.5 are calculated. Finally, the kernel density function is used to give the thresholds of issuing ice melting warning and starting ice melting pulling force for the straight-line tower and tension tower lines. The conclusion of this paper is simple and accurate.
Research on Skill Training of Relay Protection Device Based on Virtual Reality Technology
Authors: Chang Chun , Wang Jianlong , Duan Fengju , Tian Rubing , Liu Yu , Ji Xuanying , Qiao Xuejing 
Published: August 2021

Abstract
Aiming at the problem that operation and maintenance personnel and new employees have insufficient experience in substation secondary equipment, especially the secondary circuit operation, this article introduces the current domestic and foreign research status of virtual reality technology. With the goal of enhancing the fun of substation secondary equipment training and improving training efficiency, the overall research ideas and content are proposed, and the application function framework of virtual reality technology is explained.
Wood acoustic emission signals classification based on pseudospectrum, and entropy
Authors: Meilin Zhang , Junqiu Li , Jiale Xu , Jiawen Zheng , Qinghui Zhang 
Published: August 2021

Abstract
The nondestructive testing technology of generated acoustic emission(AE) signals for wood is of great significance for the evaluation of internal damages of wood. In order to improve the classification accuracy and adaptability of AE signal, we selected two features(pseudospectrum, entropy) for classify AE signals in the process of wood fracture using SVM classifier. The three-point bending load damage experiment was utilized to generate original AE signals. Evaluation indexes(Precision, Accuracy, Recall, F1-score, Cohen Kappa score, Matthews Corrcoef) were adopted to assess the classification model. The results showed that the overall accuracy of the SVM classification model obtained by the method combining pseudospectrum and entropy features is 89.44%, which indicates that this automatic classification model has good AE signal recognition performance.
A pest sexual attraction monitoring system based on IoT and image processing
Authors: Qing ZHAO , Hecang ZANG , Jie ZHANG , Meng WANG , Guoqing ZHENG , Guoqiang LI 
Published: August 2021

Abstract
In order to improve the efficiency and timeliness of pest field sexual attraction monitoring and then improve the efficiency of crop pest forecasting, in this study, we improved the traditional method of sexual inducement by designing a remote insect trap image collection device with image collection, remote communication and other Internet of Things technologies. An image processing and counting method based on OpenCV cascade classifiers was constructed with remote sexual attraction images. A pest situation database was established, and a pest monitoring and early warning system was constructed. The application of the system is convenient for plant protection technicians to collect and query the pest monitoring data, as well as the release of the pest early warning information, and it does realize the informatization of crop pest monitoring and early warning.
Multi-focus Source Images Reconstruction based on Adaptive Regional Data Hiding
Authors: Liu Meng-yao , Zhou Quan , Zhang Yi , Hu Yan-lang , Liu Juan-ni 
Published: August 2021

Abstract
Preserving the information of multi-focus source images was neglected in previous image fusion schemes since source image data discarding will happen during the fusion process. Data hiding technology can utilize the redundant bits to embed essential secret data. Inspired from that we proposed a multi-focus image reconstruction algorithm using adaptive regional data hiding. Integrating the Human Visual System (HVS) into the reconstruction module, we further proposed a visual grayscale information entropy operator, which is implemented to segment fused images into texture and flat regions for adaptive data hiding after unfocused region data compression. Our method achieves excellent performances in reconstruction Peak signal-to-noise Ratio (PSNR) above 43dB and maintains the satisfying visual effect of the fused images.
Research on the module of color image sonar system based on imx6ull
Authors: Zhao Xiaofeng , Wang Jing , Li Wei , Wang Zhiyuan , Zhang Qijiang 
Published: August 2021

Abstract
Underwater sonar imaging system has a wide range of application prospects, and both military and civil are increasingly valued. This paper introduces the module design of a color image sonar system based on IMX6ULL and completes the imaging of the sonar system through experiments. The main frequency and sampling frequency of the system are improved and applied to the TKIS-I color image sonar digital system. High-performance A / D is used for data acquisition and storage, and RS485 is used for long-distance transmission to the host computer to realize display and imaging. It is mainly composed of a core board, PWM signal module, communication module, sampling module, and motor drive module. The processing speed and imaging effect of the improved system are significantly improved.
Slap swarm algorithm with memory mechanism and boundary collision processing
Authors: Yu Kaixuan , Li Yachao , Zhang Dongsheng 
Published: August 2021

Abstract
Aiming at the problem of that the standard salp swarm algorithm has low result precision and slow convergence velocity in the evolutionary process, an improved salp swarm algorithm optimization based on memory mechanism and boundary collision processing is proposed. Firstly, a Chebyshev chaotic map was used to initialize the salps to make them distribute more evenly in search space. Secondly, adding the memory mechanism introduces the individual history optimum of salps into the optimizing strategy of individual salps, which accelerates the convergence speed of the algorithm. Finally, the boundary collision rebound mechanism is introduced to ensure the effectiveness and diversity of the population. The improved algorithm is simulated on 12 types of benchmark test functions in this paper, and compared with other intelligent optimization algorithms under the same conditions. The results show that the improved algorithm has not only a obvious improvement in convergence speed and convergence accuracy, but also has better optimization performance.
An improved conical scaning tracking method in Satellite Communication Systems
Authors: Wang Zhaowen , Zhao Laiding , Xie Min 
Published: August 2021

Abstract
Shipborne satellite earth stations will cause feed vibrations when the conical scanning frequency is too high under low dynamic conditions, which will cause large fluctuations in the received signal strength of the earth station in a relatively stationary environment. And too low conical scanning frequency will cause the earth station Lost the target satellite in a high dynamic environment. The tracking system adopts adaptive speed regulation strategy and initial phase estimation algorithm, and adjusts the frequency of cone scanning in real time according to the motion attitude of earth station measured by IMU, so that the earth station can adapt to different dynamic environment. In practical engineering, a Ku band tracking system of ship borne satellite earth station is designed and implemented based on FPGA. The actual test results show that the signal fluctuation of the improved cone scanning algorithm is about 2dbm lower than that of the cone scanning algorithm with a fixed frequency of 50Hz.
Research and Improvement of TextRank Algorithm Adding Degree Adverbs
Authors: Liu Chengxia , Che Yuheng , Duan Ruixue 
Published: August 2021

Abstract
Textrank algorithm is an approach to exact keywords in articles which will be the premise to find useful information in massive network data. After analysing the characteristics of this algorithm, this paper improves the accuracy of keyword extraction by adding degree adverbs. Based on the function of the original algorithm, a degree adverb table is established, which contains all the degree adverbs that need to be marked. By adding the degree adverbs marker, the results of keyword extraction for the same text will be improved. According to experimental studies, for most articles, adding degree adverbs judgment function increases the importance of key words in these articles. At the end of this paper, the keyword extraction results for different types of articles is demonstrated and compared.
Vehicle re-identification method based on global and local feature fusion
Authors: Bing Zhou , Wei Wei , Huaihong Wu 
Published: August 2021

Abstract
Vehicle re-identification is still an issue worth discussing due to change of view, light and angle changes. At present, the key of vehicle reidentification research is to solve the problems that the difference between the same class is big and the difference between different classes is small. For the study, a vehicle re-identification method ground on view classification is proposed.The vehicle images are divided into four views, namely, front, rear, top and side, and local features are extracted by the segmented view information. Using the CNN feature extractor, the global feature representation with car ID attribute is learned. We have done experiments with the VERI-776 data sets. The mean average accuracy of 78.13% is obtained, which proves the effectiveness of the method.
A service caching method for mobile edge computing
Authors: Wu Xiaojun , Wang Yong , Yuan Sheng , Xie Peiru 
Published: August 2021

Abstract
Mobile Edge Computing (MEC) is considered as a key technology to support 5G networks. It can push cloud computing functions to the edge of the network, and achieve the purpose of reducing latency and reducing energy consumption through computing offloading and edge caching. In the MEC system, by caching computing services from the cloud center to the network edge, MEC can provide users with more services, and also be able to make greater use of network resources and improve system performance. However, which services to cache at edge nodes and how to cache these services have become an important challenge of the research. In order to solve the aforementioned problems, in this paper, we analyze the popularity of each cached object firstly, and propose a novel service caching algorithm, which aims to reduce system delay and improve resource utilization. In addition, we design a novel cache replacement algorithm that successfully predict future requests by analyzing historical data, thereby greatly improves the cache hit rate. Finally, experiments prove that our algorithms have greatly improved system performance and hit rate.
Application of Improved S-Curve Flexible Acceleration and Deceleration Algorithm in Smart Live Working Robot
Authors: Wu Han , Huang Jianye , Lin Shuang , Liu Bingqian , Fan Yuanliang , Wu Binyu , Huang Zhifan 
Published: August 2021

Abstract
Smart live working robot incorporates the merits of security and reliability, which can greatly improve automation rate of living working, suitable for power distribution network live working applications. Due to flexible strike and shake in automatic stripping wire module of smart live working robot start and end period, an improved S-curve flexible acceleration and deceleration control method is proposed. Based on analyzing disadvantage of conventional linear and exponential acceleration and deceleration algorithm, formula math model of improved cubic polynomial S-curve acceleration and deceleration algorithm is derived. Five-paragraph format motion planning is adopted the proposed S-curve control method, which can realize appointed acceleration and deceleration time moving. Meanwhile, the acceleration is continuous during moving period, and according to different working condition, different Scurve type can be chose. The simulation and practical operating results showed that proposed control strategy can effectively reduce flexible strike, thus improving stationarity and accuracy of the control system.
Research on optimization of improved ant colony algorithm in the temperature control process of cold creep forming
Authors: Xu Yiming , Liu Naijia , Xue Peng 
Published: August 2021

Abstract
In the process of cold creep forming, the temperature control has problems such as low accuracy and slow response speed. Moreover, the conventional PID temperature controller has poor anti-interference ability and low control accuracy.This paper designs a PID control strategy based on improved ant colony algorithm which is applied to the temperature control of cold creep forming. With the help of Matlab simulation software, a temperature controller simulation model is established, and certain improvements are made to the model on the basis of the traditional ant colony algorithm, applying to search for the optimal parameter combination in PID control. The simulation results show that the designed control strategy can find a better parameter combination than the PID control of the ant colony algorithm. Therefore, the application of this control method to the cold creep forming temperature control system can effectively improve the product quality and production efficiency of the cold creep forming process.