bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Structure Integration and Thermal Control Technology of RF Microsystem
Authors: Zhong Jianfeng , Yang Zihao , Tan Liangchen , Jiang Shouli
Published: December 2021

The urgent demand for small volume and light weight of APAR brings new challenges to the integration of radio frequency (referred to as RF) structure. This paper reveals the importance and characteristics of RF microsystem structure integration. Then the new challenges and key technologies in the process of microsystem integration are studied, such as system level thermal management and application of high thermal conductivity, multiphysics simulation and so on. In the end the further thinking of the integration and thermal management technology is illustrated.
Investigation on the effects of vertical baffles on liquid sloshing based on a particle method
Authors: Chen Minghui , Wu Qiaorui , Zhang Zhen , Yu Huimin , Huang Ruichang
Published: December 2021

This study adopts the numerical simulations of Moving Particle Semi-Implicit Methods (MPS), which are meshless methods based on Lagrange particles. Using Lagrange particle has an advantage that it can avoid numerical dissipation problems without directly discretizing the convection term in the governing equation. First of all, a numerical model of a liquid sloshing tank without baffles is used to confirm the effectiveness of the MPS by comparing the numerical results with the experimental data of Kang and Li. And the pressure curves obtained with MPS method were in good agreement with the experimental findings, which confirmed its effectiveness. On that basis, simulations of liquid sloshing movements with one baffle, two symmetrical baffles, and three baffles are performed, respectively. The results indicate that the addition of vertical baffles in the tanks effectively enhanced the ability to reduce liquid sloshing.
Research on Control Method of Microgrid Based on Multi Distributed Generation
Authors: Yue Chengyi , Bei Binbin
Published: December 2021

Reducing the dependence of microgrid upon the communication system and realizing the efficient control of multiple distributed generation of the microgrid are problems that need to be solved urgently. Through the research, based on multiple microgrid operation modes, the peer-to-peer control strategy in microgrid is investigated, and the peer-to-peer control strategy method of microgrid is given for a variety of complex control problems of distributed power According to the peer-to-peer control strategy method, distributed power supply adopts droop control in adjusting distributed power supply in output voltage and frequency; the droop controller has P-f and Q-U droop characteristics. This paper establishes a peer-to-peer control microgrid simulation model, adopts the droop controller designed in this paper to island mode and grid-connected mode, and investigates how the microgrid switches between the two modes. In accordance with Matlab/Simulink simulation outcomes, the research examines frequency, voltage and power changes in distributed generation in the microgrid, and verifies the validity and feasibility of microgrid peer-to-peer control strategy.
Research on Anti-Corrosion and Coating Technology of Outer Pipes of Submarine Pipelines Shallow Sea by Physical Testing
Authors: Jiang Xiaobo , Yin Qingguo , Zhang Xiaochun , Wang Xiaoyan , Yang Shaomin
Published: December 2021

In this paper, by discussing the characteristics of the beach and shallow sea marine environment, combining with engineering design and application, studying the anti-corrosion coating and coating technology of the outer pipe of the pipeline, and analyzing the design of the concrete counterweight layer of the submarine pipeline. According to the submarine pipeline of the environment, structural characteristics, construction methods, etc, the reasons for the damage of the external protective coating under certain conditions are explained, so as to select the external protective coating more reasonably, and provide data for the anti-corrosion and coating selection of the marine pipeline.
A Study on the Physical Structure and Residual Stress of Forgings by Vacuum Induction and Atmosphere Protection
Authors: Dong Zhaowei , Xu Kuikui , Wan Xiaohang , Sun Lihui , Liu Meng , Dong Zhongqi
Published: December 2021

GH4169 alloy was prepared by vacuum induction, atmosphere protection and vacuum self-consumption triple-smelting-technology. After forging and standard heat treatment, the microstructure defects of GH4169 alloy bar were analyzed by scanning electron microscope and x ray diffraction. The change law of tissue defects was simulated by statistical analysis. Residual stress of GH4169 bar is measured by drilling method, and strain release coefficient is calibrated by finite element analysis. The experimental results show that the GH4169 alloy forgings have fine grain size, including δ phase, γ’ phase, γ’” phase and mc carbide phase. The distribution of small defects near the center is dense, the distribution of large defects near the edge is sparse, but the distribution of large defects near the outermost layer is also very dense. The residual stress increases first and then decreases along the radial direction, and the residual stress shows the trend of “external pressure internal pull” on the disk surface, and the compressive stress increases greatly near the edge of the disc. The residual stress is consistent with the density of tissue defects.
A Study on Different Bandwidths and Rim Decorations’ Influence on the Mechanical Properties of Graphene Nanoribbon
Authors: Ziliang Guo
Published: December 2021

This paper structured the Graphene Nanoribbon with different bandwidths and rim decorations and obtained the ideal strength and modulus of elasticity based on the calculation under the First Principle. It can be known that the mechanical properties of Graphene Nanoribbon are close to that of graphene, which have less changes with different bandwidth. However, the mechanical properties would be influenced by different decorations which may change the electronic connection state of edge carbon atoms. The results found in this paper can provide some reference for researchers to study the mechanical properties of graphene nanoribbons in the future.
Study on method of HEPA filter recycling by CFD & Physical treatment
Authors: Cheng Lei , Zhang Zhenwei , Xie Shan , Zhang Jing
Published: December 2021

To find out the best method to recycle the filter, this article used both CFD simulation and Physical treatment to clean the filter. This article shows how the air travel thought the filter and how the pollution particles attracted on the filter and what would be the possible way to remove the particles, by using CFD simulation, the result will be show in the following graphic. found out the most efficiency physical treatment is Ultrasonic, by measuring the transmittance of the liquid after the ultrasonic treatment.
Study on Tunnelling Radiation in 4 Dimension Black Holes Vector Particles
Authors: Chen Bingbing
Published: December 2021

Recent studies show that the tunnelling radiation of vector particles has been studied successfully by WKB approximation and Hamilton-Jacobi method. In view of this, the main purpose of this paper is to study the Proca equation and the vector particles tunnelling radiation in a 4-dimensional black hole. Finally, the results here show that the temperature of the vector particle is the same as that of the Dirac particle.
Computer intelligent dynamic simulation and optimization for structural platform of water treatment subsystem on the spacecraft
Authors: Wang Xiaoxin , Sun Tianfeng , Jiao Feifei
Published: December 2021

In order to reduce the load response condition of space-borne equipment, an optimized design scheme of carbon fiber composites sandwich panel was proposed in this paper. The state before and after optimization was analyzed and compared trough simulation calculation. The comparison shows that after the honeycomb sandwich structure was optimized, its fundamental frequency increased by 75%, the drawing force of embedded parts decreased by 50%, and the maximum acceleration response also decreased. Finally, the response under sinusoidal vibration was evaluated by test, and the results show that the optimization of the structure is reasonable and feasible, it can be the reference of other similar products.
Computer Intelligent Evaluation Model of Jining Water Quality by Fuzzy Mathematics and Intelligent Computing
Authors: Huang Xiao , Jiang Linlong , Jin Caixing
Published: December 2021

This study uses fuzzy mathematics comprehensive evaluation method to evaluate the water environment quality of Jining City and summarize the spatial distribution of water pollutants. The results of the research show: (1) The pollution of surface waters in Jining City is relatively serious. The water quality of rivers is mostly Grade V. The pollution of lakes is relatively low. The overall pollution of reservoirs is relatively light. (2) The concentration distribution area of each pollutant is roughly in a “V” shape. The most polluted areas mainly occur in the Beijing-Hangzhou Canal, Old Canal and other places. The water environment quality in the eastern mountainous and hilly area is better.
Comparison of various algorithms based on TSP solving
Authors: Zhang JianChen
Published: December 2021

The traveling salesman problem (TSP) is a classic combinatorial optimization problem. As a hot research problem, it has been applied in many fields. Since there is currently no algorithm with good performance that can perfectly solve this problem, for the solution of the traveling salesman problem, this article first establishes a mathematical model of the traveling salesman problem, and uses four solving methods for the same case: the greedy method, Branch and bound method, dynamic programming method and genetic algorithm, analyze the applicability and accuracy of different algorithms in the same case.
Forecast of Waterway Cargo Turnover Volume Based on Genetic Algorithm to Optimize Neural Network Parameters
Authors: Ma Rong
Published: December 2021

The traditional BP neural network is difficult to achieve the target effect in the prediction of waterway cargo turnover. In order to improve the accuracy of waterway cargo turnover forecast, a waterway cargo turnover forecast model was created based on genetic algorithm to optimize neural network parameters. The genetic algorithm overcomes the trap that the general iterative method easily falls into, that is, the “endless loop” phenomenon that occurs when the local minimum is small, and the calculation time is small, and the robustness is high. Using genetic algorithm optimized BP neural network to predict waterway cargo turnover, and the empirical analysis of the waterway cargo turnover forecast is carried out. The results obtained show that the neural network waterway optimized by genetic algorithm has a higher accuracy than the traditional BP neural network for predicting waterway cargo turnover, and the optimization model can long-term analysis of the characteristics of waterway cargo turnover changes shows that the prediction effect is far better than traditional neural networks.
Container throughput prediction of some ports in the Yangtze River Delta Based on GM (1,1)
Authors: Liu Xinna
Published: December 2021

The MATLAB implementation of grey neural network prediction modeling has been widely used.[1] Firstly, this paper briefly introduces the prediction process of grey GM (1,1) model, constructs the data of container throughput of some main ports in the Yangtze River Delta from 2016 to 2020, uses the powerful scientific calculation function of MATLAB, first accumulates the correlation coefficients a and B, and obtains the corresponding prediction model; Secondly, verify the original data with residuals and relative errors, and then predict the container throughput from 2021 to 2025. According to the prediction results, it provides suggestions for the logistics development of Shanghai port, which can provide a certain theoretical basis for the government departments to formulate the future development plan of the port to a certain extent.
Research on Logistics Distribution Path Planning Based on Genetic Algorithm
Authors: Liu Shaokun
Published: December 2021

In this paper, SF express company Jinzhou Guta District Pinganli business point as an example, to investigate its distribution, statistical analysis of the survey results, summed up the problems in logistics and distribution. Through the systematic study of the problem, a planning model with time window and with the objective of minimizing the total cost of distribution is established. At the same time, an intelligent algorithm for distribution path optimization - Genetic Algorithm (GA) is designed. Genetic algorithm is used to design chromosome coding methods and genetic operators for solving the planning model with the objective of minimizing the total cost of distribution. Finally, the simulation experiment is carried out. MATLAB software is used to solve the distribution route and the total driving distance of vehicles, and the distribution route with the goal of minimizing the total distribution cost is obtained.
Trend Prediction of DC Measuring System Based on LSTM
Authors: Pei Ying , Niu Lin , Li Haifeng , Li Yajin , Yu Dayang
Published: December 2021

The accuracy of DC measurement system directly affects the reliable operation of DC control and protection system. In order to improve the estimation and prediction of DC measurement system op-eration state, a trend prediction algorithm based on multi-dimensional analysis and long-term memory network is proposed. Based on the analysis of DC measurement principle, the DC measurement status is diagnosed and abnormal is identified by time series trend analysis and anomaly detection. The LSTM is used to construct a multi factor driving current prediction model, and the model is trained and an-alyzed based on the actual operation data. Compared with the traditional time series prediction model, the results indicate that the proposed method is more accurate, simple and effective, and can be applied to the prediction of driving current.
Research and application of 3D GIS in the visualization and information management of power grid construction projects
Authors: Zhang Le
Published: December 2021

The research direction and application scope of transmission line 3D visualization aided design system include design data retrieval of transmission line project, preliminary path selection, feasibility study, and preliminary design. Actively explore the in-depth application of line 3D construction drawing design and digital transfer. Based on the relevant work experience of the author engaged in the application of GIS technology for many years, and taking the application of 3D GIS technology in power grid planning and design as the research object, this paper designs and implements a 3D GIS visualization system for power grid planning and design, decomposes the system function with a case, and analyzes the operation flow of the system in detail, which is believed to be beneficial to colleagues engaged in related work.
Facial expression recognition based on improved VGG convolutional neural network
Authors: Dong Cui , Wang Rongfu , Hang Yuanqin
Published: December 2021

With the development of artificial intelligence, facial expression recognition based on deep learning has become a current research hotspot. The article analyzes and improves the VGG16 network. First, the three fully connected layers of the original network are changed to two convolutional layers and one fully connected layer, which reduces the complexity of the network; Then change the maximum pooling in the network to local-based adaptive pooling to help the network select feature information that is more conducive to facial expression recognition, so that the network can be used on the facial expression datasets RAF-DB and SFEW. The recognition rate increased by 4.7% and 7% respectively.
A GNSS anti-spoofing algorithm based on attention scheme in synchronization network
Authors: Lv Bo , Miao Xinyu , Liu Zishan
Published: December 2021

A GNSS anti-spoofing algorithm based on attention scheme jointly with label smooth loss was proposed and verified under designed GNSS dataset to detect potential and complex spoofing threat in synchronization network. Moreover the experimental results verified that the proposed algorithm showed some better performance of machine learning metrics comparing to conventional ways.
Urban Dynamic Expansion Computer Simulation of RF-NH-CA Model Considering Neighborhood Heterogeneity
Authors: Li Junyi , Liu Minghao , Liu Tianlin , Jing Lei
Published: December 2021

“Neighborhood” as the principle of “the closer the distance, the more relevant the attributes”, is often used as a key driving factor for the urban dynamic modeling of cellular automata; however, the current implementation of the “neighborhood” idea is mostly adopted Mean probability method. This method affects the accuracy of urban dynamic simulation to a certain extent because it ignores the spatial heterogeneity of neighboring cells. Based on the random forest method to evaluate the suitability probability of land use, this study uses the intensity gradient change characteristics of the luminous data to endow the traditional neighborhood cell heterogeneity characteristics, and builds a random forest neighborhood heterogeneity CA model (Random forest Neighborhood Heterogeneity Cellular Automata, RF-NH-CA), and verified the effectiveness of the model by simulating the changes in urban land use in the 21 districts of Chongqing’s main city from 2010 to 2017 through a multi-scheme comparative experiment. The results showed that the overall simulation accuracy of the RF-NH-CA model reached 97.59%, and the Kappa coefficient reached 0.7434; compared with the traditional models RF-CA, ANN-CA and Logistic-CA, FoM increased by 0.0274,0.0383,0.0579, respectively. The Kappa coefficient increased by 0.0162,0.0229,0.0351 respectively. Studies have shown that giving the neighborhood cell heterogeneity through luminous data has played a role in improving the accuracy of land use simulation, which is more in line with the real urban expansion.
Campus Computer Network Construction Simulation and Cyber Security Technology
Authors: Yu Bohan
Published: December 2021

With the rapid development of the network age, the network has become an indispensable part of our daily life and work. Computer network is also an indispensable part in campus. How to build a suitable computer network according to the campus environment has become an important problem. Then, while improving the level of network security management, it helps the school carry out its work smoothly. Therefore, this paper expounds the construction scheme of campus computer network, so as to help the campus computer network more perfect.
Research on Computer Modeling of Fractional Differential Equation Applied Mathematics
Authors: Su Linlin
Published: December 2021

This paper qualitatively analyzes the stability of the equilibrium solution of a class of fractional chaotic financial systems and the conditions for the occurrence of Hopf bifurcation, and uses the Adams-Bashford-Melton predictive-correction finite difference method to pass the analysis Bifurcation diagrams, phase diagrams, and time series diagrams are used to simulate the complex evolution behavior of the system.
Application of SAS Algorithm in Responsive Submarine-searching Path Planning
Authors: Han Qiang , Li Lin , Lv Xinyi , Hao Dongsheng
Published: December 2021

Whether the planned path is optimal or not is an important condition for the completion of the responsive submarine-searching task, which depends on the applicability of the planning algorithm. According to the requirements of responsive submarine-searching mission of the anti-submarine aircraft, SAS algorithm used in responsive submarine-searching path planning is analysed in this paper, the relevant constraints are given, and the simulation calculation is carried out by using SAS algorithm. The results show that SAS algorithm has excellent performance in operation speed and planning effect, and it can better meet the training requirements.
Research on Stereo Library Based on Homogeneous Markov Chain
Authors: Sun Shunkai , Li Jie , Xu Qi , Lu Haihua , Cui Haobo , Shen Xue , Chi Yingxiao , Liu Jingjie
Published: December 2021

The intelligent inventory has not yet been implemented in the automated three-dimensional library. The warehouse basically relies on the accounts of the warehouse. It is really necessary to check the pallets manually with the help of a stacker, or venture into the aisle to check on the spot, or install radio frequency identification (RFID) on the pallet. The radio frequency recognition device on the stacker’s loading platform obtains the information of a specific pallet to achieve a physical inventory. After investigation, the results that can pass the three-dimensional library system automatic library are still blank. For the three-dimensional library, the intelligent inventory is of great significance to the actual production. It can automatically identify whether the goods in the designated cargo space are consistent with the storage according to the needs of the warehouse manager, so the demand for the intelligent inventory is very urgent.
Study of BP neural network based on improved particle swarm algorithm
Authors: Ma Xiaoqian , Li Liyuan
Published: December 2021

This paper uses first-order difference to transform non-smooth data into smooth time series data, determines the p and q parameters in the model by judging the trailing and truncated nature of ACF, PACF, and finally establishes the ARIMA model after ACI, BCI detection. According to the parameters of the neural network randomly selected similar to the initial spatial position of the particles in the particle swarm algorithm, the improved particle swarm algorithm is used instead of the gradient correction method to precisely adjust the parameters and establish the BP neural network, which improves the robustness and accuracy of the prediction model.
Design and Research of Non-contact Temperature Measurement and Identity Recognition System
Authors: Zhou Zhaowei , Ruan Taiqi , Wang Tuyang
Published: December 2021

With the rapid spread of the new crown epidemic, prevention of the epidemic has become an important task in daily life. As of now, the cumulative number of confirmed cases in the world has exceeded 150 million, and the epidemic prevention situation is very serious. In the face of the spread of the epidemic, effective temperature measurement, mask recognition, and face recognition are necessary for mobile personnel. Traditional methods such as the deployment of Raspberry Pi, windows platform, etc. can better meet the above requirements, but there are disadvantages such as low number of recognition frames, low accuracy, and bulky equipment. Due to the large market demand, the cost of the chip has also risen. If the above-mentioned functions are deployed according to the traditional method, the cost is relatively high, which increases the economic pressure on small and medium-sized enterprises. The main work of this research is to solve related functions through a processor Kendryte K210 based on the open source instruction set RISC-V. So as to realize a portable and low-cost non-contact temperature measuring device. The paper introduces a low-cost solution based on K210 on the basis of comprehensive discussion of multi-party implementation methods. Based on this processor, the face recognition and mask recognition functions based on YOLOv2 training are deployed through its machine vision and machine hearing capabilities. The temperature is measured by an external MLX90614 sensor; the serial port screen and the voice module JQ8400 are used for user interaction, which meets the guidance of users to the greatest extent. In the design of the hardware circuit, a lithium battery charging and boosting mobile power board based on MH-CD42 is designed. The user can supply power through an external lithium battery to realize the portability of the system.
Research and analysis of music development based on k-means and PCA algorithm
Authors: Cai Zimo , Fu Luqi , Li Wenchao
Published: December 2021

The purpose of this article is to establish an algorithm model that can measure the influence of music, capture the evaluation index reflecting the influence of music, and extend the model to other fields such as politics, culture, and society. We have established a music influence-oriented network algorithm model based on influencers and followers, where each artist is a node, and each follower is a connection between artists. We define relative interaction strength indicators to help understand the entire network algorithm. In addition, we also used time, genre and other scales to further optimize the network algorithm. We first use the PCA algorithm to determine indicators that reflect music similarity, such as vitality, activity, popularity, overall loudness, etc. On this basis, an evaluation algorithm model based on cosine similarity is established to calculate music similarity values of different genres. In addition, we use the K-MEANS algorithm to normalize each feature index and sum its variance. Finally, we noticed that the similarity of artists within genres is higher than the similarity of artists between genres. We further analyzed the differences and influences within and between genres. Taking time as a distinction, a relative heat map of the interactive influence of genres is drawn. It is understood that certain genres will obviously have a certain influence over time. We summarize this model as an impact correlation analysis model. First, we choose a representative influencer. Then, based on the cosine similarity, we obtained the music similarity with the fans in batches, thus more intuitively concluded that the Internet celebrities did affect the respective artists. In addition, we combined the calculation of SPSS variance and selected different indicators to visualize the radar chart to understand the attractiveness differences of certain music features. We first select the musical characteristics with obvious changing trends, then locate the position of the changer in the music evolution process through the time distribution diagram of the corresponding work, and finally select the representative changer. We analyzed the change history of each indicator in the selected genre over time, and finally got the global directed network diagram. Based on the network algorithm model established in the previous question, we analyzed the background of the times and found that there is an interaction between music and the cultural environment. Finally, we also analyzed the advantages and disadvantages of the algorithm model, and discussed the application of the method in other fields.
Numerical Simulated and Mechanism Research on Fine Particle of Pigsty Removal in the Coupling Effection of Acoustic Wave and Electric Field
Authors: Hu Jie , Huang Yangyang , Li Bo
Published: December 2021

For improving the collection efficiency of electrostatic precipitator (EP) in the pigsty, MATLAB & Finite element method (FEM) is applied to calculate RNG k-ε equations, corona equation and acoustic radiation equations to analyze sound field, electric field and particle trajectory in the wire-plate EP. The results show that fine particle agglomeration can be induced, so as to promote the enlargement of fine particles and improve the capture efficiency of fine particles at acoustic node area. Moreover, the particle distribution can be controlled according to the above V-η curve in the pigsty. In addition, η initially increases, and then decreases in the range of f from 1000 Hz to 2000 Hz. Therefore, the linear variation law of V– η & SPL – η & f – η provide scientific control method for the construction of green and efficient removal technology of particulate pollutants in the piggery.
Modified Chirp Scaling Algorithm for Ultra-High Resolution Spaceborne-SAR
Authors: He Tao , Wang Pengbo , Ma Jixiang , Zhou Xinkai , Xue Lingling
Published: December 2021

The hyperbolic range equation model (HREM) and equivalent squint range model (ESRM) are applied in traditional chirp scaling algorithm (CSA). However, these range models cannot describe the satellite range history in the high-resolution case accurately because of the long azimuth integration time. The non-negligible phase error caused by this will lead the targets distort. In this paper, a modified chirp scaling algorithm (MCSA) is proposed by introducing a novel high-precision range model. A more accurate signal spectrum is calculated through it. Then, the modified chirp scaling factor, range compression filter, range cell migration correction (RCMC) filter and azimuth compression filter can be derived based on this signal spectrum, and the focused target obtained at last. Finally, the experimental results, to validate the proposed algorithm, adopted by the sliding spotlight synthetic aperture radar (SAR) simulation are provided.
Azimuth Ambiguity Suppression in SAR Images Based on VS-KSVD Dictionary Learning and Compressive Sensing
Authors: Hu Xinchang , Wang Pengbo , Guo Yanan , Han Qian , Zhou Xinkai
Published: December 2021

The azimuth ambiguities appear widely in Synthetic Aperture Radar (SAR) images, which causes a large number of false targets and seriously affect the quality of image interpretation. Due to under-sampling in Doppler domain, ambiguous energy is mixed with energy from the main zone in the time and frequency domains. In order to effectively suppress the ambiguous energy in SAR images without loss of resolution, this paper presents a novel method of KSVD dictionary learning based on variance statistics (VS-KSVD) and compressed sensing (CS) reconstruction. According to the statistical characteristics of distributed targets, the dictionary that represents the ambiguities is selected and suppressed by coefficient weighting, in which local window filtering is carried out to remove the block effect and optimize the edge information. Finally, the high resolution images with low-ambiguity can be reconstructed by CS. With the proposed approach, the feasibility and effectiveness of the proposed approach is validated by using satellite data and simulation in suppressing azimuth ambiguity.
A 3-D SAR Imaging Method Based on Back Projection Algorithm
Authors: Han Qian , Wang Pengbo , Zhou Xinkai , Hu Xinchang , Guo Yanan
Published: December 2021

3D back projection (BP) algorithm is an imaging algorithm based on time domain echo data, which effectively solves the overlapping mask problem existing in 2D SAR. It can complete the imaging processing of echo signal under any geometry configuration, and has the advantages of high target focusing accuracy and high phase preservation. However, the high complexity and low efficiency of 3D BP imaging algorithm limit its application and development. In this paper, a 3d imaging method based on improved back projection algorithm is proposed. Aiming at the problem that existing imaging algorithms need 2D imaging first and then 3D imaging, an improved 3D BP algorithm is proposed to directly 3D imaging, which avoids 2d imaging processing. The proposed method simplifies the steps of the traditional 3D BP algorithm and improves the efficiency of the algorithm. The validity and effectiveness of the proposed method are verified by the 3d imaging results of simulated lattice targets.
Speckle noise suppression method using multi-azimuth SAR images.
Authors: Shi Yingru , Liu Yang , Xi Peili , Yang Wei , Zeng Hongcheng
Published: December 2021

Synthetic aperture radar images play an important role in military and civilian fields, but the presence of speckle noise has an impact on subsequent tasks such as target detection and target interpretation. With the development of multi-azimuth observation mode, the obtained multi-azimuth image sequences have high similarities. Therefore, combined with multi-azimuth image sequences, a novel method of SAR image speckle noise suppression based on clustering is proposed in this paper. In this method, multi-azimuth joint filtering framework based on two-level filtering is proposed, in which pre-filtering for single image and joint filtering based on Non-local Means algorithm for multi-azimuth image are used to suppress the noise. And k-means clustering is used to optimize the search area in the multi-azimuth joint filtering, so as to effectively suppress speckle noise while retaining structural details.
Design of Heat Exchange System of Sand Core Drying Furnace
Authors: Peng Yuhao , Ren Tianping
Published: December 2021

Heat exchange system is a circulatory drying system on sand core drying furnace. However, there are some shortcomings in the heat exchange system of sand core drying furnace in the current industrial field. For example, the temperature in the drying process is not stable enough, and the optimal temperature control parameters are difficult to choose. In this study, a proportional regulating heat exchange system is designed. The system adopts SIMATIC 1200 programmable logic controller as controller, motor-driven control valve as actuator and back propagation neural network proportion integral differential control algorithm. After sand core drying test, the results revealed that the proportional regulating heat exchange system can realize automatic control of sand core drying temperature and output the optimal combination of heat exchange system control parameters. Compared to the previous heat exchange system, it has better drying temperature control stability.
Design and Realization of Shooting Virtual Training System for UAV-borne Missile
Authors: Lin Shicong , Tang Xin , Lu Wanlin , Liu Zehui
Published: December 2021

UAV-borne missile is effective weapon to attack enemy ground targets. It is expensive, costly and difficult to live-fire drill. Using virtual training instead of actual training can greatly improve the training efficiency and the combat effectiveness. The article regards the operation training of a certain type of UAV-borne missile shooting training as the research object, based on the development of a visual simulation system for UAV-borne missile, uses the object-oriented design method to design a virtual training system based on LabVIEW. The system can realize the shooting operation training of trainees in a virtual environment, and achieve the goals of reduce training costs; improve training efficiency and shorten training period.
Computer System Integration Technology of Hydraulic Engineering Design Based on Machine Learning Algorithm
Authors: Liu Ting
Published: December 2021

With the development of water conservancy informatization, the research on water information system integration is born, which is the need of water conservancy informatization construction at present and also an urgent problem to be solved. Based on the machine learning algorithm, combined with the actual needs of water conservancy business field, the overall framework of computer system integration for water conservancy engineering design is put forward. The overall framework includes: resource layer, comprehensive integration layer and user layer, which exchange data with configuration monitoring software by means of communication. The analytic hierarchy process in machine learning algorithm is used to construct the risk prediction index system, and the risk prediction index and initial prediction results are taken as the input and output of extreme learning machine algorithm in machine learning algorithm. The simulation results show that the prediction accuracy of this method is 94.88%, which can accurately predict the risks existing in hydraulic engineering design computer system and improve the system security.
Research on Electronic Image Stabilization Technology of Vehicle-Mounted Remote-Controlled Weapon Station
Authors: Qin Shumin , Zhao Lizhen , Tian Xingke , Li Lidan , Liu Shuyun
Published: December 2021

The image information of the vehicle-mounted remote-controlled weapon station is jittered and blurred when the stance changes or vibrates, which increases the aiming difficulty and observation fatigue of the shooter, in order to realize the stable marching fire of the vehicle-mounted remote-controlled weapon station, the two-stage stable scheme with the shared gyro sensor is adopted in the system design, namely, the aiming device is rigidly fixed on the initially stable weapon platform, and then the electronic image stabilization is carried out. This paper proposes an approach combining two image stabilization schemes: gyro sensor data and image projection registration, optimizes the selection of image compensation data by registering and comparing the results of the two stable data, and uses the special features of the two schemes to improve the robust stability of electronic image stabilization, which ensure the observation effect of video image stabilization of the vehicle-mounted remote-controlled weapon station.
Design of classification model on high-dimensional imbalance data of motor bearing fault
Authors: Zhu Xiaocui , Hui Li , Sai Qian
Published: December 2021

According to the characteristics of high-dimensional imbalance distribution of motor bearing fault data, a design scheme of classification model is proposed for the high-dimensional data reduction problem in the classification algorithm. For details: Combining standard particle swarm optimization algorithm and random forest algorithm, a new high-dimensional data reduction algorithm is proposed. Aiming at the imbalance problem of data categories in the classification algorithm, we proposes to use machine learning under the sum of squares of dynamic deviations criterion to divide the minority sample data set into mixed regions, high-purity minority sample regions and outlier regions, and then use smote algorithm to complete the data equalization processing, so as to make the sample data equalization processing more reasonable, Focusing on the task of motor bearing fault classification, a design scheme of using standard particle swarm optimization algorithm to improve the least squares support vector machine model is proposed.
Access Data Analysis Technology and Implementation of Electric Power Big Data Achievement Sharing Platform through Artificial Intelligence
Authors: Qian Wang , Na Mi , Zenan Yi , Yue Sun Ming , Qing Liu
Published: December 2021

With the rapid development of the information age, the data generated by all walks of life is showing an increasing trend of “blowout”. According to statistics, the total amount of data generated by mankind in the past 40,000 years is less than the total amount of data generated from 2010 to 2013 alone. The global big data reserves reached 8.61ZB in 2015 alone, and the growth of data in the future will reach an unpredictable value, entering the data age in an all-round way. Traditional power data computing technology and intelligent analysis technology are undergoing profound changes, and emerging big data intelligent analysis platforms are gradually emerging. With the in-depth development of power informatization and the concept of smart grid, the power industry data has grown exponentially, and the business demand for intelligent analysis of large amounts of power data is increasing day by day. Therefore, the access data analysis technology and realization of the power big data achievement sharing platform based on AI is of great significance. The AI-based power big data achievement sharing platform constructed in this article is a research on previous data analysis, and it aims to use the current cutting-edge artificial intelligence technology to build a scalable and highly available power big data analysis and processing platform to provide fast and reliable smart data services for the power industry, smart grid and other grid businesses. Research has shown that the overall availability of the ultrasonic partial discharge recognition system of the artificial intelligence-based electric power big data achievement sharing platform is 99.9967%, which meets the high availability index requirements, and verified that the artificial intelligence-based power big data achievement sharing platform provides highly available computing, storage and other services for its applications.
SAR Images Change Detection based on Sparse Coding and NMF
Authors: Wang Shaona , Liu Yang , Wang Yanan , Li Linlin
Published: December 2021

There are many applications for SAR image change detection, from military and agriculture to detection and management. But in fact, there is the speckle noise in SAR images inevitably. Therefore, the difficulty to detect change is increased. For purpose of reducing the interference of noise, we propose an unsupervised feature learning method using the non-negative matrix factorization algorithm and an improved sparse coding algorithm. First, non-negative matrix factorization method is used to obtain a dictionary which contains spatial structure information. Then, in order to increase the discriminate ability, we extract features for each pixel and apply sparse coding. Finally, the result of SAR image change detection is generated by applying simple k-means clustering method to divide the learned features into two different clusters. The superior performance of the proposed method is verified on several real SAR image datasets through comparisons with several existing change detection techniques.
Capacity optimization of renewable energy microgrid considering hydropower cogeneration
Authors: Fan Lijun , Cui Jiedong
Published: December 2021

This paper proposes a renewable energy system based on photovoltaic power generation, wind power generation and solar thermal power generation, combining thermal power plants with low-temperature multi-effect distillation. Through the electric heater and the thermal storage system photovoltaic and wind power will spare capacity in the form of heat energy, at the same time by thermal power generation system to maintain the stability of the power supply, run under constant output scheduling policy, to the levelling of the smallest energy cost and the design of power rate of maximum satisfaction as the goal, using multi-objective particle swarm optimization (PSO) algorithm to find the best combination of capacity, this system is established. At the same time, combined with low-temperature multi-effect distillation, compared with reverse osmosis seawater desalination cost is lower, reduce energy consumption, has a good application prospect.
Research on Logistics Carbon Emission Mathematical Estimation and Compensation by Computer Statistics and Data Analysis
Authors: Chen Hao , Wang Haiming , Li Ping
Published: December 2021

Global warming is one of the most serious environmental problems facing human society. Greenhouse gases represented by CO2 are considered to be an important cause of climate change. The development of human society is the main reason for the generation of CO2. Economic development and population growth make the use area of fossil fuels continue to expand, which is an important factor leading to the increase of CO2 emissions. The logistics industry is developing rapidly. Its development not only brings value-added economic benefits, but also increases CO2 emissions, and the carbon emission of the logistics industry has gradually become one of the hotspots of attention. Based on the previous theories on carbon emission, this paper determines the research on carbon emission estimation and carbon compensation in the operation of logistics industry, and estimates the carbon emission of logistics industry around the official statistical yearbook data and survey data. Finally, this paper further improves the carbon compensation mechanism of logistics industry from the perspective of compensation subject, compensation standard, compensation mode, process management and carbon price formulation, and puts forward the corresponding measures of carbon compensation mechanism from the perspectives of planning, management, technology, market and publicity.
Numerical simulation study of mining process of upper and lower walls of normal and reverse faults
Authors: Zhuang Bian
Published: December 2021

Mining coal seams near faults are prone to various mine disasters, and different mining sequences have different effects on coal seam disasters. Under this background, the numerical models of normal fault hanging wall, normal faultfoot wall, reverse fault hanging wall and reverse fault footwall under the same geological conditions are established. It is found that the stress concentration of coal pillar is the largest in the mining process of hanging wall of normal fault and footwall of reverse fault, and the possibility of inducing coal pillar rockburst is the largest. Affected by the fault, the coal pillar abutment stress between the working face and the fault shows an upward trend. When mining the coal seam near the fault, various methods such as hydraulic fracturing should be adopted to reduce the coal pillar abutment stress and reduce the risk of mine disasters.
Effect of Reaction Temperature on Adsorption Efficiency using Computer Mathematical Statistics Visible Spectorphotometer
Authors: Zhang Yongli , Li Ruiting
Published: December 2021

In this paper, waste shrimp shells extracted from the head of the chitosan material; static adsorption experiments manner by wastewater containing Fe(III) added chitosan, vis spectrophotometer absorbance before and after the measurement experiment was obtained by reacting the size of the metal ion concentration, adsorption conditions whereby chitosan Fe(III) and the ability to explore. Experiments show that. In the case where the reaction temperature is less than 55°C, chitosan has adsorption rate Fe(III) smaller rise, the optimum temperature was 55°C, but the effects on the reaction temperature adsorption rate is not large; Adsorption when control time 30 min to 50 min, the absorption effect is increased with increase in the time, to reach the optimal reaction time 50 min.
Research on the Adsorption Effects of Biomass by Microstructural Characterization and Intelligent Numerical Computation Method
Authors: Zhang Yongli , Li Ruiting
Published: December 2021

In this paper, sodium sulfide solution as a simulation of sulfur-containing wastewater, using orange peel as adsorbent, through the change of the absorbance of simulated wastewater to analyze the orange peel adsorbent on the treatment effect of simulated wastewater, to explore its optimal experimental conditions. The experimental results show that the adsorbent has a certain adsorption effect on the sulfur compounds in the sulfur-containing wastewater. With the change of the pH value of the adsorption environment, the adsorption rate has changed. The addition of different chemical modifiers in the water will affect the adsorption and effect of orange peel.
The Application of Industrial CT Detection Technology in Defects inspection of lithium Ion Battery
Authors: Hu Shuai , Xu Jiankang , Lv Mengchuan , Zhu Zhengbing , Jia Jusheng , Li Weiquan , Weng Wenxiang
Published: December 2021

Industrial CT can intuitively display the internal structure, material composition and defect status of the tested object in the form of two-dimensional sectional image or three-dimensional image without damaging the structure of the tested object. It is widely used in the location, size, density change and distribution of internal defects of composite materials. It is the best nondestructive testing technology for internal micro size structure. Compared with the traditional detection technology, the defect detection of lithium-ion battery using industrial CT detection technology has many advantages, including component measurement of complex battery internal structure through high-density information in a non-contact and non-destructive manner. This paper introduces a series of defects of lithium ion battery scanned by industrial CT, analyzes the causes and how to improve the process.