bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Fault Diagnosis of Low voltage Transformer Based on Sound Feature Analysis
Authors: Huang Changbao , Cao Yang , Wang Youxiang , Zheng Yinggang , Xu Yaoliang 
Published: December 2022

Abstract
This paper analyzes the frequency spectrum of the sound and vibration signals during the operation of the transformer, extracts various sound characteristics for fault classification, accurately carries out real-time early warning of the operation state of the transformer, reduces the occurrence of various power consumption faults and disasters, and improves the “intelligent” means of transformer management.
Design of Backup Protective Hardware for Suspension Clamp of Electric Power Overhead Ground Wire
Authors: Feng Zhenbo , Zheng Xiaogan , Yang Yihao , Lin Li , Qian Chaofei 
Published: December 2022

Abstract
Aiming at the disconnection problem of power overhead ground wire caused by wind vibration or the action of power frequency short-circuit current, the newly revised “Eighteen major anti-accident measures of State Grid Corporation China” proposes that independent double string structure should be adopted in suspension clamp of overhead ground wire. Based on this, a research scheme of backup protective hardware for the suspension clamp of the overhead ground wire of the power transmission line is proposed. In this scheme, the backup protective hardware for the suspension clamp is designed and added on the premise that the original overhead ground wire-suspension clamp structure is not changed. It provides backup measures for the original suspension clamp and reduces suspension clamp heating by an electrical shunt. Finally, the mechanical failure load test and salt spray test are performed on the designed production. The results show that the designed production meets the standard and could be used in actual engineering. At the same time, the practical engineering application shows that the backup protective hardware can effectively reinforce the ground wire suspension clamp with double strings, avoiding the problem of dropping and breaking after the original clamp is broken.
Development and Application of Ionospheric Detection Technology
Authors: Sun Haiyang , Xu Liren , Wang Shengguo , Wu Yiyun 
Published: December 2022

Abstract
Aiming at the needs of ionospheric detection and application development, this paper mainly introduced the current development and analyzed the advantages and disadvantages of ionospheric detection technology from ground-based and space-based instruments. Meanwhile, the hot topics of ionospheric application were introduced from the three aspects of ionospheric irregularity, earthquake-ionospheric effect, and ionospheric heating, respectively. Finally, the development trend of ionospheric detection technology and its application were discussed from five aspects, and some suggestions for the future comprehensive research fields of ionospheric detection technology in China were also given.
Radar-Embedded Communication Waveform Design Based on Parameter Optimization
Authors: Liu Yiyuan , Li Baoguo , Yao Yizhou 
Published: December 2022

Abstract
Radar-embedded communication (REC) is a low probability of intercept (LPI) communication method that enables radar and communication to share the spectrum. Covert communication is accomplished by embedding low-power communication waveforms in high-power radar backscatter echoes. This research, by optimizing the eigenvalue matrix power exponent a of the shaped dominant projection (SDP) waveform, proposes an SDP waveform with variable eigenvalue matrix power exponent, namely SDP-a waveform. Then, the reliability of waveform communication and LPI performance are theoretically analyzed by processing gain. Finally, the simulation experiments are carried out with SDP-0.25, SDP-0.5, and SDP-0.75 waveforms as examples. The experimental results are consistent with the theoretical analysis results, indicating that the optimization of the eigenvalue matrix power exponent can meet the performance requirements of different aspects.
Research on Non-Contact Electricity Inspection Technology of Unmanned Aerial Vehicles
Authors: Wang Hui , Zhang Haitao , Chang Junting , Guo Yang , Ma Xiaolong , Wang Yongquan 
Published: December 2022

Abstract
The airborne non-contact electroscope developed in this paper does not need to touch the tower and can be remotely controlled to complete the electroscope. It can be widely used in the maintenance operation of various voltage levels, and the entire operation process is in line with the State Grid Corporation of China Electric Power Safe work regulations (power line part) regulations. The application of the device can effectively reduce the labor intensity of the operators, improve the operation efficiency, and ensure the safety of the operation.
Real-time Monitoring Platform for Transmission Line Trips Based on Data Mining
Authors: Diao Haoran , Zhou Zhifeng , He Xiqi 
Published: December 2022

Abstract
In order to improve the correctness of the judgment of transmission line tripping and the response efficiency of monitoring, data mining technology is introduced to carry out the research of real-time monitoring platforms for transmission line tripping. The required hardware of the monitoring platform includes an electromagnetic induction sensor, a clock chip, memory and the like. A hardware framework structure of the real-time monitoring platform is constructed on the basis of the hardware. Compressed sensing is carried out on a transmission line trip monitoring signal by using a data mining technology; and finally, real-time monitoring is carried out on the operation of the transmission line, and an alarm is carried out according to the relative importance of the trip. The practical application performance of the new monitoring platform is verified by comparative experiments. The experimental test shows that the proposed platform can ensure the correctness of monitoring and has faster monitoring response efficiency.
Building a Unified Spatio-Temporal Data Model for Grid Resources Based on Microservice Architecture
Authors: Dai Haoqi , Chen Yuxu , Ren Haowen , Li Xiaolu , Ao Zhiqi 
Published: December 2022

Abstract
Under the background of accelerating the process of power grid construction, the unified spatial-temporal data model of power grid resources has become a necessary means to describe the relationship between spatial objects and power grid data. Affected by the defect of the information island, some unified spatiotemporal data models of power grid resources have poor updating performance. Therefore, a unified spatiotemporal data model of power grid resources based on microservice architecture is designed. The architecture can obtain the spatial structure elements of the power grid area, identify the spatial correlation characteristics of the modeling object through the distribution of power energy supply lines, eliminate the dimension of meteorological data variables, design a unified resource scheduling scheme based on the microservice architecture, calculate the space-time weight matrix, and build a space-time data model. Test results are that under the two update task scenarios, the average update performance of the unified spatiotemporal data model of power grid resources based on the Internet of things is 11363 times/second. The average update performance of the unified spatiotemporal data model of power grid resources based on the Internet of things is 9958 times/second). And the average update performance of the unified spatiotemporal data model of power grid resources based on the genetic algorithm is 9771 times/second. It shows that the designed unified spatiotemporal data model of power grid resources is perfect after combining the microservice architecture.
A Distributed Adaptive Control Model for Microgrids with a Microservice-oriented Architecture
Authors: Cao Xiaoming , Zhang Huabing , Shi Hongyu 
Published: December 2022

Abstract
In the face of increasingly complex application conditions, some distributed adaptive control models for microgrids suffer from large differences between voltage magnitudes and rated values. To address such shortcomings, a distributed adaptive control model for microgrids is designed for a microservice architecture. The mathematical expressions of the state integral control variables and control input variables under steady-state conditions are derived by extracting the integral control variables of the distributed generation units of the microgrid, and the current at the end of the line short circuit is used as the database to design the current quick-break protection mechanism for the microservice architecture. Experimental results is that the voltage magnitude of the distributed adaptive control model of the microgrid in the paper is 317.71V, which is closer to the rated output voltage value of 320V, indicating that the distributed adaptive control model of the microgrid is better when the microservice architecture is fully utilized.
Transformer Connection Terminal Registration Based on Objective Function
Authors: Dai Jianzhuo , Zhang Sicong , Tao Jiagui , Hu Kaifeng 
Published: December 2022

Abstract
In recent years, the traditional ICP algorithm has high requirements for the initial position of point clouds, and low registration ability for point clouds with low overlap. The Microsoft Kinect depth sensor was used to obtain the point cloud data of the target object from the real scene. Then, pre-processing such as point cloud segmentation, filtering and down sampling. In the coarse registration, the feature point sampling consistency algorithm was used to make the point cloud obtain a better initial position. Finally, a point-to-surface ICP algorithm optimized by linear least squares was proposed in the fine registration. The experimental results show that the root mean square error of the improved algorithm is 0.761mm and the time is 52.32ms. Compared with the ICP algorithm based on SIFT feature points and the improved ICP algorithm based on feature point sampling consistency, the registration accuracy of the improved algorithm is increased by 21.0% and 43.3%, and the speed is increased by 18.9% and 30.2%.
Research on Efficient Detection Method of Foreign Objects on Transmission Lines Based on Improved YOLOv4 Network
Authors: Shan Hua , Song Yu , Wang Hongxing , Chen Yuquan 
Published: December 2022

Abstract
The normal operation of transmission lines is one of the basic guarantees for industrial development. The foreign object on the transmission line is one of the main reasons for the failure of the transmission line, which brings huge economic losses to the society. The traditional method has the problem of low accuracy and slow speed. The detection and identification of foreign objects on transmission lines are beneficial to the maintenance of huge economic benefits. Therefore, cloud-edge technology is introduced into this study, and a monitoring model for foreign objects on transmission lines in complex scenarios based on an improved YOLOv4 network is proposed. The feature extraction module of the YOLOv4 model is improved based on the GhostNet network to speed up the detection of foreign objects. The SPP module in the YOLOv4 network is improved to enhance the accuracy of detection and identification of foreign objects on transmission lines. The accuracy and speed of the detection of foreign objects tested are 99.2% and 218ms, respectively. The experimental results can meet the needs of real-time detection.
A new approach for calculating the average frequency of power system based on the identification of regional inertia center nodes
Authors: Wan Zhonghui , Liu Fusuo , Wu Xuelian 
Published: December 2022

Abstract
The grid structure of the modern power system is complex and the space span is large. When the power system is disturbed to generate unbalanced power, the transient distribution process among the various synchronous units leads to the spatiotemporal distribution characteristics of the frequency response of the system. By measuring the generator Frequency and Inertia, the inertia center frequency can be calculated. Based on the two-generator system, the relationship between generator frequency and bus frequency is analyzed. A method for selecting the frequency inertia center node of the local power grid in the power system is proposed, and the inertia center frequency of the system is estimated based on the measured frequency at this point. Taking 10 machines and 39 nodes as an example, the simulation calculation is carried out to verify the effectiveness of the proposed method.
Cogging Torque Reduction of Permanent Magnet Motor Based on Particle Swarm Optimization Algorithm
Authors: Zhang Linsen , Tang Bo , Tan Siwei , Ning Xiaoling 
Published: December 2022

Abstract
The permanent magnet motor will inevitably produce cogging torque because of its inherent structure, which will cause vibration and noise and affect its application in certain high-precision applications. Firstly, considering the actual cogging structure of the stator, a general analytical model of cogging torque of the permanent magnet motor is obtained by the energy-based approaches. On the basis of the further derivation of cogging torque analytical expressions with different segmented pole structures, a cogging torque combination reduction method is presented based on the particle swarm optimization algorithm, by comprehensively optimizing three different combinations of the opening width of stator slot, the calculating pole arc coefficient and the number of PM pole segments, the method can reduce the “peak-to-peak value” of cogging torque. The finite element analysis (FEA) results prove the validity of the proposed method.
An Improved Dynamic Smooth Weighted Round-robin Load-balancing Algorithm
Authors: Gao Chenhao , Wu Hengyang 
Published: December 2022

Abstract
Load-balancing is a key component of highly available network infrastructure. Weighted round-robin is one of the important strategies to achieve load-balancing, which is a classic research subject. In recent years, the weighted round-robin algorithm has developed from static weight to dynamic. The Dynamic weighted round-robin algorithm needs further research in time-sensitive of dynamic weights and the rationality of results. Based on Nginx, this paper improves the dynamic weighting algorithm. Firstly, it proposes a method of dynamically calculating weights. The method determines the weight of the server in the cluster according to its theoretical performance and runtime state. Secondly, making the request allocation result more balanced and avoiding continuous centralized scheduling by an improved weighted algorithm. Experiments show that the algorithm proposed in this paper is effective and can improve system performance and load-balancing efficiency.
Large-Scale Power Cloud Resource Scheduling Algorithm in an Edge Computing Environment
Authors: Huang Xiang , Liang Zhihong , Zhang Qiankun , Mo Jianfeng , Zhao Lei 
Published: December 2022

Abstract
Aiming at the problem that the current power cloud resource scheduling is inefficient and time-consuming, a large-scale power cloud resource scheduling algorithm in an edge computing environment is proposed. Firstly, the resource management method of large-scale power clouds is optimized. Considering the resource sharing and task scheduling security requirements between secondary nodes, and combined with edge computing technology, the resource distribution management and scheduling algorithm of the power cloud are optimized. Finally, the experiment proves that the resource scheduling time of a large-scale power cloud resource scheduling algorithm under an edge computing environment is reduced by more than 15 minutes in the actual application process, And the scheduling effect is also better than the traditional method.
Researches Advanced in Human Pose Estimation Based on Deep Learning
Authors: Song Xuzhe 
Published: December 2022

Abstract
Human pose estimation has always been a popular research topic in the discipline of computer vision, which aims to predict the spatial position of the human body’s key points (parts/joints) from a given image or video. Benefiting from the powerful feature representation ability of the convolutional neural networks, the pose estimation methods based on the deep learning have become the mainstream framework of this task, which obtain the human pose estimation results by extracting the human pose feature information at different scales with specific neural networks and using the corresponding methods to process it. This paper, based on the depth study of human body posture estimation can be divided into single-task and multi-person missions. The time and method of correlation are classified and summarized, respectively from the network architecture, algorithm and feature extraction of performance that are analyzed. The current problems existing in the research field and methods are summarized, and the research prospect for the future has been prospected.
Image Super-Resolution via Multi-scale Channel Attention Residual Network
Authors: Yang Caidong , Sun Fangwei , Li Chengyang , Zhou Heng , Du Ziwei , Li Zhongbo , Xie Yongqiang 
Published: December 2022

Abstract
The refinement of existing CNN-based Super-resolution Reconstruction (SR) networks mainly focuses on deeper network architecture, which hinders the transmission of information in the networks. A deeper network is unable to make full use of intermediate correlation features and makes the training of the network difficult. To solve these problems, we propose a multi-scale channel attention residual network (MCAR). Specifically, we propose a multi-scale channel attention fusion module (MCAF) to learn local and global channels feature and capture the long-range dependencies. Furthermore, the multi-scale block is adopted to get the different scale feature representations. The experimental results on four benchmark datasets demonstrate that our models can effectively improve the visual effect of images, and outperform most of the advanced SISR methods in PSNR and SSIM.
Expansion Dynamic and Characterization of Stagnation Layer in Laterally Colliding Plasmas: Dependence of Observation Bandwidth and Plasma Plume Separation
Authors: Al-Juboori Haider M. , McCormack Tom 
Published: December 2022

Abstract
The colliding laser-produced plasma (CLPP) has a wide range of applications in various contexts, that might start with astrophysical applications or pulsed laser deposition or Laser-Induced Breakdown Spectroscopy (LIBS), which is a powerful analytical technique for elemental analysis and material identification.
In CLPP experiments, the stagnation layer might form at the interface region when two dense laser-induced plasmas collide, and the degree of stagnation can be diagnosed by the collisionality parameter that is used to determine what kind of interaction will take place, i.e., soft or hard stagnation.
Our experimental work presents the results of the temporal, spatial and semi-spectrally imaging of colliding plasmas of aluminium and silicon targets. The analysis is focused on describing the velocity of the expanding plasma front for the interaction zone. The aim of the work presented here is to further advance and study colliding plasma techniques, as well as other methods to realize and control species density and expansion, with a view to a deep understanding of these complex mechanisms and optimising emission in the visible wavelength range.
All investigation sequences were based on a similar experimental setup, where two different focusing lenses were used with an effective focal length (EFL) of approx. 100mm or 125mm to achieve seed separation around 1.66mm or 2.16mm, respectively. Time-resolved emission imaging was employed to track the stagnation layer‛s size and shape, which might act as a signature of hard versus soft stagnation.
The study provides a considerable amount of detailed data related to the expansion velocity of the interaction zone which extends the understanding of the behaviour of particular species within colliding laser-produced plasmas.
Meibomian gland loss area and its relationship with eyelid margin hyperemia and meibomian gland orifice plugging
Authors: Garcia-Queiruga Jacobo , Sabucedo-Villamarin Belén , Pena-Verdeal Hugo , Garcia-Resua Carlos , Giraldez M. Jesus , Yebra-Pimentel Eva 
Published: December 2022

Abstract
Purpose: The aim of the present study was to state a relationship between the meibomian gland loss area (MGLA), eyelid hyperemia and meibomian gland (MG) orifices plugging in a sample of university students. Material and methods: A total of 74 participants were recruited. Meibography images were obtained with the OCULUS® Keratograph 5M and MGLA was calculated using the ImageJ software; also, MGLA was categorized following the Meiboscale into 4 groups: group 1 (<25%), group 2 (25-50%), groups 3 (50-75%), and group 4 (>75%). An exhaustive slit lamp examination of both eyelids was performed. Eyelid margin hyperemia and MG orifices plugging of each eyelid were categorized following Arita et. al grading scales. Results: A significant statistical relationship was found between MG orifices plugging and MGLA for both eyelids (Fisher’s exact test; both p < 0.019). Also, correlations were obtained between lower MGLA and lower MG orifices plugging (Cramer-V = 0.583, p ≤ 0.001); and between upper MGLA and upper eyelid margin hyperemia (Cramer-V = 0.418, p = 0.023), and upper MG orifices plugging (Cramer-V = 0.413, Fisher’s exact test: p = 0.042). Conclusion: MGLA varies depending on MG orifices plugging in upper and lower eyelids; also, in upper eyelids MGLA was correlated with eyelid hyperemia.
Pressure and Angle Sensors with Optical Fiber for Instrumentation of the PrHand Hand Prosthesis
Authors: Arco Laura De , Pontes María Jose , Segatto Marcelo Eduardo Viera , Monteiro Maxwell E. , Cifuentes Carlos A. , Díaz Camilo A. R. 
Published: December 2022

Abstract
The principal cause of upper limb amputations is due to traumatism. The prosthesis is an assistive device to help in the activities of daily for the amputee person. However, one of the latest reports shows that in developing countries there are around 30 million people without assistive devices. This work presents the development of two kinds of sensors for the PrHand, an upper limb prosthesis based on compliant mechanism and soft-robotics. The sensors are made with polymeric optical fiber (POF), due to their flexibility and low cost, and the working principle is based on intensity variation. The angle sensors are used for monitoring the interphalangeal joint of the fingers, and for the assessment were made cycles of closing and opening each finger. On the other hand, the force sensors are located at the tip of three fingers to track the force made over the objects. Before encoring the sensors were evaluated making five cycles of compressing and decompressing each sensor. The results show a linear behavior between the angle and the voltage variation, one most remarkable angle sensor result was with a sensibility of 0.0357 V/° and an R2 of 99 % closing and 0.0483 V/° opening. In the case of the force sensor, a polynomial relation was found between the voltage changes and the pressure over the sensor; in some cases, the relation between voltage changes and pressure could be linear but that depends on the construction of the sensor. Regarding the obtained R2 of 99 %, its sensibility was 0.0361 V/N compression and 0.0368 V/N decompression. In conclusion, was successfully developed two kinds of sensors for the instrumentation of PrHand prosthesis. It is expected to use angle and sensor variables as input in algorithms of Machine Learning to improve the detection of objects. One aspect to improve is to control in a better way the sensor construction parameters due to the considerable influence over the sensor behavior.