bluuebunny/crossref_metadata_2025_split huggingface dataset:
Static finite element analysis of three-closed box thin-wall beam based on Pseudo-elastic SMA hybrid composite material ANSYS
Authors: Zeng Lingqi 
Published: March 2021

Abstract
The Auricchio model based on shape memory alloy and the finite element analysis software ANSYS Workbench firstly simulated the pseudo-elastic characteristics of SMA bar during the stretching cycle loading and unloading. Secondly, based on ANSYS Material Designer module, a SMA/glass/epoxy resin composite Material model was established and its Material parameters were obtained. ANSYS ACP module was used to establish the finite element model of pseudo-elastic SMA hybrid composite box thin-walled beam. Finally, the static response of SMA composite box thin-walled beam under transverse load is studied, and the influences of SMA, layout Angle, width to height ratio and volume content of SMA layer on the static response of box girder are discussed. The results show that the transverse displacement of the free end of the thin-walled beam increases with the increase of the laying Angle whether there is SMA fiber or not. After embedding SMA, the transverse displacement of the free end of the box thin-wall beam of hybrid composite was smaller. The transverse displacement of the free end of the thin-walled beam with the change curve of the lay-up Angle under the two con Figurations is consistent and basically consistent. At the same laying Angle, the transverse displacement of the free end of SMA hybrid box thin-walled beam decreases with the increase of the width to height ratio and the volume content of SMA monolayer.
Optimization of Casting Process of Headstock Based on Numerical Simulation
Authors: Wang Yifei , Shan Zhongde , Yang Haoqin , Zhang Xueliang , Zhao Mengmeng 
Published: March 2021

Abstract
In this paper, the casting process optimization design of a certain type of headstock is carried out by numerical simulation technology of casting process. Designed the pouring plan based on theoretical calculation; based on the numerical simulation results, quantitatively designed the riser size, and rationally arranged the pouring riser system based on the equilibrium solidification theory, which can reduce the shrinkage porosity and shrinkage defects in the casting process and increase the process yield; Finally, a sand core production plan is provided based on the precision machining technology of the moldless casting mold, which provides a new idea for the process plan design of complex spindle box castings.
Finite element analysis of stress and distortion for welding reinforced structure of angular steel used for power tower under load
Authors: Deng Hualing , Zhang Zhongwen , Yang Bo , Du Baoshuai , Suo Shuai , Li Xinmei , Xu Guoxiang 
Published: March 2021

Abstract
Based on thermal-elastic-plastic theory, a three-dimensional numerical model of residual stress and distortion in L-shaped welding reinforced structure of angle steel used for power transmission tower is developed. The characteristics of residual stress distribution and deformation are numerically investigated, which are compared with the stress and deformation under the action of lateral compressive load. The research results show that, a large stress is generated in and near the weld zone. With enhancing the weld bead length, both equivalent stress and residual distortion have a growth, and the equivalent stress peak reaches 329Mpa, slightly lower than the yield stress of base metal, meanwhile the longitudinal residual stress peak is 399Mpa, higher than the yield stress of base metal. Under the action of 15000Pa lateral compressive load, the stress has no obvious change in the near weld zone of reinforce structure compared with that without load, and the distortion peak reaches 11mm.
Shear Vibration Equivalent Method for Determining Vibration Frequency of Concrete Prefabrication Production
Authors: Li Xiaotian , Fang Junpeng , Zhang Shengjun 
Published: March 2021

Abstract
In order to solve the problem of determining the process parameters caused by the rheological property of concrete in the industrialized vibration compaction production, the shear vibration equivalent method for determining the vibration frequency of concrete prefabrication production is proposed. According to the equivalent effect of shear and vibration, the particle flow interaction theory is used to calculate the rheological parameters of cement paste in the flow field of rotary viscometer under vibration. The mapping relationship between vibration frequency and shear rate can be established when the amplitude is fixed. The apparent viscosity can be used as the evaluation index of the fluidity of concrete mixture in rheology. By studying the critical point of the influence of shear rate on the decrease of apparent viscosity of concrete mixture, the optimal shear rate which can make the apparent viscosity decrease to the limit value is obtained. Combining with the optimal shear rate and the mapping relationship between vibration frequency and shear rate, the optimal vibration frequency of concrete precast production can be determined. This method can be applied to the quantitative determination of vibration frequency in the vibration compaction production of precast concrete components, which is conducive to the improvement of product performance and control of energy consumption cost.
Wafer Crack Detection Based on Yolov4 Target Detection Method
Authors: Li Xingxing , Duan Chao , Zhi Yan , Yin Panpan 
Published: March 2021

Abstract
In recent years, the breakthrough of deep learning technology has brought a qualitative leap in the field of industrial detection. In the past, defects that are difficult to detect by traditional image methods can be detected by deep learning automatic feature extraction to find the expression of difficult samples. In the field of industrial silicon wafer defect detection, with the help of deep learning target detection algorithm, it can effectively adapt to different size, illumination, depth, length of defects. In this paper, yolov4 target detection algorithm is applied to silicon wafer crack problem. Yolov4 target detection algorithm uses many training skills, such as weighted residual connection (WRC), cross stage partial connections (SCP), cross Mini batch Normalization (CmBN), self-adaptive training (SAT) and mish activation make yolov4 better trained on a GPU, and can achieve 98.23% detection accuracy on the wafer crack detection data set.
10 kW Optimization of grid-connected wind power system and its application in Xiamen
Authors: Zhu Guangze , li Jiacheng , He Zihao , Chen Chengxiang , Zhu Qiangqiang 
Published: March 2021

Abstract
Coastal areas not only have large annual average wind speed, but also have more days of strong winds in a year. Xiamen >8 gale days, 22.4 days a year, so it is very suitable for wind power generation. This design is 10 kW wind grid-connected power generation system, each branch is composed of permanent magnet synchronous motor, rectifier, boost module, inverter and filter, 20 groups are used in parallel to form 10 kW system. Choose a single permanent magnet synchronous wind turbine power of 500 W, need 20. System DC voltage :12 V, when the power is fixed, the proper lifting of DC voltage is helpful to reduce the current, thus preventing the IGBT from causing device damage due to overcurrent. A two-dimensional fuzzy controller is used to select the outer loop error and error differential signal as input variables. In order to verify the correctness of fuzzy adaptive PI control strategy, a system simulation model is built.
Research on Optimizing Material Structure Based on Optoelectronic Physical Performance System
Authors: Ma Dinghan 
Published: March 2021

Abstract
High-voltage technology can effectively adjust the crystal lattice and electronic state of optoelectronic materials. It is a feasible means to adjust the physical properties of optoelectronic materials and an important method for synthesizing new optoelectronic materials. This article summarizes the current status of high-voltage research on optoelectronic materials at home and abroad, and introduces the effect of high-voltage on the crystal structure, electronic configuration and physical properties of optoelectronic materials. At the same time, the thesis looks forward to the development of high-voltage research on photovoltaic materials based on the properties of PbS gel mass dot solar cell photovoltaic materials.
Research on Key Construction Technology of Building Engineering Under the Background of Big Data
Authors: Qian Zhixin , Yang Xinyi , Xu Zian , Cai Weilang 
Published: March 2021

Abstract
In the era of the construction engineering industry informatization, the collection, storage, and reuse of big construction data is the only way to apply and inform big data in the construction industry. Relying on the reverse logistics management system, modern construction technology can simulate the timeliness of materials, funds, and time limits of the actual construction site according to the logistics reverse engineering principle. Then, reverse the active management status of the internal logistics model of the actual project. It is one of the critical problems for construction engineering informatization to study applying big data and cloud computing technology to solve problems from massive and complicated data or mass data. Since the research on big data and cloud computing technology started late in construction engineering, it is worth studying which aspects of these technologies can be used in the whole life cycle of this field. This paper proposes a structural construction optimization identification method based on IPEM rapid reanalysis. USES the co-solubility of reverse logistics structure construction technology and applied the data mining method to solve many problems such as refined construction management leftover material surplus in the later construction stage. Finally, a construction optimization model of reverse logistics building system based on improved data mining is proposed according to the actual engineering requirements.
Optimization of Bridge Crane Control System Using Fuzzy PID Control and Speed Control of Frequency Converter
Authors: Zhou Qicai , Wang Kai , Xiong Xiaolei , Zhao Jiong 
Published: March 2021

Abstract
Objective: As a carrier, bridge cranes are widely used in port cargo handling. Due to the structure of the crane itself, the load inevitably produces displacement deviation and lifting weight swing. Therefore, the optimization investigation of the bridge crane control system is carried out to guarantee the fast and secure operation of the crane. Method: According to the characteristics of bridge cranes, combined with the experience of on-site operating staff, the fuzzy rules that meet the working conditions of the site are designed by using the advantages of fuzzy PID (Proportion-Integration-Differentiation) control algorithm without relying on an accurate mathematical model, to set the parameters of the fuzzy PID controller. The speed control technique of frequency converter is adopted to design the system to improve the safety of the overall system. Results: The results show that the adjustment time of the swing angle of crane weight of the traditional PID control requires 6.79s, and the maximum swing angle of crane weight is 0.039rad, and the adjustment time under the fuzzy control is 4.89s, and the swing angle of crane weight is 0.013rad. The fuzzy PID controller surpasses the traditional PID controller in the positioning accuracy. It is not sensitive to changes in the internal parameters of the system. Also, it has strong adaptability to changes in operating conditions. The swing angle of crane weight is smaller, which further improves the robustness. The vector frequency conversion speed control has a more precise control effect on the speed and running track of the operating mechanism of the bridge crane. This method can be applied to the automatic operation mechanism of bridge cranes and achieve good control performance. Conclusion: The conducted optimization investigation of the bridge crane control system makes the control system flexible, simple and robust, providing important theoretical support for related explorations.
The Design of Detector to Illegal Ingredients of Kitchen Waste Based on Embedded Device
Authors: Chen Xing , Sheng Jinliang 
Published: March 2021

Abstract
In this paper, a kitchen waste illegal component recognizer based on embedded device is proposed, which can intelligently identify and record illegal components in kitchen waste. The recognizer is based on SSD-MibileNetV2 algorithm. The Quantization-aware training model is established in TensorFlow framework. The whole model is quantized by uint8 and transformed into TensorFlow Lite structure, and then deployed to the embedded device based on raspberry Pi 4b, which can finally achieve 4.5FPS and 76.35mAP. The recognizer can meet the requirements of real-time and accuracy in detecting illegal components of kitchen waste, and can effectively reduce labor costs and meet the requirements of intelligence.
Multi-Source Image Registration Based on Slic Superpixel Segmentation and Autoencoder
Authors: Zhao Xie , Yong Tianda 
Published: March 2021

Abstract
A new Harris-AE feature matching algorithm based on image edge information combined with SLIC superpixel segmentation method is proposed to achieve high-precision registration of visible and infrared images. First, perform edge enhancement and histogram equalization processing on visible light and infrared images, superpixel segmentation technology is used to eliminate sub-images with low information entropy, and then by constructing a multi-scale Gaussian pyramid to detect the Harris corners of the image edge information, using autoencoder neural network to generate feature descriptors corresponding to feature points, and match the feature points of two images through the fast nearest-neighbor algorithm with bidirectional matching strategy. Finally, the RANSAC algorithm is used to purify the matching points, and the spatial geometric change parameters between the two images are estimated by the least-squares solution to complete the registration of visible light and infrared images. Experiments have proved that this algorithm improves the accuracy of matching while shortening the registration time.
Research on Computer Multimedia Software Graphics and Image Processing and Analysis System in Colleges
Authors: Na Bao 
Published: March 2021

Abstract
With the development of computer software and hardware technology in colleges and universities, the application of multimedia computers has become increasingly widespread. Graphics and image processing occupy a major position in the application of multimedia computers in colleges and universities. Image display is the basis of image processing. The key of special effect display is to divide the image into different image area blocks. The usual image special effect display method is to divide the image into different image blocks according to certain rules. Based on the analysis of the principle of image special effects display, this paper proposes a template-based image special effects display method. Experimental results show that compared with traditional interpolation algorithms, such as bilinear interpolation and bicubic polynomial interpolation, this algorithm has better interpolation effects and overcomes the speckle interference in single wavelet interpolation.
Design and Application of Automatic Meter Reading System For Anti Stealing Electricity
Authors: Fan Hongshen 
Published: March 2021

Abstract
Based on the high-speed development of computer technology, VLSI and communication technology, this paper studies an anti stealing wireless meter reading system which can improve the power supply enterprise’s anti stealing ability and collect, count and analyze the power consumption of large users timely, effectively and accurately, and analyze the characteristics and components of the system design to meet the market demand. The system studied in this paper is mainly used for power supply enterprises to control power stealing for large users.
Research on Practical Byzantine Fault Tolerant Consensus Algorithm Based on Blockchain
Authors: Zheng Xiandong , Feng Wenlong 
Published: March 2021

Abstract
Practical Byzantine Fault-tolerant Algorithm (PBFT) is the most widely used consensus algorithm in alliance chain, which has the advantages of fault tolerance and large throughput. However, PBFT also has some problems that can’t be ignored in specific blockchain applications, such as bad behavior of master node, high network communication overhead and low system flexibility. In this paper, the improvement measures of PBFT consensus algorithm are summarized from many aspects, and then compared with traditional PBFT algorithm. Finally, the development direction and trend of PBFT algorithm are prospected, hoping to provide reference for the research and innovation of PBFT consensus algorithm in the future.
Research on Transmission Resource Allocation in Communication Management System
Authors: Wang Huiqing , Chen Junwei , Zhang Feng 
Published: March 2021

Abstract
This paper studies the completion of power communication technology and transmission network planning. It summarizes the basic research and current situation analysis of transmission technology and business network planning. First, it focuses on the functions of power communication business, information flow, transmission channels and bearing requirements. The characteristics of various power grid technologies and grid communication business models in China are analyzed. Secondly, it carried out analysis and research on the basic design principles of power communication technology and transmission network business planning, evaluation of main indicators, and focused on elaborating the digital communication network management system of synchronous transmission of power communication, the characteristics of ason power communication technology, network protection and management and basic principles of power communication technology and transmission network such as restoration.
Research on holographic image and hierarchical classification evaluation of power suppliers based on Intelligent System
Authors: Zhang Xiaofeng , Wang Chao , Chen Xi , Wang Ying 
Published: March 2021

Abstract
Based on the current new situation, not only to more scientific assessment of the supplier’s equipment quality and technical level, but also on this basis to take into account the equipment in the supply chain life cycle of the production, procurement, operation and decommissioning of the cost, through the evaluation of equipment quality and cost, to achieve the asset-wide life cycle management of the supplier intelligent evaluation, the establishment of supplier intelligent evaluation management information system in order to achieve the establishment and perfection of supplier classification performance evaluation management system.
A survey report on demand characteristics of wisdom supply chain management talents facing Yangtze River Delta and surrounding areas
Authors: Huang Xiaodi , Chen Jianghua , Wang Erchun 
Published: March 2021

Abstract
Wisdom supply chain is a new supply chain model developed in the new generation of information technology revolution, which makes the organization and management mode of supply chain undergo an inevitable change. As an important intersection connect “One Belt and One Road” and the Yangtze river economic belt, integrating wisdom supply chain industry into the regional resource construction system and cultivating wisdom supply chain management talents are the urgent requirements for the Yangtze River Delta urban agglomeration to adapt to the adjustment and upgrading of industrial structure and pursue higher quality development. This survey analyzes the new characteristics of wisdom supply chain and the new demand for human resources by using the methods of literature analysis and enterprise research. Then, explores the demand characteristics of market-oriented wisdom supply chain management talents by mining the recruitment information of supply chain and logistics posts in the Yangtze River Delta and its surrounding areas based on clustering, statistics, text mining and other data analysis methods.
Design of electric power remote meter reading system
Authors: Zhang Ran , Sun XiaoLu , Chen Wei Min , Zhong Li 
Published: March 2021

Abstract
Recording the electricity consumption of users is a monthly routine of the electric power department, which often requires a lot of material and manpower. Therefore, using new technical methods, with the help of automatic remote and local meter reading technology, to achieve the purpose of automatic meter reading to monitor the electric energy meter, work efficiency is improved, and the real automatic power management is realized, and the remote electric meter reading system becomes Alternative meter reading problem solutions for grid companies. This system can meet the remote data recording, collection and real-time monitoring functions of the user’s electric energy meter in the remote power meter reading system within a certain range.
Study on a CNN-HMM Approach for Audio-Based Musical Chord Recognition
Authors: Li Taixiang 
Published: March 2021

Abstract
Convolutional Neural Network (CNN) has shown its strength in image processing task, and Hidden Markov model (HMM) is a powerful tool for modeling sequential data. This paper presents a new architecture for audio-based chord recognition using a CNN-HMM mixture model. This architecture replaces the Gaussian mixture model (GMM) and Deep Neural Network (DNN) layers of GMM-HMM and DNN-HMM models with CNN. The model performance is evaluated through a dataset using different combinations of chroma vectors (STFT, CQT, CENS) as features, based on that, a scale recognition sub-model is tested.
House price prediction using polynomial regression with Particle Swarm Optimization
Authors: Zhou Chenhao 
Published: March 2021

Abstract
This paper combines the characteristics of the real Washington DC house price estate market and the theoretical model of housing prices to conduct an empirical analysis and comparison of the current mainstream housing price index prediction models. It is found that the current mainstream model only studies the trend of the housing price index itself, and is not sensitive to the characteristics of the house itself. Therefore, this paper uses a multiple regression model to integrate the advantages of external factors and use the improved housing price composition establishing a multiple regression prediction model with the particle swarm optimization. It not only makes up for the disadvantages of poorly determined housing price regression indicators and lack of statistical data in multiple regression prediction, but also enables the model to reflect the inflection point of housing prices in advance. PSO is used for selection of affect variables and regression analysis is used to determine the optimal coefficient in prediction.