bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Incremental Shrinking Process on Mechanical Properties and Microstructure of Alloy through Electron Backscatter Diffraction Analysis
Authors: Gu Zhengwei , Li Yusheng , Tang Ziming , Yu Ge
Published: December 2021

In recent years, the incremental shrinking process has been widely used in the forming process of aluminum alloy components for the railway vehicles. The effect of the incremental shrinking process on the performance and microstructure of 6082-T6 aluminum alloy was investigated through mechanical tests and electron backscatter diffraction (EBSD) analysis. The tensile test specimens prepared in different rolling orientations (0˚,45˚and 90˚) along the original and deformed sheets exhibited the mechanical anisotropy. After the incremental shrinking process, the average microhardness, tensile strength, and yield strength of this alloy were respectively increased by nearly 8.78%,2.26%,2.72%, while the Elongation was decreased by almost 31.67%. By analyzing the EBSD data, the strength of the material is increased by the incremental shrinking process and its mechanical anisotropy is improved, whereas its plasticity is greatly deteriorated.
Study on Spinning Process Parameters of the Copper Bushing by Tribological Properties and Physical Testing
Authors: Hong Xiaolu , Xu Hengqiu , Xu Ying , Huang Tao , Guo Yaming , Zhang Jiang , Peng Yinjiang
Published: December 2021

The bushing is a kind of ring sleeve which acts as a liner outside the mechanical parts, which needs good strength, hardness and fatigue resistance. In this paper, the copper bushing was prepared by spinning forming method, and the process parameters of spinning were explored. According to the results of material thermal simulation and test, the conclusion is that the spinning process of copper bushing needs to be carried out in two passes by reverse spinning method. The thinning rate is 30% and 25% respectively. The gap between the mandrel and the roller is 10mm, the feed ratio is 1mm/r, and the spinning temperature is 250°C.
Research on the physical properties and film removal mechanism of silver brazing flux by micro morphology analysis and X-Ray Diffraction
Authors: Zhao Yue , Long Weimin , Zhong Sujuan , Wang Luyi
Published: December 2021

The effect of KHF2 addition on silver brazing flux was studied in this paper. Results showed that the melting temperature of brazing flux would sustainably decrease with the increasing content of KHF2. KF could not be completely replaced by KHF2 in the brazing flux because it could restrain excessive spreadability, which was resulted from KHF2. F element in the flux replaced O element to form Fe2F5.
Research air gap on electromagnetic field of high speed motor under the influence of air gap
Authors: Wang Qi , Xing Shiyu , Ma Jian , Liu Aoxiang
Published: December 2021

High speed motor are mainly used in aerospace, petrochemical and NC machining fields. Complex electromagnetic field is distributed in the motor. With the continuous maturity of asynchronous motor technology, research on magnetic field has been rapidly developed. In this paper, the changes of air gap and magnetic field of high speed motor under different working conditions is introduced. The magnetic field model of high-speed motor with Maxwell electromagnetic which established theory through Ansoft finite element software. The distribution of electromagnetic field in the motor is explored. The results show that the magnetic field distribution of induction motor tends to increase with the increase of the air gap magnetic field. Therefore, this study has an important guiding significance for the motor.
Research on Trench Etching and Photolithography Process of SiC Trench MOSFET
Authors: Zhao Wanli , Ge Huan , Wu Peifei , Bai Xue , Wu Xiaowei , Zhu Tao
Published: December 2021

In this paper, the development of trench etching process and photolithography process for 6-inch 4H-SiC trench-type power MOSFET devices is mainly studied. Among them, the etching process successfully solved the anisotropy of dry etching of SiC, the different etching rates of different crystal planes, the difficulty of controlling the angle of the trench sidewall, and the easy formation of micro-trenches at the corners, etc. Successfully realized trenches with etch depth greater than 1.2um and sidewall angle greater than 90° in SiC. Subsequently, the trench was filled with SiO2 to achieve no holes in the trench after filling, and then the photolithography process was studied. Photolithography process is resolved at the trench coating, exposing and developing the non-uniformity problem, achieve a full and uniform coating, self-aligned trench overlay and the overlay accuracy of less than 0.1um, and there is no residue of photoresist in the groove after development. This article uses scanning electron microscope (SEM) to measure the morphology of the trench after etching and photolithography to characterize the experimental results, and the results meet the process requirements. The successful development of this process will facilitate the research and development of deeper trench-type power MOSFET devices.
Improved Electrical Characteristics of 1200V/20A 4H-SiC Diode by Substrate Thinning and Laser Annealing
Authors: Jiao Qianqian , Zhu Tao , Zhou Hang , Li Qingling
Published: December 2021

In this paper, two kinds of silicon carbide (SiC) backside metallization processes were developed, which were backside thinning combined with laser annealing to form ohmic contact and direct rapid annealing (RTA) to form ohmic contact. The specific contact resistivity obtained by both annealing processes was 3.4E-5 Ω·cm2 to 3.8E-5 Ω·cm2. In order to obtain the effect of thinning combined with laser annealing process on forward conduction characteristics of medium voltage devices,1200V/20A JBS diode was developed, and the backside contact adopted the above two annealing schemes, the thickness of 4H-SiC substrate is 200μm. According to the statistical results of hundreds of JBS diodes, the electrical characteristics of the two types JBS are basically the same. Compared with the JBS diode without substrate thinning, the forward conduction voltage (VF) of the thinned JBS diode is decreased about 0.048V. When the substrate of 1200V SiC JBS diodes is reduced to 80μm, the value of VF can only be reduced by about 0.0868V.
Remaining useful life prediction for lithium-ion battery based on the particle filter considering temperature effect
Authors: Han Yangyang , Ma Changlin , Ye Hui , Tang Shengjin
Published: December 2021

Temperature would affect the degradation process of lithium-ion battery. Therefore, considering the influence of temperature, this paper proposes method to predict the Remaining useful life (RUL) of the lithium-ion battery based on Arrhenius and double exponential model. And update the parameter by particle filter. Firstly, we establish a capacity degradation model with considering the influence of temperature, which is based on Arrhenius model and double exponential model. And then, in order to obtain the initial value of the parameters, we process the fitted the lithium-ion battery degradation data. Next, we use the particle filter (PF) algorithm to update the model parameters to realize the capacity estimation and the RUL prediction. Finally, according the experiment, we prove that the accuracy of the method proposed in this paper is better than that the method without considering the influence of temperature change. The result shows that the lithium-ion battery capacity degradation model established in this paper has great potential in the RUL prediction of the lithium-ion battery.
Comprehensive detection device and physical testing for mechanical properties of seabed sediments and shallow gas
Authors: Li Zhe Yun , Li Qing
Published: December 2021

In this paper, a comprehensive detection device for the mechanical properties of seabed sediments and shallow gas is designed, which is mainly composed of the seabed sediment mechanical properties detection part, the shallow gas detection part and the ultrasonic wireless transmission part. The mud water gas separation structure of the shallow gas detection part separates the shallow gas from the mud water, and then the methane concentration in the shallow gas is measured by the non-dispersive infrared methane sensor, which realizes the collection of the submarine shallow gas and the automatic real-time monitoring of the concentration. The measurement of the mechanical properties of seabed sediments realizes the real-time measurement of the three parameters of cone resistance, sidewall friction and pore water pressure, which characterize the mechanical properties of seabed sediments, through strain-sensitive elements. The ultrasonic wireless data transmission part is mainly for the data detected by the mechanical properties of the seabed sediments to be wirelessly transmitted to the sensor placement room through the ultrasonic transducer across the mud-water-gas separation structure. Finally, the data measured by the two parts are transmitted to the mother ship through the cable located in the sensor placement room. The experimental results show that it has the ability to comprehensively detect the mechanical properties of seabed sediments and shallow gas, and has strong operability.
Molecular dynamics simulation to enhance the mechanical and tribological properties of polyimide composites by graphene reinforcement
Authors: Chen Zhe , Li Aijiao , Liu Hong
Published: December 2021

Background: Polyimide is one of the organic polymer materials with the best comprehensive performance. It has outstanding mechanical properties, excellent thermal stability and excellent corrosion resistance, but pure polyimide has high coefficient of friction and wear rate. By combining graphene with polyimide, the mechanical properties of the composite are significantly reformatived, and the friction coefficient and wear rate can be reduced. Objective: The molecular models were developed to study the mechanical and tribological properties of graphene as a reinforced material. Methods: In this paper, the mechanical properties and friction and wear mechanism of materials are studied by molecular dynamics method from the microscopic point of view. The Young’s modulus and hardness of composites were calculated using the strain constant method. Results: Molecular dynamics simulation results expressed that the Young’s modulus and hardness of polymer composites benefited by approximately 115% and 42%, respectively, after the addition of the graphene-reinforced material. The average friction coefficient and wear rate of polymer composites fall by 35% and 48%, respectively. Through the calculation and statistics of the micro-information in the process of friction simulation, the internal mechanism of various situations is revealed in the atomic dimension. Conclusions: Graphene can adsorb on the surface of polymer chain segment, a strong polymer matrix, through van der Waals and electrostatic forces and can effectively resist external loading.
Theory and Calculation of Nontraditional Stable Isotope Fractionation
Authors: Han Zhenyu , Han Guilin
Published: December 2021

This paper conducts processing on isotope anharmonic effect with molecular dynamics method and Monte Carlo method based on path integration. It introduces the theoretical calculation method of pressure effect, and finally the nuclear volume effect and its theoretical calculation method, stressing that the nuclear volume effect is an important part of isotopic studies of heavy metals in the future. This paper makes an analysis on the equilibrium fractionation theory based on simple harmonic approximation.
Car Following Model and Algorithm Design based on Reinforcement Learning
Authors: Ren Jie
Published: December 2021

Based on reinforcement learning technology, this paper establishes a new driverless car following model. DQN algorithm and traffic simulator are mainly used to train the agent, and the following model is finally obtained. Under the precise and controllable experimental environment, the preset optimization targets can achieve the expected assumption and complete the following behavior. This study will contribute to the development of unmanned vehicles in the future.
Research on vehicle scheduling based on C-W algorithm
Authors: Wang Meng
Published: December 2021

Vehicle scheduling is one of the most important links in logistics distribution, a large number of demands also lead to logistics companies have to reasonably arrange the transportation of vehicle routes to save costs. By optimizing the distribution routes of vehicles, logistics companies can save transportation mileage and thus save transportation costs. In this paper,10 demand points of an agricultural products logistics company in Beijing are selected, and the location of the distribution center is obtained through the center of gravity method. Finally, the route allocation is completed by using the mileage saving algorithm, and the scheduling of transport vehicles is realized. The example shows that the mileage saving algorithm can optimize the vehicle route and realize route allocation.
Optimal path selection of multimodal transport based on Ant Colony Algorithm
Authors: Ge Dayun
Published: December 2021

In the process of multimodal transport, the cost and time of transportation are particularly important. In order to avoid unreasonable container transportation and unnecessary waste of transportation capacity and transportation cost, we must effectively integrate the advantages of various transportation modes, select the most suitable transportation mode and the most reasonable transportation path, and take the minimum cost and time as the goal to ensure the smooth transportation of goods to the destination. Therefore, optimizing multimodal transport network has very important practical significance. This paper starts with the multimodal transport network under a single task, designs the solution method of the model combined with ant colony algorithm, and gives an example. Finally, the model and algorithm design are proved to be reasonable by using MATLAB solution algorithm.
Research on resilience recovery strategy optimization of highway network after disaster based on genetic algorithm
Authors: Zhao Fayu
Published: December 2021

In order to effectively improve the recovery efficiency of the highway network after the disaster and make the road network quickly recover to the normal operation level, the recovery strategy of the highway network after the disaster aiming at the optimal toughness was studied and formulated. First clear the toughness in this paper the definition and put forward the two toughness indexes, then constructs the model of road network resilience restored after a disaster, in considering the time, money, resources and cost conditions, through the corresponding genetic algorithm to solve, it is concluded that the shortest road repair, restore minimum loss in the process of recovery program. Finally, an example is given to illustrate how to use the model established in this paper. The results show that from the beginning of repair to the end of repair, the repair team can achieve the expected task in a faster time, which minimizes the performance loss of the road network and saves the cost.
Transportation route optimization based on heuristic algorithm
Authors: Wu Fan , Zhu Yongan
Published: December 2021

With the rapid development of Internet technology, many enterprises are committed to finding the best solution in transportation organization and solving the vehicle distribution routing problem. Firstly, this paper introduces the current situation of transportation organization of Sichuan Yida Feiniu Transportation Company, and analyzes the main problems of the company. Secondly, through the prediction of freight volume, prepare the truck vehicle operation plan and optimize the company’s transportation organization and production plan. Finally, the heuristic algorithm is used to establish a mixed integer programming mathematical model to optimize the pooled vehicle distribution path problem and the vehicle distribution path with time window. In terms of centralized vehicle distribution, combined with the actual situation of Sichuan Yida Feiniu Transportation Company, an example is analyzed, the shortest total path is obtained, and the goal of shortest vehicle travel distance is realized. Through the optimization of the company’s transportation organization, this paper is of great significance to improve the company’s transportation organization to a certain extent.
Calculation and analysis of landing double rocker arms holding pole based on finite element simulation
Authors: Zhang Xing , Shao Yingpeng , Xing Yu
Published: December 2021

Landing double rocker arms holding pole are widely used in the erection of UHV construction towers. Most of the construction arms are based on experience in engineering application, and there are some potential safety hazards. In this paper, the finite element model is established based on the relevant parameters of 700×700mm2 double rocker arm holding pole, and the actual lifting conditions of the pole are analysed. The finite element method is used to simulate nine working conditions for stress analysis. The results show that the double rocker arm holding pole has good mechanical properties under rated load conditions, which verifies the reliability of the arm design. Asymmetric moment hoisting is an important factor threatening the safety of holding pole, which must be strictly controlled.
The Prediction of CMDB Propellant lifetime Based on Arrhenius accelerated model, Berthelot’s equation and Multi-step Prout-Tompkins Model
Authors: Wang Qiong , Gu Yan , Du Jiao Jiao , Jia Lin , Zhang Lin Jun
Published: December 2021

Different models were provided to predict the storage lifetime of propellants more accurately. The stabilizer was recognized as a vital parameter for double based propellants’ storage lifetime estimation. The stabilizer contents of a certain RDX-CMDB propellant were traced during the accelerated aging tests. Based on that, the safe storage lifetime of this propellant were predicted using the Berthelot’s equation, Arrhenius accelerated equation and the advanced kinetic model, respectively. The predicted results were compared and the causes were analysed. It found that the biggest disadvantage of Berthelot’s equation and Arrhenius accelerated equation is that the predicted results are significantly affected by the original data. In details, the minor difference of original data will bring tremendous errors when extrapolating to normal temperature. The general model which can be used to depict complex reactions adopted in AKTS software was preferred compared to reaction order (RO) model and Prout-Tompkins (PT) model.
3D Digital Twin of Intelligent Transportation System based on Road-Side Sensing
Authors: Guo Yunpeng , Zou Kai , Chen Shengdong , Yuan Feng , Yu Fang
Published: December 2021

Cooperative vehicle-infrastructure is one of the most import developing direction of future intelligent transportation system, while digital twin system can record, reproduce, and even deduce the physical system, which could be helpful for the development of cooperative vehicle-infrastructure. In this study, we proposed a 3D digital twin platform of intelligent transportation system based on road-side sensing, a core component of cooperative vehicle-infrastructure system. This platform consists of real road-side sensing unit,3D virtual environment, and the ROS bridge between them, by receiving the sensing results of physical world in real-time, the virtual world can reproduce the compatible road traffic information, such as the type,3D position and orientation of traffic participants.
Simulation application of three-dimensional GIS based on full-scenario intelligence in power grid company transmission line planning
Authors: Zhang Le
Published: December 2021

Traditional data collection and review methods in power grid planning have always had the problems of time-consuming, poor real-time performance, and cumbersome processes. The application of mobile GIS solves the problems of data collection and review methods and makes more efficient use of mobile GIS terminal collection. The data of the mobile GIS solve the urgent problems that need to be solved since the popularization and application of mobile GIS. This system implements functions such as storage, transmission, and review based on mobile GIS data, which will greatly improve the efficiency of data collection by mobile terminals and reduce the cost of data collection. Realize the planning simulation of the power grid under the intelligent cycle of the whole scene.
Energy-saving Scheme of 5G Base Station Based on LSTM Neural Network
Authors: Wang Yuxuan
Published: December 2021

As China’s new infrastructure,5G has received national and social attention. 5G promotes economic to grow rapidly. But, the high energy consumption caused by the massive deployment of 5G base stations cannot be ignored. The total annual power consumption is expected to reach 243 billion degrees when the 5G base station is fully built. In the tidal scene, some 5G base station in an idle state still power fully, which causes great power waste. The historical volume of base station business data is used to train LSTM model, and predict the future base station business. When the business is lower than the threshold, the base station will be closed to avoid unnecessary power waste. And the LSTM model prediction results fits the original data ideally. By implementing the power saving strategy, the energy consumption of the base station is reduced by 18.97 %. A single station can save 1174 degrees of electricity yearly. It can be seen that the energy saving effect is remarkable.
An Algorithm for Path Planning of Autonomous Ships Considering the Influence of Wind and Wave
Authors: Zhou Yucheng , Gong Yan , Geng Xiongfei , Li Dongsheng , Gao Beili , Li Chunxu
Published: December 2021

Aiming at the problem that external factors such as wind, waves and currents are not considered in the path planning of autonomous sailing ships, which affect the safety of navigation, an improved particle swarm optimization algorithm is proposed. Introduce adaptive inertia weight to improve the convergence of the algorithm, wind and wave influence factors in the algorithm fitness function, increase the wind and wave resistance of the path, and improve the safety of the path. MATLAB simulation experiment results show that the optimized PSO algorithm can obtain the global optimal path and improve the safety of the path.
Robust Prescribed Performance Control of Uncertain Vehicle Lateral System under State Constraints
Authors: Yu Jing
Published: December 2021

In the study of the zero-error tracking control problem for vehicle lateral control systems under full-state constraints and nonparametric uncertainties, the zero-error tracking control problem is presented in this paper. A neural adaptive tracking control scheme is proposed by combining the error transformation of the vehicle lateral control system with the barrier Lyapunov function, which realizes that the tracking error of the vehicle lateral control converges to a prescribed compact set at a controllable or specified convergence rate in a specified finite time. The scheme has the following significant characteristics: 1) Based on the Nussbaum gain, the preset new energy finite-time control algorithm, the tracking error of the vehicle lateral control system with non-parametric uncertainty and external disturbance decreases to zero with t → ∞. In addition, it also has the control ability to cope with the presence or even unknown moment of inertia of the system. 2) Barrier Lyapunov function (BLF) ensures the bounded input of the neural network during the whole system envelope, and ensures the stable learning and approximation of the neural network. Furthermore, the bounded stability of the closed-loop system is proved by Lyapunov analysis. Finally, the effectiveness and superiority of the proposed control method are verified by simulation.
Numerical simulation on Crashworthiness of 105000t LNG Carrier
Authors: Sun Qian , Liu Jianmin , Zhou Hong
Published: December 2021

It is of great significance to study the crashworthiness of LNG carrier to improve its crashresistance and enhance its operation safety. In this paper, the collision process between the bulbous bow of the container ship and the side structure of the LNG ship is analyzed by using nonlinear finite element numerical simulation. Collision performance of LNG carrier and collision indicators during the collision, the impact force, velocity and displacement and energy absorption in the process of collision by changing parameters of the major velocity, impact angle and impact location and others are studied. The relevant research results have a strong practical significance for analyzing the deformation, strengthening measures and structural repair of ship side structure impact damage.
Research on Multi-dimensional Data Collaborative Virtual Inventory Based on Markov
Authors: Sun Shunkai , Li Jie , Lu Haihua , Xu Qi , Cui Haobo , Cao Weilin , Chi Yingxiao , Zhou Jun
Published: December 2021

The three-dimensional elevated warehouse is a production equipment, and it is inevitable that it will malfunction during the operation. If it is not handled properly, there will be inconsistencies between information and practice, resulting in inconsistency between inventory information and the actual product. In order to solve the above problems, this project team carried out functional research on various SQL tables of multi-dimensional data collaboration, and constructed a virtual inventory method based on Markov multi-dimensional data collaboration. The behavioral characteristics of the cargo location information in the cargo location table TWMS_LOC and the pallet status table TWMS_PLT are extracted, and the two are compared. If the deviation between the two exceeds the threshold, the status is judged to be no cargo information. Experiments are conducted to test the feasibility and effectiveness of the sentences of the proposed virtual inventory. The results show that the inventory method can better describe the status of the cargo location and information, and effectively realize the virtual inventory at the database level. The research results of this method will completely replace the complicated manual inventory business. It can provide accurate and efficient virtual inventory solutions for similar logistics elevated warehouses.
Wireless communication network security intelligent monitoring system based on machine learning
Authors: Liu Hongkun , Wang Nianci , Liang Sirong
Published: December 2021

Aiming at the problems of traditional wireless communication network security vulnerability monitoring systems such as low monitoring accuracy and time-consuming, a machine learning-based intelligent monitoring system for wireless communication network security vulnerabilities is proposed. In the hardware design of the monitoring system, based on the overall architecture of the wireless communication network and the data characteristics of the wireless communication network, it is divided into a vulnerability data collection module, a vulnerability data scanning module, and a network security vulnerability intelligent monitoring module. In the vulnerability data collection module, the wireless data collector is used to collect vulnerability data in the vulnerability database, and according to the attributes of the vulnerability data, the XSS vulnerability detection plug-in is connected to the vulnerability scanner to scan for wireless communication network vulnerabilities; When the communication network vulnerability data signal is traced, the system session operation of monitoring the vulnerability data. The software part introduces the neural network algorithm in the machine learning intelligent algorithm to process the hidden data in the security vulnerability data. The experimental results show that the wireless communication network security vulnerability intelligent monitoring system based on machine learning can effectively improve the system monitoring accuracy and the efficiency of wireless communication network security vulnerability monitoring.
Leakage analysis of campus water supply system based on MLP neural network
Authors: Wang Yuanhao
Published: December 2021

Water supply system is an important part of campus public facilities, and the water supply pipeline will leak, not only increase the cost of water supply, but also cause water waste. This paper collects water consumption data of water meters at all levels in a school’s water supply system, establishes MLP multilayer perceptron neural network model, determines the water leakage rate according to the fluctuation of predicted value and actual value, so as to analyze the leakage situation of each school’s water supply system. When the fluctuation between the actual and predicted water consumption exceeds a certain threshold, water leakage occurs on that day. Through solving the model, the following conclusions are finally drawn: (1) the annual water leakage rate of the school is 10.74%, and the water leakage is 29131.418L. (2) The water leakage rate in the first quarter is the highest, and the water leakage in the second quarter is the highest.(3) The school aquaculture area is the most serious leakage phenomenon, and the maximum water leakage rate of each water meter node is more than 10%.
Study of a Privacy Preserving Logistic Regression Algorithm (PPLRA) For Data Privacy in the Context of Big Data
Authors: Chen Qiang , Deng Meiling
Published: December 2021

Regression algorithms are commonly used in machine learning. Based on encryption and privacy protection methods, the current key hot technology regression algorithm and the same encryption technology are studied. This paper proposes a PPLAR based algorithm. The correlation between data items is obtained by logistic regression formula. The algorithm is distributed and parallelized on Hadoop platform to improve the computing speed of the cluster while ensuring the average absolute error of the algorithm.
Power Generation Prediction Model Based on Improved PSO-BPNN
Authors: Yu Yan
Published: December 2021

Electricity generation greatly impacts economic development, and electricity is indispensable for production, transportation, and living. Therefore, forecasting electricity generation accurately is of great research significance for the development of the country and the livelihood of the people. Because of the nonlinear relationship between electricity generation and the influencing factors, this paper, supported by the above data in China over the past 20 years, describes a prediction model based on Improved Particle Swarm Optimization (PSO) -- Back Propagation Neural Network (BPNN) to optimize the algorithm about forecasting electricity generation. The experimental results have shown that the accuracy and stability of the prediction model were constructed in this paper, which was improved by about 2%-6% compared with the traditional ones. In addition, the application of this model could provide a constructive theory for some relevant works in the electric-power industry.
Segmentation of Cracked Silicon Wafer Image Based on Deep Learning
Authors: Li Xingxing , Yin Panpan , Duan Chao , Wang Ningxing
Published: December 2021

With the development of the new energy industry, a large number of silicon wafers need to be tested for production quality through the automation industry. The development of deep learning technology has brought huge technological improvements to the industrial quality inspection industry. Through the image segmentation technology based on deep learning, it can accurately divide the defects existing in the silicon wafer. In this paper, the UNet deep learning network is used to segment the hidden cracks in the silicon wafer. The network can extract the shallow semantic features in the silicon wafer well. It uses 5,000 samples collected on the industrial site as the training set,1,000 pieces the sample is used as the test set, and the segmentation accuracy IOU can reach 58.7%.
Research on Service-Oriented Software Systems and Computer Software and Intelligent Calculation Method
Authors: Ni Zhimin , Zhao Fan
Published: December 2021

For the existing service-oriented software single, favors business processing, cannot guarantee the software business processing into the development of software. When the operator encounters operational problems, software failure problems and other problems related to software operation and operation, software development technicians to provide technical support to ensure the software’s business processing functions. This study will move away from dependence on other software and provide technical support to business software operators accurately and in a timely manner to effectively solve the problems that operators may encounter.
Realization And Network Security Design of Information System Digitization of Scientific Project By JAVA+STRUTS
Authors: Zhao Fan
Published: December 2021

At present, the technical plan project appraised the management systematic characteristic, continuous, the independent not strong third party appraised carries out the advancement to be slow; The project may supervise the measure not strong not to have the explicit monitor target and the baseline data; Has not established a set to conform to the technical project characteristic and the project monitor appraisal system which matches with the science and technology project management. In view of above question, uses JAVA and the STRUTS method of exploitation realization easy to maintain, the easy dynamic expansion, to have the secure technical plan project appraisal management process. Through in the recent three years in the Gansu Province science and technology plan project appraised in the management the application indicated, the system enormous enhancement project appraisal management working efficiency, the system movement has been stable, the speed of response is quick, the security is high.
Research on Geological Disaster Forecast Method Based on PCA Structure BP Model
Authors: Luan Zhangbao
Published: December 2021

The BP neural network prediction method constructed by PCA and the geological hazard prediction method based on the MM5 numerical model were used to establish geological hazard classification short-term objective forecast models. The calculation results show that these two objective forecast methods have a good fitting effect on historical samples. The independent sample’s trial report effect is also good; based on the above two objective forecasting methods, through correction, the comprehensive forecast product is finally obtained.
Computer Image Recognition and Recovery Method for Distorted Underwater Images by Structural Light
Authors: Jian Bijian , Ling Yongfa , Zhang Xuebo , Ou Jiawei
Published: December 2021

When imaging through water surface, the random fluctuation of sea surface will cause the distortion of the target scene image, so the distorted image needs to be corrected and reconstructed. At present, distortion compensation mainly adopts iterative registration strategy based on image sequences which is difficult to satisfy the real-time observation. This paper presents a correction method based on active imaging of structured light for underwater image. Experimental results show that compared with the traditional iterative algorithm, the proposed algorithm cannot only improve the restoration accuracy, but also greatly shorten the processing time. Experimental test results demonstrate that the proposed algorithm has good recovery results.
Research on Application of Computer Recognition Technology in C Language Programming Modeling System
Authors: Zhao Yikun
Published: December 2021

C language programming is more and more favoured by the majority of technical personnel in embedded systems. The application of C language technology in computer software programming can effectively avoid unnecessary language logic problems, ensure the smooth progress of programming work and effectively improve the quality and efficiency of programming. For the development of C language embedded system, the programming ideas of system software are explained, the functional module division based on hierarchical design is given, and the realization methods of project organization, program framework design, module reuse design, etc. in the software development process are clarified. To solve the contradiction between C language flexibility and application development engineering. Although it is introduced for the ARM platform, the basic experience and algorithms are also suitable for software design on other embedded platforms.
Research on the Application of Artificial Intelligence Technology in Computer Graphics Processing
Authors: Yang Xia
Published: December 2021

In structured light geometric reconstruction, due to the complexity of shooting methods and scene lighting conditions, the resulting images may be lack of image details due to uneven light. For this reason, the article proposes a Retinex algorithm with colour restoration and colour saturation correction strategy based on HSV colour space transformation based on artificial intelligence technology. Then distinguish whether it is a bright area according to the threshold value, and modify the insufficient transmittance estimation of the bright area. Finally, the intensity component and saturation value are restored in the HIS colour space, and the histogram is used to stretch the intensity component.
Computer Prediction Model for Equipment Maintenance Using Cloud Computing and Secure Data-sharing
Authors: Pan Kun , Jiang Yuchen
Published: December 2021

A With the popularization of automation in the industrial field, productivity has been greatly improved. However, manufacturing corporations are facing a data tsunami which brings new challenges to predictive maintenance (PdM). In recent years, many approaches and architecture for predictive maintenance have been proposed to solve some of these problems to varying degrees. This paper introduces a general framework based on the Internet of Things, cloud computing and big data analytics for PdM of industrial equipment. In this framework, smart sensors are installed on the device to obtain electrical data, which is then encrypted and uploaded to the cloud platform to predict the health condition by deep learning methods. Several working instances including feature selection, feature fusion, and Remaining Useful Life (RUL) prediction are provided. The effectiveness of the proposed methods is demonstrated by real-world cases.
Research on prediction method of S-wave velocity based on deep learning
Authors: Yang Guojie , Wang Shuhua
Published: December 2021

Aiming at the s-wave velocity prediction problem, based on the analysis of the advantages and disadvantages of the empirical formula method and the rock physics modeling method, combined with the s-wave velocity prediction principle, the deep learning method is introduced, and a deep learning-based logging s-wave velocity prediction method is proposed. This method uses a deep neural network algorithm to establish a nonlinear mapping relationship between reservoir parameters (acoustic time difference, density, neutron porosity, shale content, porosity) and s-wave velocity, and then applies it to the s-wave velocity prediction at the well point. Starting from the relationship between p-wave and s-wave velocity, the study explained the feasibility of applying deep learning technology to s-wave prediction and the principle of sample selection, and finally established a reliable s-wave prediction model. The model was applied to s-wave velocity prediction in different research areas, and the results show that the s-wave velocity prediction technology based on deep learning can effectively improve the accuracy and efficiency of s-wave velocity prediction, and has the characteristics of a wide range of applications. It can provide reliable s-wave data for pre-stack AVO analysis and pre-stack inversion, so it has high practical application value and certain promotion significance.
Algorithm analysis based on machine learning in alarm information of metering system
Authors: Ma Yuhan
Published: December 2021

Due to the huge scale of the metering warning system and the wide variety of warning information, manual identification can no longer meet the real-time monitoring needs of modern power grids. Through the use of machine learning, data mining technology, linear regression method, naive Bayes method, automatic classification analysis of alarm information from the massive alarm information. Construct an SVM prediction model to improve the accuracy of alarm information analysis and improve the effectiveness of power grid monitoring and management. The experimental results show that it can provide support for the normal operation of the grid metering system.
Research on Big data Security privacy Protection based on cloud Computing
Authors: Xu Tongtong , Shi Lei
Published: December 2021

Cloud computing is a new way of computing and storage. Users do not need to master professional skills, but can enjoy convenient network services as long as they pay according to their own needs. When we use cloud services, we need to upload data to cloud servers. As the cloud is an open environment, it is easy for attackers to use cloud computing to conduct excessive computational analysis on big data, which is bound to infringe on others’ privacy. In this process, we inevitably face the challenge of data security. How to ensure data privacy security in the cloud environment has become an urgent problem to be solved. This paper studies the big data security privacy protection based on cloud computing platform. This paper starts from two aspects: implicit security mechanism and display security mechanism (encryption mechanism), so as to protect the security privacy of cloud big data platform in data storage and data computing processing.
Study of Chinese spam filtering Based on Improved Naive Bayesian Classification Algorithm
Authors: Zuo Kaiying
Published: December 2021

Spam is a growing threat to mobile communications. This paper puts forward some mitigation technologies, including white list and blacklist, challenge response and content-based filtering. However, none are perfect and it makes sense to use an algorithm with higher accuracy for classification. Bayesian classification method shows high accuracy in spam processing, so it has attracted extensive attention. In this paper, a Bayesian classification method based on annealing evolution algorithm is introduced into Chinese spam filtering to improve the accuracy of classification. Our simulation results show that the algorithm has better performance in spam filtering.
Research on the Development and Application of Computer Data Mining Technology
Authors: Fu Zhe
Published: December 2021

With the rapid development of computer technology, computer data mining technology has been widely used in various fields, and it has also promoted tremendous progress in society as a whole. As the economic and social development will inevitably promote the continuous skyrocketing of data in various fields, how to find useful information in the infinite data will inevitably require computer data mining technology. The article will analyze the development and application of computer data mining technology.
RETRACTED: Application of Keras neural network in the era of big data
Authors: Wang Junqi
Published: December 2021

The experiment uses crawler tools to obtain data, and the data is preprocessed to find missing values and eliminate invalid data, meanwhile, the model is constructed by information entropy and ID3 algorithm so as to select the desired amount of features, and then basic modeling and data filtering is performed to train and evaluate the model for the first time, finally, in order to get a more ideal model, this experiment The optimal model is obtained by changing the number of hidden layers and neurons of the neural network to build a high-level neural network API neural network model written by pure python - Keras neural network model. The results show that when the model defines a 2-layer neural network and the number of neurons in the hidden layer is fourteen, the accuracy of the model is the highest, and the accuracy of the test set is as high as ninety-one percent.
Research on numerical simulation and intelligent computing of vehicle wading driving by smooth particle hydrodynamics method
Authors: Zhang Wei , Jiao Peigang , Hou Qinzhong
Published: December 2021

The method based on Smooth Particle Hydrodynamics (SPH) is a meshless method which is widely used at present. Its advantage is that it can effectively improve the mesh distortion when finite element is used to deal with large deformation, and its particle characteristics are suitable to deal with the simulation problem of fluid. Based on the actual vehicle wading test site and the actual parameters of the vehicle, combined with the actual situation and theoretical basis, the SPH method is used for numerical simulation analysis of the vehicle wading problem. By comparing the simulation process with the actual water changes during wading, the feasibility of using SPH method in vehicle wading application is proved. In the simulation process of vehicle wading driving, under the condition of constant water level, by setting different wading speeds of vehicle, the flow law and change mechanism of water free surface are analyzed, which are of great significance in theoretical research and engineering application research.
Spatial resolution enhancement of rotational-radar subsurface datasets using combined processing method
Authors: McDonald Thomas , Robinson Mark , Tian GuiYun
Published: December 2021

Effective visualisation of railway tunnel subsurface features (e.g. voids, utilities) provides critical insight into structural health and underpins planning of essential targeted predictive maintenance. Subsurface visualisation here utilises a rotating ground penetrating radar antenna system for 360° point cloud data capture. This technology has been constructed by our industry partner Railview Ltd, and requires the development of complimentary signal processing algorithms to improve feature localisation. The main novelty of this work is extension of Shrestha and Arai’s Combined Processing Method (CPM) to 360° Ground Penetrating Radar (360GPR) datasets, for first-time application in the context of railway tunnel structural health inspection. Initial experimental acquisition of a sample rotational transect for CPM enhancement is achieved by scanning a test section of tunnel sidewall - featuring predefined target geometry - with the rotating antenna. Next, frequency data separately undergo Inverse Fast Fourier Transform (IFFT) and Multiple Signal Classification (MUSIC) processing to recover temporal responses. Numerical implementation steps are explicitly provided for both MUSIC and two associated spatial smoothing algorithms, addressing an identified information deficit in the field. Described IFFT amplitude is combined with high spatial resolution of MUSIC via the CPM relation. Finally, temporal responses are compared qualitatively and quantitatively, evidencing the significant enhancement capabilities of CPM.