bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Study of Milling Cutter with High Damping Alloy Sleeve
Authors: Sheng Dongping , Lu Fengxia , Wan Hongshen
Published: August 2021

This paper proposed three types of milling cutter, including the normal one, the modified cutter with high damping alloy sleeve, the modified cutter with high damping sleeve and gasket, these three type of cutters are identified with type A, type B and type C respectively. The testing items including cutting force, surface smoothness and fatigue life of above three type of cutter are conducted under different working conditions respectively. The result shows that the milling cutter with high damping alloy behaves better and could improve the related performance dramatically. Specifically, the cutting force of the cutters including type B and C is lower obviously than type A at three different directions, and type C cutter has the lowest cutting force and has the best anti-vibration effects. Additionally, under working condition 1, the surface smoothness of the three type of cutters have the similar behavior. But under working condition 2, the high damping milling cutter has at least 30% improvement. Finally, at the aspect of the fatigue life, the milling cutter with high damping alloy has at least 54.55% better performance than the normal cutter, and the wear of the high damping cutter is at least 38.13% less than normal cutter.
A Multiple Solutions Approach to the Inverse Kinematics Problem of a General Serial Manipulator
Authors: Fan Yanping , Li Pin , Zhen Xijin , Shen Zongbao
Published: August 2021

The inverse kinematics problem (IKP) is at the center of computer control algorithms for general serial manipulator. The exact number of feasible solutions of the IKP is highly dependent on the manipulator structure as well as the desired end-effector pose, and the existing inverse kinematics methods have difficulties to solve all feasible solutions of a general serial manipulator. In this work, a multiple solutions approach is applied to the IKP. Then, three numerical examples are used to validate the effectiveness of the multiple solutions approach, and the numerical results demonstrate that the multiple solutions approach is effective and practicable. Finally, an infinite solutions example is presented to show that the proposed approach could also provide limited number of numerical solutions in singularity.
A Study on Strain Energy of Ellipsoidal Inclusion in Half-space
Authors: Qian H P , Zhu K , Zhang R , Li P , Jin X
Published: August 2021

An inclusion refers to localized eigenstrains appearing in such processes as thermal expansion and plastic deformation. In view of micromechanics, the existence of inclusions may significantly influence the mechanical properties of the engineering materials. A micromechanical model is proposed to determine the variation of the strain energies in the presence of the near-surface inclusions. The corresponding inclusion problem in a half-space is usually difficult to be solved analytically. In this work, the strain energy is evaluated numerically via the method of images, which superposes the counterpart solutions in full-space and eliminates the tractions on the boundary surface of the half-space. The validity of the present work is confirmed by comparing with the published results and the finite element method (FEM).
Study on Mechanical Properties of Curved Vascular Stent after Crimping
Authors: Pan Chen , Han Yafeng , Lu Jiping
Published: August 2021

It is a great challenge to improve the mechanical properties of vascular stent, especially in curved vessels. Vascular stent should have ideal mechanical properties, such as high elasticity, high strength and biocompatibility. At present, most of the literatures focus on the mechanical properties of the stent after expansion, ignoring that of the stent before the stent is implanted into the human body. After the stent is crimped, it has a great impact on the stress fatigue of the stent. Excessive compression will lead to the weakening strength, which cannot support the blood vessel. Therefore, in this paper, an improved algorithm was proposed to crimp and straighten a curved stent to a smaller diameter to generate the required boundary conditions by finite element analysis (FEA). This method is helpful to study the mechanical properties of the stent after being crimped and treat lesions in highly curved locations.
Structure Analysis and Optimization Design of the Base of Four-pillar Hydraulic Testing Machine
Authors: Zhu Yurong , He Yan , Ren Jialong
Published: August 2021

Hydraulic testing machine is a kind of testing machine that transfers energy to implement mechanical test by liquid as medium. With the emergency requirement of energy saving and emission reducing, it becomes significant to kick off the infrastructure research to optimize the hydraulic testing machine. At present, some new products always designed with experience is without any improvement. Consider the current situation in testing machine industry, and combined with the desire of design lightweight, some job about optimization and parametric design of product was done from the angle of finite element in this paper. Following content is included: getting a more accurate finite element analysis method about the analysis of the base based on Solidworks, Hypermesh, ANSYS, and optimize model of the base by Optistruct. A more reasonable model of the base with full strength is been got. Puts forward a kind of finite elements analysis for the structure of the hydraulic testing machine. Meanwhile, share shape optimization techniques through which the structure is designed more reasonable.
Detection of Surface Defects of Steel Plate Based on ViT
Authors: Fan Jiangling , Ling Xufeng , Liang Jingxin
Published: August 2021

A self-attention-based method termed as Vision Transformer (ViT) is applied to efficiently detect the Surface Defects of Steel Plate. The defect image is divided to N*N patches, each of which corresponds to a word, and the whole image data is used as a sentence or paragraph in NPL. A ViT framework is constructed by a learnable module with sequence length of L and 12 multi-head attention layers. We train the proposed model on the surface defects dataset. The experiment results show empirically that ViT has superior performance compared to alternative approaches.
Dynamics Analysis of Rolling Bearings for Motor of a Mobile Power Station
Authors: Li Xiaoquan , Ju Rui , Cai Shulin
Published: August 2021

The electric motor is an important part of a mobile power station. Under the complex operating conditions, the stiffness of the rolling bearing exhibits strong time-varying characteristics and non-linear characteristics, which is the one of the main sources for the system non-linearity. Taking the angular contact bearing as the research object, the coupled dynamic model of the bearing-rotor system is established to calculate the time-varying stiffness. The bifurcation law exhibited by the system can be attributed to the excitation of the non-linear bearing force. The numerical calculation method is used to study the motion state bifurcation law and dynamic frequency response characteristics under the rated working condition of the motor. Considering bearing damping, clearance and radial load, the bifurcation and time domain diagrams of different parameters, displacements and rotation speeds in different directions are studied respectively. The results show that when the parameters change, the system will experience chaos, quasi-period and period-doubling motion state; Damping suppresses vibration very clearly, while changes in bearing clearance and radial load significantly cause the system’s vibration amplitude to increase, and radial load changes accelerate system vibration. A reasonable bearing is of great significance for motor the design of a mobile power station.
Finite Element Simulation Analysis of Fluid Pipeline Leakage
Authors: Su Pan , Wu Jiechang , Liu Haisong , Sun Xiaolong , Feng Xuejiao
Published: August 2021

Due to the harsh working environment and the inconvenient maintenance, leakages of warship pipeline often occur. When the pipeline leaks, the fluid flow and pressure in the pipeline will change. The pressure fluctuation of the fluid is one of the main sources of abnormal vibration and noise in the pipeline system. In order to locate the leaking part of the pipeline effectively, it is necessary to use sensors to collect and capture these changing parameters to facilitate real-time monitoring of the pipeline system. In this paper, ANSYS finite element analysis software is used to establish the geometric model of “I” type combined pipeline, and the pressure variation characteristics under different leakage conditions are obtained through simulation.
Research on Dynamic Compression Testing of Silicone Rubber under Different Temperatures
Authors: Zhu Xintao , Li Wenbin
Published: August 2021

For study the mechanical characteristic of silicone rubber under impact loading, the Uniaxial compression tests of silicone rubber under different strain rates (1 × 103/s∼6 × 103/s) and temperatures (233K∼373K) were carried out with test device using the split Hopkinson pressure bar which has a controllers of temperature. The dynamic stress-strain curves and related dynamic mechanical parameters of silicone rubber were generated. The results show that the dynamic compressive strength of silicone rubber at different temperatures has the characteristics of the strain rate strengthening, which increases along with the raise in strain rate. Under dynamic condition, the stress-strain curve at 263K shows the characteristic of transition to “glass state”.
Measurement and Analysis of Optical Properties of Polymer Films with Triangular Pyramid Optical Functional Texture
Authors: Feng Wei , Xu Zhilong , Wu Haifeng , Fang Fang , Wang Su
Published: August 2021

A poly (vinyl chloride) film with triangular pyramid array structure was designed and fabricated. In this paper, a plane to plane hot embossing technique is used to fabricate a triangular pyramid antireflection film on the surface of single crystal silicon solar cells. By testing the optical properties of optical functional textured films, it is found that the reflectivity of triangular pyramid textured films obtained by hot embossing is significantly lower than that of smooth flat films; The absorption and antireflection of high light on the film surface are obvious; The photoelectric conversion efficiency of the solar cell is further improved. Triangular pyramid optical functional structure has great potential in improving the performance of silicon solar cells, which can be applied to different types of solar cells. These improvements are of great significance to the commercialization of silicon solar cell devices.
Polarization Field on Edge States of Single-layered MoS2
Authors: Hu Gongwei , Dan Minjiang , Zhang Yan
Published: August 2021

Operating quantum materials through the application of strong electric field holds great promise for the development of new-generation electronic and photonic technologies with currently inaccessible functionalities. The conventional way of applying gate voltage to produce sufficiently high electric field faces challenge in micro-nano level. Here, we explore polarization field of two-dimensional piezoelectric semiconductors under externally applied strain. The results suggest that the intensity of polarization field can exceed 10 MV/cm near the boundaries of single-layered MoS2 ribbon. Such polarization field can trigger the metallicity-to-semiconductor (M-S) phase transition of one-dimensional edge states, and even lead to metallic bulk states. Similar phase transition can also be driven by a pure external electric field but the required intensity is in the order of MV/cm. Electric field driving the semiconducting phase of edge states presents the sensitive dependence of ribbon width but relatively robust for polarization field. This study opens a new avenue to manipulate quantum materials by high polarization field.
Solution of a Plane Six Setting Sites Problem
Authors: Zhu Yuyang
Published: August 2021

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The Mechanical Effect of Pit Excavation with Protection on Adjacent Pipelines
Authors: Wen Hao , Li Kaihong , Jia Yanjie , Zhou Daijun , Ma Jun
Published: August 2021

The normal operation of pipelines will be affected by the surrounding environment. As an outstanding problem, pit excavation with protection on adjacent pipelines has been paid more and more attention in urban infrastructure. Adding retaining structure in soft clay area can effectively reduce the influence of pit excavation on buried pipeline. In this paper, a3D simulation model of pipeline-soil-wall coupling is established. And the effect parameters of soil, pipeline and envelope on pipeline stress distribution, axial strain and pipeline displacement are analysed. It is found that the stress of pipeline concentrated on the middle part of the pipeline after excavation with retaining foundation pit. The larger the elastic modulus and cohesive force of soil, the smaller the deformation of pipeline, while the change of Poisson’s ratio is opposite. With the increase of pipeline wall thickness and distance between pipeline and diaphragm wall, the Poisson’s ratio is decreased. The internal pressure of the pipeline has hardly affected by the deformation of pipeline, but the deformation of pipeline is increased with the increase of the depth of the foundation pit. The thickness and modulus of elasticity of diaphragm wall have the same change. They are greater with the smaller of deformation capacity of pipeline. These results provide theoretical guidance for the research of foundation pit and pipeline, and provide reference basis for engineering construction.
Quantitative Analysis of the Effect of Pier Turbulence on Ship Yaw Moment
Authors: Tan Zhirong , Chen Wei , Chen Bin , Wang Yang
Published: August 2021

In order to quantitatively analyze the action mechanism of the pier flow field on the adjacent bow, Fluent was used to simulate the flow field variation characteristics of a single cylinder pier without ship passing. Secondly, the DES model and the dynamic grid technology are used to simulate the turbulence and the change of the ship’s bow moment when the ship passes through a single cylinder pier under different transverse distance parameters. The numerical simulation results under multiple working conditions show that when the ship approaches the pier, the bow moment is significantly affected by the flow field of the pier. With the increase of the distance between the pier and the ship, the influence of the pier flow field on the ship’s bow moment is gradually strengthened to gradually weakened.
A Moving Object Detection and Predictive Control Algorithm Based on Deep Learning
Authors: He Yan , Li Xiuxian , Nie Hongfei
Published: August 2021

In traffic scene, a low detection rate of dynamic target is caused by interference features of background area and fast speed of detected moving target. In this paper, an optimal target detection and prediction algorithm is proposed. Firstly, the algorithm of real-time motion parameters (speed, direction, etc.) detection of moving objects (vehicles) based on the depth theory is studied. The original prediction problem is transformed into the problem of automatic updating rate of uncertain parameters and the problem of minimizing the maximum path distance. Secondly, by on-line estimation of the automatic update rate, the proposed trajectory generated is guaranteed to be the minimum length. The allocation strategy minimizes the maximum distance traveled in the collision free. Then, the stability of the estimation error system is guaranteed base on deep learning algorithm. Finally, the simulation shows that the proposed algorithm can be used for moving target detection and path prediction accurately. The performance of the control system is improved.
An analytical method for parameter identification based on datasheet values
Authors: Lu Hao , Zhang Yunpeng , Hao Peng
Published: August 2021

A new method for extracting five parameters of single diode is presented in this paper. Through the further derivation and simplification of the formula, five parameters under a single condition can be obtained analytically by using only three key operating points (open circuit voltage point (OC), short circuit current point (SC), maximum power point (MPP)) and datasheet values, which can achieve high accuracy in only two iterations. The accuracy and effectiveness of proposed method have been validated by experimental data under different environmental conditions.
Data Preprocessing and Quality Evaluation for Building the Power Grid Supervision Knowledge Graph
Authors: Zhang Xinjie , Wang Jian , Guo Lingxu , Wang Xin , Wang Yao , Xu Lei
Published: August 2021

In the process of constructing the power grid supervision knowledge graph, it is necessary to sort out and integrate structured and unstructured multi-source data for knowledge extraction and reasoning. In order to solve the quality problems of multi-source data redundancy and errors, this paper proposes a multi-source data quality evaluation system to achieve multi-dimensional quality evaluation of power grid supervision data such as maintenance, defect, measurement, alarm and oil chromatography. Data preprocessing methods are firstly adopted for text and numerical data separately to complete data noise reduction, data filtering, data filling, etc. According to the actual calculation example, the practicability and effectiveness of the data preprocessing method and data quality evaluation system are verified. Finally, the data value of the power grid supervision knowledge graph is significantly improved, which is helpful to comprehensively improve the equipment state perception ability.
Improved Aspect-level Sentiment Analysis Method based on Multi-Head Attention Mechanism
Authors: Yu Kaixuan , Li Yachao , Zhang Dongsheng
Published: August 2021

The purpose of the aspect-level sentiment analysis task is to analyze the sentiment orientation expressed by different aspects in the text. It has more fine-grained sentiment evaluation objects and is more in line with actual needs. Therefore, it has received extensive attention in recent years. At present, the model that combines the attention mechanism with the Recurrent Neural Network and its variants has gradually become the main method to solve aspect level sentiment analysis tasks. However, this type of method is limited by the deficiencies of the RNN itself, the training time is too long and the dependence between words decreases with the increase of distance. Even if the attention mechanism is added, the above problems will still exist. Therefore, this paper introduces the multi-head attention mechanism into the GCAE model (Gated Convolutional network with Aspect Embedding), and then proposes the GCAE-MHA model (Improved GCAE model based on Multi-Head Attention mechanism). This model models the context and specific aspects of the text sequence at the same time, and learns the interactive relationship between them. And finally uses the two together as the basis for sentiment classification. At the same time, in order to make up for the problem that the convolutional neural network can only extract the dependencies between local words, the GCAE-MHA model also uses the Dilated Convolutional Neural Network to replace it, which can extract the semantic information between long-distance words, and by setting different dilation rate to obtain a richer semantic feature. Finally, experiments are carried out on the SemEval2014 dataset and Twitter dataset. The experimental results show that the GCAE-MHA model can effectively improve the effect of aspect level sentiment analysis while ensuring the simplicity of the model network structure.
Applicability evaluation of blockchain technology in distributed power transaction
Authors: Zhang Han , Xue Song , Ma Li , Wu Zechen , Zhang Gao , Cong Pengwei
Published: August 2021

With the proposal of peaking carbon dioxide emissions and carbon neutrality target, distributed generation, especially distributed renewable energy generation, will play a more and more important role in the future power system and become the main source of power supply. The rapid development of blockchain technology provides more imagination and development opportunities for distributed power transaction. Its security, decentralization and rapidity are very suitable for distributed power transaction. This paper analyzes the key factors affecting the level of distributed power transaction, establishes the applicability model of various transaction modes for distributed transaction, analyzes the applicability of blockchain technology for distributed transaction, and puts forward the improvement direction of blockchain technology in distributed power transaction in the future.
Error analysis in a D(H)/Pd gas-loading system when using isothermal calorimetry
Authors: Wang Xingye , Shen Bingjun , Jin Lihong , Zhou Dan , Tian Jian
Published: August 2021

In the field of low energy nuclear reaction, isothermal calorimetry is often used to calculate the excess heat power released in the system. Due to the structure of the reaction chamber and the differences of the thermal conductivities of the gases used in the calibration and triggering experiments, the chamber will have different temperature gradient or distribution which leads to errors when calculating the excess heat power using isothermal calorimetry. Different gas pressure also has an influence on the heat transfer.
Construction and experiment of phenotyping system based on field wheat
Authors: Hecang ZANG , Jie ZHANG , Qing ZHAO , Qiaoli ZHAO , Guoqing ZHENG , Guoqiang LI
Published: August 2021

In response to the actual needs of informatization of the collectors engaged in the whole process of field wheat production, this paper constructed a phenotyping system based on field wheat, which was of great significance to improve the efficiency of data collection and reduce the labor intensity of the collectors. Based on the collection and management of phenotyping traits data from sowing to harvesting, combined with barcode recognition, database technology and mobile terminal APP technology, a field wheat phenotyping system was designed and developed, and the data was compared with collection efficiency by manual collection methods. The system was composed of the phenotyping trait collection system APP and the phenotype trait management system Web. The APP development architecture used client/server (C/S), the development language used Java, and the phenotyping traits were collected. As the core, upload collected data to the Web to realize data exchange and sharing between APP and Web; Web development architecture used browser/server (B/S) to realize the distribution of test tasks in the wheat production process, data management, report generation center, and statistical analysis. Compared with the manual data collection method, the application of APP could improve the data collection efficiency by 72%. This system had been realized the rapid collection, efficient management and automatic analysis of wheat phenotyping traits, which ensured the standardization of data collection and management, and improved the efficiency of data collection and utilization. The system could support the phenotyping collection and management of other crops, and it is also suitable for field phenotyping surveys in various industries such as fruits, vegetables and so on.
News text classification based on hybrid model of Bidirectional Encoder Representation from Transformers and Convolutional Neural Network
Authors: Wei Fan , Li Fan
Published: August 2021

At present, with the rapid development of Internet technology, text data show massive characteristics. Network media and new media platforms have become an important part of journalism and communication, and network news has become one of the important sources of information. In order to meet the needs of online news reading users and improve the efficiency of personalized news recommendation by content distribution platform, it is urgent to effectively manage and utilize online news. Based on this, this paper studies and implements the algorithm for news text classification, and the goal is to build a classification model for news text with higher classification accuracy. In this paper, BERT and CNN algorithm are combined to classify news texts. The core idea is to send BERT as the embedding layer into the CNN model. The experimental results show that this method is better than the simple BERT model or the simple CNN model.
Task Scheduling Method for Embedded System Composed of All Linear Tasks
Authors: Chen Xing , Li Hongkun , Chen Yugang
Published: August 2021

There are still a large number of small and medium-sized embedded software applications that do not use operating system due to various conditions, for which a lot of time and effort are spent to build appropriate software structure in doing development. This paper presents a concept of linear task and a scheduling method based on the linear task, which can all use C language to realize the fully distributed dynamic multi-task scheduling of embedded single machine system based on the basic foreground-background system structure. On this basis, the system structure of the embedded software application without operating system can be quickly built and the subsequent application function development can be completed. Through the example implementation and simulation verification, it is proved that this method has good hardware independence, low CPU occupancy, small data and code space, flexible application support, comprehensive function, easy time coordination and simple real-time control. The application of this method to build an embedded system composed of all linear tasks can provide an effective foundation for dealing with the increasingly complex application requirements and limited development cycle.
Anti-follower jamming performance analysis of dual sequence frequency hopping in Gaussian white noise channel
Authors: Meng Qingbin , Quan Houde
Published: August 2021

With the increasingly severe wireless communication confrontation, the traditional conventional frequency hopping (CFH) system has poor performance in anti-follower jamming, so a new dual frequency hopping mode is proposed from the perspective of frequency hopping principle. Firstly, the communication model and anti-jamming principle of the dual sequence frequency hopping (DSFH) system are introduced. Secondly, the typical follower jamming model and its parameters in communication are summarized, and the anti-follower jamming performance of different parameters of the system under follower jamming is analyzed. Finally, the CFH and DSFH system are compared. Bit error rate performance under different parameter conditions. The results show that under the AWGN channel, the anti-follower jamming performance of the DSFH system is better than that of CFH, and the value of the bit error rate is lower than that of CFH.
Characters, Spirals and Unit Dynamics by training neural network model
Authors: Luo Zhe
Published: August 2021

Deep learning is an integral part of machine learning by building a structure like the neural network in the human brain. Amounts of different neural network models have been emerged, improved, and transformed. This article will implement various neural network models for three different specific tasks (Japanese character recognition/double helix task/remote unit dynamics) and analyse the fine-tuning parameters process (different network layers, different types of network layers). The result is that generally, models with more layers would perform better. However, other parameter could have significant effects on the performance. For example, activation function, different numbers of hidden nodes, different initial weights, and different periods, etc.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.