bluuebunny/crossref_metadata_2025_split huggingface dataset:
Key Technologies and Development Status of Smart City
Authors: Zhong Yuanchang , Sun Lili , Ge Chenhao 
Published: February 2021

Abstract
In the 21st century, the rapid development of Internet information technology has provided a trend and direction for breaking the construction concept of traditional cities and building new smart cities. However, with the rapid development of smart cities, timely attention and research on the key technologies and development status of global smart cities, so as to provide directions and references for the further research of smart cities, has become a research hotspot of smart cities in the new century. Firstly, this paper studies the development status of smart cities by studying a large number of domestic and foreign literatures. Secondly, it further studies several key technologies and their development status. Through the research, it is concluded that the rapid development of smart cities at the present stage has achieved outstanding achievements in various application fields of smart cities, but it is urgent to break the bottleneck of key technologies and help the further development of smart cities by combining with the application of key technologies of smart cities in the new era.
Speed sensorless control of permanent magnet synchronous motor based on robust adaptive algorithm
Authors: Wang Zeng Hui , Zhang Jun Hong , Zhang Yin Heng , Xiao Huan Yu , Zhang Xiao Chen 
Published: February 2021

Abstract
In order to solve the problem that the parameters of the regulator and the actual parameters do not match due to the time-varying motor parameters in the operation of PMSM, this paper adopts a robust adaptive control strategy based on linear matrix inequality (LMI) based on the model reference adaptive method (MRAS) to consider the uncertainties of the motor parameters in the state equation of the motor control system, the controller parameters are obtained by solving the LMI. The simulation model of PMSM speed sensorless control system is built in Simulink. The simulation results show that the system can track the given speed well and has strong robustness when the motor parameters change.
PCCPS-PWM based vehicle-network high frequency resonance suppression method
Authors: Ding Yong , Wang Tiesheng , Zhang Xinyu , Zhang Yuxi , Miao Yifei 
Published: February 2021

Abstract
In recent years, the safe and stable operation of electrified railways has attracted more and more attention. In particular, the stability of vehicle-grid coupling, which focuses on the phenomenon of vehicle-grid high frequency resonance (HFR), has become a hot research topic. Based on the instability mechanism of vehicle-grid coupling, and from the perspective of grid-side converter modulation strategy, measures to suppress HFR are further proposed. Based on the improvement of commonly used modulation strategies, Periodic Control Carrier Phase-Shift Pulse Width Modulation (PCCPS-PWM) is proposed, this solves the HFR problem caused by the switching characteristic frequency harmonics caused by the inaccurate phase shift angle between the grid-side converters. And it is verified by Matlab simulation and hybrid electric train sets.
A design of self-learning intelligent infrared remote controller
Authors: Lu An , Gong Yingkun , Xiong Deyi 
Published: February 2021

Abstract
This paper presents a self-learning intelligent infrared remote control system for Android system. In this paper, STM32F103RCT6 chip is selected as microprocessor, infrared integrated receiver head VS1838 and infrared light emitting diode are used as infrared receiving/transmitting module. The communication of experimental platform system is established to realize the management and control of household appliances by mobile terminal.
Research on Dual Mode Unified Control Strategy of Grid Connected Inverter Based on Droop Control
Authors: Zhang Ying , Jiang Wei , Wang Xiaohuan 
Published: February 2021

Abstract
There is a big difference between the two modes of grid connected inverter in micro-grid operation. In order to avoid large voltage and current impact, advanced control strategy is needed to realize smooth conversion during operation mode switching. A droop control method based on voltage amplitude change rate is proposed, which is suitable for dual-mode unified control of inverter. While ensuring the stability of the system, the reactive power of the inverter can be accurately shared during islanding operation. This method can realize smooth switching between grid connected inverter and islanding mode. The feasibility of the method is verified by simulation and experiment.
A wireless transmission coupling structure with low electromagnetic force disturbance and stable coupling coefficient
Authors: Xing Zikang , Yan Kui , Han Gao , Li Xiaoping , Liu Yanming 
Published: February 2021

Abstract
In the inductive wireless power transmission, electromagnetic force, which between the primary part and the secondary part, may cause the non-contact free motion and cause bad side effects on transmission. In order to calculate the force, magnetic vector potentials differential equations, based on linear array, are built, and the expression of the electromagnetic force is produced by solving this equation system.
Passivity-based Control of Voltage Source Converter Based On Mixed Sensitivity H∞
Authors: Li Yaxin , Yang Jie , Fang Rengcun , Xu Hanping , Yang Ruixi , Zhang Chengbiao 
Published: February 2021

Abstract
Considering the uncertainty of the control object, this paper aims to design the passivity-based control of voltage source converter based on mixed sensitivity H∞. Firstly, the plant model of VSC converter has been deduced and proved by simulation. Then the controllable of plant has been analyzed. Furthermore, based on mixed sensitivity H∞ theory, the performance weight function and passivity-based control have been designed. Finally, proved by simulation comparison, this control has more accurate and robust dynamic performance than the traditional ac voltage control.
A dust sensor monitoring system using Wi-Fi mesh network
Authors: Guo Zeyu , Ma Xiaolin , Zhang Pei , Liu Zhaoyang 
Published: February 2021

Abstract
This paper proposes a dust sensor monitoring system using Wi-Fi mesh network, including wireless dust sensor node and Wi-Fi mesh networking procedure. The wireless sensor node is made by integrating a dust sensor based on GP2Y1010AU0F chip, a STM32F103ZET6 chip as its MCU, a Wi-Fi module as its wireless transceiver, and a LCD screen as its user-interface. The dust sensor takes the light scattering method, measuring the flash frequency and the duration reflected by particles in the air flow. Dust sensor nodes are networking by Wi-Fi mesh network. Practical experiments validate the effectiveness of the proposed system. The measuring error of dust concentration is less than 5%. As the network is made up of 8-10 nodes, if the root node is disconnected, the network recovery time is less than 9 seconds while the other nodes’ is less than 5 seconds.
Improved Analysis Model of SiC Power MOSFET with Staged Critical Parameters
Authors: Yuan Dakang , Zhang Yiming , Wang Xuhong , Zhang Bin 
Published: February 2021

Abstract
Silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) have great advantages in improving the power density and performance of power converters due to the high switching frequency, high operating voltage. However, the increase in switching frequency is also increasingly inflicted the voltage and current stresses to the parasitic elements of the SiC MOSFET, which restricts the device’s optimal performance. In addition, many parasitic elements of SiC MOSFET are coupled with each other during the switching process, which makes the analysis complicated and calculation cumbersome. This paper presents an analytical model for SiC MOSFETs, which identifies and selectes the dominant elements and key variations of each stage separately according to the change stages of major variables. The complexity of the model is reduced while the accuracy is guaranteed. Using this model, the voltage and current switching rate of SiC MOSFET can be quickly solved, and the impact mechanism of each critical parameter can also be revealed clearly. A double pulse test circuit composed of a 600V/20A SiC MOSFET is set up and experimental results are obtained to verify the accuracy of the proposed analytical model.
Numerical Study on the Influence of Non-uniform Demagnetization of Permanent Magnet Synchronous Motor
Authors: Wu Guopei , Yu Yinquan , Yang Jinwen , Chen Qiping , Zhou Shaowei 
Published: February 2021

Abstract
To study the influence of the non-uniform demagnetization of permanent magnets (PMs) on motor performance, this paper takes a two-phase four-pole Permanent Magnet Synchronous Motor (PMSM) as the research specimen. The influences of torque, phase current, back electromotive force (back-EMF), and radial magnetic density with different grades and types of demagnetization are analyzed. The simulation results show that as the degree of nonuniform demagnetization increases, the output torque and radial magnetic density gradually decrease, on the other hand, the phase current gradually increases. According to the change law of the amplitude of some harmonics of the back-EMF, it can be judged whether the motor has non-uniform demagnetization. This research conclusion can provide a theoretical basis for fault diagnosis of motor demagnetization.
Adaptive climbing motion of snake robot based on joint decoupling and extended Kalman filter
Authors: Xiao Wenyu , Gao Yong , Wei Wu , Zhang Jie , Tan Xiaoman 
Published: February 2021

Abstract
This paper proposes a decoupled gait control function to solve the adaptive transition problem of the snake robot climbing the rod with variable diameter. Firstly, the Sigmoid function is combined with the general gait control function to achieve the decoupling control of the robot joints. Then an adaptive adjustment algorithm of key control parameters is designed based on the extended Kalman filter (EKF) to realize the decoupling gait changes continuously and compliantly as the environment changes. Finally, the physical meanings of the key control parameters are reiterated by simulation, and their influence on the decoupling of climbing gait is analyzed. The smooth transition climbing experiments of the snake robot on rods with different diameters verify the effectiveness of the decoupling and adaptive algorithm.
Replacement Scheme of Drive Boards For Traction Inverter Module of Beijing DKZ31 Metro Vehicle
Authors: Zhang Fan , Zhang Lujun , Liang Shuangqing , Sun Lu , Dai Xiaoteng 
Published: February 2021

Abstract
Nowadays, the status of metro in urban traffic is particularly prominent in Beijing. How to ensure the normal operation of metro train is particularly important. At present, the problems of high failure rate, high maintenance cost and long maintenance cycle exist in the drive boards of imported traction system. In view of the above problems, this paper put forward the alternative scheme of drive boards on DKZ31 metro, and carried out the test work. On the basis of ensuring the safety and reliability, the maintenance cost is greatly reduced and the maintenance efficiency is improved. At present, the samples of drive boards have been completed and the relevant functional tests have been carried out. The test results show that the performance of the drive boards is good, which meets the requirements and achieves the predetermined goal.
Using variational regularization method of electrical impedance tomography to reduce the position error of human arm
Authors: Du Donghai , Huang Kun , Liu Xingmou , Li Qingdu , Zhang Jiajia 
Published: February 2021

Abstract
This paper investigates how to reconstruct human arm images using electrical impedance tomography. A simplified arm model is first established. The comparison between the Tikhonov regularized reconstruction algorithm and the Variation regularized reconstruction algorithm is then made. The results show that the Variation regularized reconstruction algorithm has the lesser position error on the organizational junction edges and is basically overlap with the target area of the model. How to eliminate the artefact of the reconstructed image needs to be further investigated.
Design and analysis of the variable-axis structure before and after the large magnetic block of the charging and discharging magnetic adsorption robot
Authors: Ming-lei LI , Yu-lian ZHANG , Xin CHEN , Shi-fei WU 
Published: February 2021

Abstract
The new type of magnetic adsorption robot for charging and discharging the outer surface of ships has unique advantages in derusting the outer surface of ships. Due to the relatively large volume of the charging and discharging magnetic block, it is difficult to rotate around the bearings at the front and rear ends through the track. This paper designs a variable axis structure for large magnetic blocks before and after walking. Use NX to complete the construction of the 3D model, and import the 3D model into ANSYS for structural analysis through the association with ANSYS-Workbench. The deformation and stress analysis of parts provide theoretical support for the safety and stability of the Variable axis structure.
Short circuit fault analysis and solution research of equipment electric gas cabinet under conductive dust pollution environment
Authors: Mei Ke , Li Xiaofei , Gu Chao 
Published: February 2021

Abstract
The production of conductive dust not only pollute the environment, harm people's health, but also bring great harm to the safe operation of electrical equipment. Such as shorting electrical equipment, electrical switch according to touch bad, poor ventilation, etc., it is easy to cause equipment electrical cabinets failure problems, in order to strengthen the reliability of enterprise production, for the timely and effective maintenance of the equipment failure, and take effective measures to guarantee with the safe operation of the equipment electrical cabinets in conductive dust environment. A great deal of work has been done in this paper to prevent the harm of dust to the electrical equipment and remarkable results have been obtained.
Research on Accurate Impact Point Prediction Methods of Heavy Rocket Debris
Authors: Tao Liu , Chao Kou , Li Ma , Jing Yang , yuchao Wang , Yu Zhao 
Published: February 2021

Abstract
Driven by the demands of rocket launching safety and major scientific research projects, this study probes into the process of impact point prediction for heavy debris from rocket launching. By establishing the basic model of impact point prediction, an analysis of error sources of impact point prediction is conducted to define the research direction of improving the accuracy of impact point prediction. The calculation model of heavy debris impact points introduces the concept of comprehensive analysis of big data. Based on the current situation of equipment, it makes full use of valuable measured data resources of rocket launching and the data information of the measured flight and landing area in multiple samples. Using statistical methods, a back calculation of air resistance and velocity correction affecting the impact point calculation is made, thus forming an accurate calculation model of heavy debris impact points. The data validation shows that the real-time prediction accuracy of this model has been greatly improved compared with the original model, which meets the research expectations.
Study on Speech Recognition Method of Artificial Intelligence Deep Learning
Authors: Leini Zhang , Xiaolei Sun 
Published: February 2021

Abstract
This paper briefly describes the basic principles and related theories of speech recognition system, points out the existing problems of speech recognition technology of artificial intelligence deep learning, analyzes the speech recognition methods of artificial intelligence deep learning, puts forward the optimization methods of speech recognition technology of artificial intelligence deep learning from the aspects of strengthening targeted feature recognition of speech system, repeatedly carrying out simulation training of speech recognition and combining acoustic features with sports features, and forecasts the future prospects of speech recognition methods of artificial intelligence deep learning.
Fine-grained image classification based on attention-guided image enhancement
Authors: Lu Junming , Wu Wei 
Published: February 2021

Abstract
Extracting distinguished fine-grained features is essential for fine-grained image recognition tasks. Many researchers use expensive manual annotations to learn to distinguish part models, which may not be possible in practical applications. Unlike previous strongly supervised fine grained classification networks that require additional image annotations, weakly supervised fine grained image classification only requires label annotations. Recently, image enhancement has been increasingly used in network structures, but random enhancement will lead to background noise and filter out irrelevant areas. In this article, we propose a weakly supervised fine-grained image classification network based on attention-guided image enhancement to study the effect of image enhancement on the classification network. In detail, we use the backbone network to generate the feature map of the image, then generate the corresponding attention map through a custom mask, and use the attention map to guide the image enhancement process (including image cropping and image dropping). We conducted experiments on three commonly used fine-grained image classification datasets, and achieved sota effects in CUB, FGVC-Aircraft, and Stanford Cars.
Simultaneously Optimizing Inertia Weight and Acceleration Coefficients via Introducing New Functions into PSO Algorithm
Authors: Yang Wanli , Zhou Xueting , Luo Yulan 
Published: February 2021

Abstract
Because of the drawbacks of easy premature in initial iteration stages, the low convergence accuracy and slowed-down converging speed in final stages of the particle swarm optimization (PSO)algorithm therefore the simple particle swarm optimization (SPSO) algorithm with dynamic changes of inertia weight and acceleration coefficients (IASPSO) has been put forward. IASPSO algorithm provides a parameter optimization strategy by using exponential decreasing inertia weight and sine function acceleration coefficient to improve global exploration capacity. Simulation tests are carried out with classic Benchmark test functions. The simulation results show that compared with other PSO algorithms, IASPSO algorithm can converge to the better global optimization with a fast converging velocity and high convergence precision, promoting the optimization performance of the algorithm.
A new face detection method based on Faster RCNN
Authors: Yan He , Wang Xiaotang , Liu Yuhan , Zhang Yuning , Li Huan 
Published: February 2021

Abstract
The Non-Maximum Suppression (NMS) method based on Faster RCNN uses hard threshold to identify candidate face frames which to be detected. In complex scenes with partial occlusion of the face and uneven lighting, the phenomenon of missing and false detection of the face is prone to occur. Aiming at this problem, this paper proposes a new face detection method to extract face features through CNN, and generates a large number of face candidate frames which to be detected by the Region Proposal Network (RPN); the hard threshold of NMS is improved by linear weighting method, and the face candidate frame is screened by the linearly weighted NMS. Comparison experiment results show that on the FDDB dataset, the new face detection method in this paper can effectively avoid the false detection and missed detection of multiple faces under partial occlusion and uneven illumination, also has high detection accuracy and robustness.
Method for reducing the influence of crosstalk on quasi-distributed sensing network with time-division multiplexing fibre Bragg gratings
Authors: Wu Shengzong , Wen Hongqiao , Chen Xiaohan 
Published: February 2021

Abstract
A serial time-division multiplexing (TDM) quasi-distributed sensing array based on the ultra-weak reflection fibre Bragg gratings (FBGs) has been widely used in various areas. However, multiple reflections and shadow effect between FBGs with the same centre wavelength will accumulate as the number of gratings multiplexed increases, which will cause a significant increase in crosstalk of the reflection spectrum and will seriously affect the accuracy of the measurement results. In this paper, we theoretically analyse the instability of the results caused by multiple reflections and shadow effect, and propose a layer-by-layer compensation method to suppress crosstalk and improve the stability of the results. About 4000 FBGs with a reflectivity of 0.01% were multiplexed in the experimental system, and we measured the fluctuation of the centre wavelength of the grating at different distances to prove the effectiveness of the method we proposed. The experimental results show that the method proposed in this paper can greatly reduce the shift of the centre wavelength of the reflection spectrum and improve the stability of the system.
Automatic Chinese Text Summarization for Emergency Domain
Authors: Liu Mingshuai , Wang Zhongju , Wang Long 
Published: February 2021

Abstract
With the rapid development of the global economy, natural disasters and emergencies frequently occur. A large amount of disaster accident data and emergency case handling measures on the Internet can be used to provide technical reference and auxiliary decision-making when the various social emergency incident occurs. This study establishes an accurate Chinese text automatic short summarization model to automatically obtain summary information from accident cases. In the proposed model, Generative Pre-Training 2.0 (GPT2), which is excellent in generating tasks, is employed as the basic network structure. Adabound algorithm is used to optimize the model so that the model is not disturbed by extreme learning rates, and it converges to the global minimum at the end of training. It solves the problem that the Adam optimization algorithm causes the model to converge to the local minimum due to the extreme learning rate. Meanwhile, Jaya algorithm is utilized to optimize the hyperparameters of the Adabound for a good performance. Experimental results demonstrated that the proposed method has a significant improvement in terms of Recall-Oriented Understudy for Gisting Evaluation (ROUGE).
Design and control algorithm of dual switch forward DC/DC converter with DSP digital control
Authors: Jia-liang Li , Bo Zhu , Ming-yu Cheng , Yuan Li , Ming-liang Wang 
Published: February 2021

Abstract
On the basis of DSP digital signal processing chip TMS320F2812 function as the main control chip of power supply, this paper proposes a dual switch forward topology with RCC converter as auxiliary power supply,the bootstrap drive chip IR2110 as power drive circuit, a dual closed loop control strategy with voltage outer loop and current inner loop, and PID control algorithm using integral separation together with dead zone control. The experimental result show that the power supply structure is easy to operate, and the corresponding control strategy and algorithm effectively improve the stability of the power supply output voltage and the rapidness of the response of the system.