bluuebunny/crossref_metadata_2025_split huggingface dataset:
Grid-connected inductor design of static var generator for photovoltaic system
Authors: Xu Weijun 
Published: March 2023

Abstract
With the access of high-proportion photovoltaic power stations and the development of high permeability power electronic power systems, the problem of distributed photovoltaic access voltage over-limit and power factor is becoming more and more prominent, and the static var generator (SVG) is an important equipment to solve this kind of problem. As a key component of the static var generator, the connecting inductor has the functions of storing energy, bidirectional feeding, adjusting the phase of the output current, and suppressing the high-order harmonic current. It not only affects the dynamic and static response of the device but also restricts the output power, power factor, and DC side voltage of the SVG. At present, the parameter selection of SVG connection inductance is from the perspective of harmonic characteristics and economy, and there is no actual theoretical calculation basis. From the perspective of SVG output capacity and modulation ratio, the upper limit of the value of the connection inductance is derived. Combined with the traditional lower limit of the inductance when the harmonic suppression condition is satisfied, a design method of SVG connection inductance is given. Finally, the simulation results show that the connection inductance value designed by this method is correct and reasonable.
Short-term Wind Speed Forecast Using ARIMA Based on EEMD Decomposition
Authors: Wang Jinhui , Wang Juanjuan 
Published: March 2023

Abstract
Wind speed prediction of the wind power plant has an important influence on the stability and safe operation of the power system. Because the wind speed series is intermittent and random, a combination model of EEMD-ARIMA is proposed to predict ultra-short-term wind speed. The advantage of the prediction model mentioned in this paper is to deal with the problem of large prediction errors caused by the instability of the original wind speed series. First, the ensemble empirical mode decomposition (EEMD) is used to decompose the series, and then the autoregressive moving average (ARIMA) is used to predict the components. Through the example analysis, it can be seen that the prediction model mentioned in this paper is more accurate than the traditional ARIMA model in predicting short-term wind speed.
Active and Reactive Power Coordination Optimization of the Active Distribution Network
Authors: Deng Guohao , Wang Dang , Gao Weixin 
Published: March 2023

Abstract
The operation and control of the active distribution network are faced with great challenges due to a mass of tunable and controllable devices connected to the network, resulting in large active power loss and voltage deviation. In this paper, a method of active and reactive power coordination optimization for the active distribution network based on a one-dimensional convolutional neural network (1D-CNN) is proposed. This method can mine valuable information from the historical data of distribution networks, and use one-dimensional convolutional neural networks to map the complex nonlinear relationship between node load and optimization strategy. The simulation results of the modified IEEE33 node distribution network system show that the active power loss and the node voltage deviation of the proposed method are significantly reduced.
FPGA-based LoongArch Five-stage Pipeline CPU
Authors: Chen Lin , Ma Xiao , Ji Xiang 
Published: March 2023

Abstract
We designed and implemented a five-stage pipeline CPU based on the FPGA platform, programmed in Verilog hardware description language to implement LoongArch architecture. The design and implementation of the Instruction Fetch (IF) stage, Instruction Decode (ID) stage, Instruction Execute (EX) stage, Memory Access (MEM) stage, and Write Back (WB) stage. The design and implementation of the important modules in the pipeline are given. The use of the Bubble method and Bypass technique solves most of the parameter passing problems and branch judgment problems in the pipeline. The access memory problem is solved using design tricks. Finally, the design is verified on an FPGA platform. The CPU design can be well used in learning and research related to pipeline CPUs. It can also support experimental platforms and provide an example for further research in pipelines and SOCs.
Design of Civil Aircraft Radome Based on Lightning Protection
Authors: Wang Yi , Gao Ji , Zhang Xiaogang 
Published: March 2023

Abstract
According to relevant statistics, an aircraft will encounter lightning every 3000 hours on average. According to relevant research, the vast majority of aircraft encounter lightning during falling or climbing. For lightning protection of composite radome, there are usually measures such as metallization treatment on the surface, the layout of lightning protection diversion strips, etc., to avoid lightning on the radome by guiding the flash current.
3-PRRR parallel mechanism kinematics and workspace analysis
Authors: Zheng Zehua , Zhang Yi , Wu Yuan , Li Yongxing 
Published: March 2023

Abstract
Aiming at the current problems of small working space and the high cost of erection of parallel structure FDM-3D printer, a 3-PRRR parallel mechanism with a common line of branch chain moving sub is proposed and planned to be used in 3D printing equipment. First, the degrees of freedom of the 3-PRRR parallel mechanism is analyzed based on the spiral theory, and the positive and negative solutions of the position of the mechanism are established by the vector method; on this basis, the working space of the mechanism is analyzed using the Monte Carlo method; finally, the mechanism is specifically applied to the FDM- 3D printing device.
Mechanism Analysis of PET
Authors: Huang Xinwei 
Published: March 2023

Abstract
With the application of distributed power sources, power electronic transformer (PET) that can be connected to DC and AC power grids has attracted much attention. This article will design a PET and simulate its performance when it is connected to the grid.PET consists of three inverters. This article will design and simulate AC-DC and DC-AC inverters, and analyze their principles and performance. Then three inverters are combined into PET, so that the conversion performance of PET to voltage can be simulated and evaluated.
A Novel Topology Identification Algorithm Fusing Multi-Source Measurement Data in Distribution Network
Authors: Zhang Yanyu , Liu Jingyi , Huang Yuchun , Zhang Bin , Pan Jinyuan 
Published: March 2023

Abstract
With the development of new power systems, large amounts of decentralised clean energy and flexible loads will be connected to the smart grid, making the topology of the distribution network even more complex. At the same time, the demand for efficient interaction of “source-network-load” also makes the distribution network topology change with time, which makes it more difficult to identify the distribution network topology. However, topology identification is the basic data for power system regulation and safe optimal operation. Considering the above problems and requirements, this paper investigates and proposes a novel method to identify the topology of a distribution network based on the collaboration of data from multiple measurement devices. Firstly, a method based on multi-source data time synchronization method of μPMU measurement data is proposed, and generate additional data based on linear extrapolation to expand the available data set. Then, a method of topology optimization model identification based on least square method is proposed. Finally, the proposed algorithm is simulated in an example of the IEEE 33 bus feeder system standard. The results show that the scheme is effective in identifying the topology of the distribution network and improves the accuracy compared to traditional methods.
Robot grasping system based on deep learning target detection
Authors: Zhao Wenhui , Xu Bin , Wu Xinzhong 
Published: March 2023

Abstract
The traditional robot grasping system often uses fixed point grasping or demonstrative grasping, but with the increase in the diversity of grasping targets and the randomness of poses, the traditional grasping method is no longer sufficient. A robot grasping method based on deep learning target detection is proposed for a high error rate of target recognition and low success rate of grasping in the robot grasping process. The method investigates the robotic arm hand-eye calibration and the deep learning-based target detection and poses estimation algorithm. The Basler camera is used as the visual perception tool of the robot arm, the AUBO i10 robot arm is used as the main body of the experiment, and the PP-YOLO deep learning algorithm performs target detection and poses estimation on the object. Through the collection of experimental data, several grasping experiments were conducted on the diversity of targets randomly placed in the poses under real scenes. The results showed that the success rate of grasping target detection was 94.93% and the robot grasping success rate was 93.37%.
Industrial Boiler Intelligent Monitoring System Based on LabVIEW
Authors: Ji Yuan , Chen Heng , Shi Xianwei 
Published: March 2023

Abstract
As a kind of traditional heating and power equipment, the industrial boiler is more and more applied in industrial production and life. However, due to the uneven heating of the boiler, the process of using the boiler would result in boiler leakage accidents and cause burns to workers. Given the above situation, the intelligent control system of the industrial boiler is studied in this paper to achieve safe and stable operation of the boiler. This design uses the distributed thermocouple temperature measurement method to design the boiler safety warning system based on the thermocouple sensor collaborative monitoring. Multiple sensors are used to cooperatively monitor and collect boiler operating signals. COMSOL model is used to realize 3D temperature field simulation and reconstruction inside the furnace lining, and the results are presented as early warning results through LabVIEW upper computer interface, which solves the shortcomings of low acquisition accuracy, narrow measurement accuracy, and single measurement method of the traditional contact measurement method. The practice shows that the system has the advantages of low cost, convenient installation and maintenance, easy expansion, high reliability, and strong anti-interference.
Interval Harmonic Power Flow Algorithm Based on Relative Distance Measure
Authors: Fang Xiaoling , Lan Jinchen , Lin Yan , Wu Danyue , Xu Shuangting , Yang Jiaye , Chen Yihuang 
Published: March 2023

Abstract
In the harmonic power flow calculation of the power grid, the indeterminacy of new energy generation, the volatility and intermittency of nonlinear load will lead to the uncertainty of the injected harmonic current. In order to deal with the uncertainty information in the power grid, relative distance measurement (RDM) is used instead of point values to describe the uncertainty of distributed generations(DGs) output and state variables. In this paper, the RDM harmonic source model is built to solve the interval harmonic power flow. Through a typical 33-node distribution network calculation example, it is testified that the RDM Power flow algorithm has sufficient completeness and low conservatism compared with the traditional interval algorithm and Monte Carlo method.
A Study of Prediction of Ground Settlement of Shield Tunnel Based on EEMD-BO-GRU Algorithm
Authors: Ma Xufei , Xu Yingshun , Yang Jie , Wu Jian , Tong Fei , Song Jintao 
Published: March 2023

Abstract
Because the finite element method cannot meet the needs of shield tunnel engineering, multiple linear regression and traditional machine learning algorithms are difficult to effectively solve the shield tunnel’s nonlinear and non-stationary ground surface settlement data. Based on the Gated Recurrent Unit (GRU) algorithm of Ensemble empirical mode decomposition (EEMD) and Bayesian optimization (BO), this paper puts forward a prediction method of ground surface settlement during shield tunneling. Taking the shield tunnel construction of Zhijiang Road in Hangzhou as an example, by comparing with the traditional machine learning algorithm, the results show that RMSE, MAE, and MAPE of this algorithm are increased by 1.9313 mm, 1.7526 mm, and 4.9553%. It can be explained that this method has higher prediction accuracy and a more stable prediction effect, and the EEMD algorithm can effectively improve the generalization ability of the algorithm.
Communication Interference Signal Recognition Based on Complex Number Convolutional Neural Network
Authors: Chen Yazhong , Shan Jingmiao , Zhang Chuanhao 
Published: March 2023

Abstract
Modern wireless communication systems are facing an increasingly complex electromagnetic environment, which is affected by a variety of noise and interference signals. In the communication process, if the communication party can effectively identify the type of interference signal, it can take corresponding anti-interference measures to avoid or suppress interference to the maximum extent and reduce the damage of interference to communication quality. In recent years, with the continuous development of deep learning and its outstanding performance in image and speech processing, it has been verified that deep learning has extremely strong nonlinear mapping and data expression capabilities, inspiring researchers to apply deep learning to the field of communication anti-jamming, and improving the antijamming capability of the system. In this paper, an algorithm of interference signal recognition based on a complex convolution neural network is proposed. It also introduces the network architecture. Next, six typical interference signals at each level are identified, and the results are analyzed. The last chapter of the paper summarizes the full text. The experimental results show that the recognition ability of the interference signal recognition algorithm proposed in this paper is better than that of the traditional convolutional neural network.
The design of a manipulator drive system based on the main control chip
Authors: Wang Zhuolin 
Published: March 2023

Abstract
This paper mainly studies and designs the control system of a four-degree-of-freedom manipulator. As a motion control system, the control system is mainly oriented to the bottom, striving to develop an industrial manipulator system with high stability, strong reliability, and accurate positioning. Firstly, according to the control requirements of the mechanical arm system, a single CPU system control scheme is designed as a whole, that is, to control the steering gear rotation by controlling the duty cycle of the PWM wave output by the central controller, to achieve the position control of each joint. In terms of hardware, the main components are ARM microprocessor STM32F103ZET6, MG995 steering gear, MG945 steering gear, ultrasonic sensor, and power module. The joint motion control system is built by building a hardware platform and designing a software control program. In software design, the control program is divided into an initialization module and an operation module according to the modular design idea, and the program of each module is designed separately.
Monitoring System of Rare Earth Electrolysis Equipment Based on OPC UA Technology
Authors: Chen Jie , Liu Feifei , Wen Zhenxin , Zhou Dong 
Published: March 2023

Abstract
A set of rare earth electrolysis equipment monitoring systems based on OPC unified architecture is proposed given the complex environment of the rare earth electrolysis workshop, the difficulty of data acquisition, and the interconnection between equipment. The monitoring client of rare earth electrolysis equipment based on OPC UA communication protocol is designed and developed with C # language. The connection between the OPC UA server and the monitoring system is realized, and the data acquisition and real-time monitoring of the running state of the electrolysis equipment are completed. The primary goal of the rare earth electrolysis field equipment is to acquire and monitor rare earth electrolysis process current, voltage, and other internal state data in real-time.
System development of silicon photonics links for CERN experiments and accelerators
Authors: Scarcella C. , Detraz S. , Lalović M. , Marcon L. , Olanterä L. , Prousalidi T. , Sandven U. , Sigaud C. , Soós C. , Troska J. 
Published: March 2023

Abstract
Future upgrades of the CERN Experiments and Accelerators require optical links capable of handling the large data volume generated in particle detectors and beam position (BPMs) sensors. Silicon Photonics optical transceivers are a promising candidate to process the required data rate as well as efficiently operate in the harsh radiation environment. We present the experimental characterisation of silicon modulators together with demonstration of optical transmitters based on custom designed Silicon Photonics integrated circuits.
An AB-BNCT epithermal neutron source using 7Li(p,n)7Be reaction
Authors: Wang Y.Q. , Du J.L. , Lin H. , Zhou X.Ch. , Lin C. , Qiu J. , Li J.Y. , Guan X.C. , Gu L. 
Published: March 2023

Abstract
A suitable neutron source is indispensable for boron neutron capture therapy (BNCT). This article proposes a design of beam shaping assembly (BSA) for an accelerator-based BNCT (AB-BNCT) epithermal neutron source facility using 7Li(p,n)7Be reaction, and the results show that all parameters of BSA meet the recommended values of International Atomic Energy Agency (IAEA). The dose distribution and parameters in the Snyder head phantom are calculated using the Monte Carlo simulations to evaluate the performance of the epithermal neutron beam.
A novel method for assessing imaging quality of coded-aperture gamma-ray camera to radioactive plane source
Authors: Zhao Mingyang , Wang Zhonghai , Zhu Balin , Bai Lixin , Zhou Rong , Yang Chaowen 
Published: March 2023

Abstract
With the wide application of the coded-aperture gamma-ray
camera in the field of nuclear radiation monitoring, research on its
imaging performance of radioactive point sources has increasingly
matured. However, because of the difficulty in obtaining complex
radioactive plane sources with specific activity distributions,
there is a lack of experimental research on imaging performance of
such sources currently, the main focus being on simulation research
and on-site imaging trials. In addressing the issue, we proposed a
method to assess image quality of coded-aperture gamma-ray camera to
such sources, and performed imaging experiments with a custom-made
gamma-ray camera. Driven by a two-axis computer-numerical control
(CNC) motion platform, a point source was moved through prescribed
paths at a given velocity, from which a custom activity distribution
plane source for coded-aperture imaging was constructed. Peak
signal-to-noise ratio and structural index similarity were the two
indicators used to evaluate the imaging quality of the plane source
for seven distinct shapes. The results indicate that the imaging
quality of the plane source imaged by our custom-made camera and
constructed using our method is excellent with these two indicators
being better than 17 dB and 0.996, respectively. Our method
provides good reliability and practicality, and offers an
alternative approach for assessing imaging quality of coded-aperture
gamma-ray camera for complex radioactive plane sources.
Oil adsorbing and transporting surfaces: a simulative determination of parameters for bionic functional textiles
Authors: Wagner Jan , Akdere Musa , Gürbüz Kevser , Beek Leonie , Klopp Kai , Ditsche Petra , Mail Matthias , Gries Thomas , Barthlott Wilhelm 
Published: March 2023

Abstract
Certain superhydrophobic plants, such as Salvinia molesta, are able to adsorb oil films from water surfaces and thus separate the oil from the water. There are first attempts to transfer this phenomenon to technical surfaces, but the functional principle and the influence of certain parameters are not yet fully understood. The aim of this work is to understand the interaction behavior between biological surfaces and oil, and to define design parameters for transferring the biological model to a technical textile. This will reduce the development time of a biologically inspired textile. For this purpose, the biological surface is transferred into a 2D model and the horizontal oil transport is simulated in Ansys Fluent. From these simulations, the influence of contact angle, oil viscosity and fiber spacing/diameter ratio was quantified. The simulation results were verified with transport tests on spacer fabrics and 3D prints. The values obtained serve as a starting point for the development of a bio-inspired textile for the removal of oil spills on water surfaces. Such a bio-inspired textile provides the basis for a novel method of oil–water separation that does not require the use of chemicals or energy. As a result, it offers great added value compared to existing methods.
Optimality of the triangular lattice for Lennard–Jones type lattice energies: a computer-assisted method
Authors: Bétermin Laurent 
Published: March 2023

Abstract
It is well-known that any Lennard–Jones type potential energy must have a periodic ground state given by a triangular lattice in dimension 2. In this paper, we describe a computer-assisted method that rigorously shows such global minimality result among 2-dimensional lattices once the exponents of the potential have been fixed. The method is applied to the widely used classical

(
12
,
6
)

Lennard–Jones potential, which is the main result of this work. Furthermore, a new bound on the inverse density (i.e. the co-volume) for which the triangular lattice is minimal is derived, improving those found in (Bétermin and Zhang 2015 Commun. Contemp. Math.
17 1450049) and (Bétermin 2016 SIAM J. Math. Anal.
48 3236–3269). The same results are also shown to hold for other exponents as additional examples and a new conjecture implying the global optimality of a triangular lattice for any parameters is stated.
Effects of rod radius and voltage on streamer discharge in a short air gap
Authors: FU Yuwei , HE Mengsha , CHEN Chi , WANG Chuang , ZHANG Zaiqin 
Published: March 2023

Abstract
Streamer discharge is the inaugural stage of gas discharge, and the average electron energy directly determines the electron collision reaction rate, which is a key parameter for studying streamer discharge. Therefore, taking into account the average electron energy, this work establishes a fluid chemical reaction model to simulate and study the course of evolution of a streamer discharge in a 5 mm rod–plate gap, considering 12 particles and 27 chemical reactions. It introduces the electron energy drift diffusion equation into the control equation, and analyzes the temporal and spatial changes of average electron energy, electric field intensity and electron density with change in rod radius and voltage. The effects of voltage and rod radius on the course of streamer discharge can be reflected more comprehensively by combining the average electron energies. Three different values of 0.3 mm, 0.4 mm and 0.5 mm are set for the rod radius, and three different values of 5 kV, 6 kV and 7 kV are set for the voltage. The influence of an excitation reaction on the streamer discharge is studied. The findings indicate that, as voltage raises, the streamer head’s electron density, electric field and average electron energy all rise, and the streamer develops more quickly. When the rod radius increases, the electron density, electric field and average electron energy of the streamer head all decrease, and the streamer’s evolution slows down. When an excitation reaction is added to the model, the average electron energy, the magnitude of the electric field and the density of electrons decrease, and the evolution of the streamer slows down. An increase in average electron energy will lead to an increase in electric field strength and electron density, and the development of the streamer will be faster.