bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Application of Hot Dip Galvanizing Simulation Test Machine
Authors: Bai Lu , Yue Chongfeng
Published: August 2019

Hot dip galvanizing simulation test machine is a large-scale laboratory process pilot system, consisting of high efficiency electromagnetic induction system, short wave infrared heating system, cooling water supply system, drive system, protective atmosphere pneumatic system, pressure supply system, etc. Composition is an important basic equipment for scientific research and development in the galvanizing industry. The simulator can quickly and cost-effectively carry out laboratory process simulation and pilot test of the production line, and can carry out new technology, new product development, process development and performance optimization, thereby saving a lot of development time, pilot cost and labor cost.
Eliminating continuous grain boundary α phase in laser melting deposited near β titanium alloys by heat treatment
Authors: Li Penglin , Liu Changmeng , Wang Jie , Lu Jiping , Ma Shuyuan , Fan Hongli
Published: August 2019

Continuous grain boundary α phase (α

gb
) is widely present in laser melting deposited near β and β titanium alloys, and it can lead to intergranular fracture and low ductility. Because of the preferential nucleation and growth of α phase at β grain boundaries, the continuous α

gb
cannot be effectively eliminated by traditional heat treatment. Thus, in this study, we develop a new heat treatment including beta solution + ultra-slow furnace heating up + traditional heat treatment, to eliminate continuous α

gb
in laser melting deposited Ti-5Al-5Mo-5V-1Cr-1Fe near β titanium alloy, and the microstructures and tensile properties are investigated. The results indicated that, after beta solution + normal heating up + traditional heat treatment, the continuous α

gb
still exists, and the elongation is still low about 7.5%. However, after beta solution + ultra-slow heating up + traditional heat treatment, there are almost no continuous α

gb
, and the elongation increases to 15.2%. The mechanism about the α

gb
formation during ultra-slow heating up process is simply revealed. Furthermore, this new heat treatment is also suitable to eliminate continuous α

gb
for laser melting deposited Ti17 alloy.
Study on sensitivity of JOM-4 Overhauser magnetometer
Authors: Zhao Jianchang , Chen Shudong , Zhang Shuang
Published: August 2019

Overhauser proton magnetometer is a scalar instrument for measuring the total magnetic field intensity. Sensitivity, as one of the important specifications, reflects the ability to measure the change of magnetic field when detecting magnetic anomalies. It is very important to study the sensitivity estimation method for accurately evaluating the sensitivity specification of the magnetometer. In this paper, two methods, synchronous measurement method and gradient measurement method, are proposed to estimate the instrument sensitivity. The experimental results show that the lower the external environmental electromagnetic interference is, the more accurate the sensitivity estimation is. Furthermore, when the synchronization accuracy is about 1.7 milliseconds, the estimation results of the synchronization measurement method and the gradient measurement method are almost equal. Finally, in the environment with low electromagnetic interference, the sensitivity estimation of the JOM-4 magnetometers is 0.042 nT@3s.
Improving fracture toughness of epoxy resin composites by magnetic particles modified short glass fiber
Authors: Huang J J , Ma C G , Wang S , Huang T , Chen C F , Dai P B
Published: August 2019

In this paper, magnetic nanoparticles were loaded on the surface of short glass fibers by solvent thermal method to prepare magnetic short glass fibers (MSGF) that has orientation response to a weak magnetic field (0.12T), and further MSGF/epoxy resin (EP) composites were prepared. Scanning electron microscope, X-ray diffractometer, infrared spectroscopy and vibration sample magnetometer were used to characterize the samples before and after loading magnetic nanoparticles on the surface of SCF. The effects of MSGF particle content and magnetic field on the fracture toughness of MSGF/EP composites and the toughening mechanism were investigated. The results show that γ-Fe2O3 nanoparticles surface loaded MSGF are successfully achieved using solvothermal synthesis method under the 240 °C with ferric acetylacetonate as iron source and ethanol as solvent. With the optimum MSGF content of 3wt%, when MSGF are oriented along the direction perpendicular to the crack growth under magnetic field, compared to that of pure epoxy resin, the fracture toughness K
ic
and G
ic
of the composite materials with magnetic orientation are increased by 54.4% and 138.5%, respectively, and increased by 20% and 43.9% than that of MSGF/EP composites without magnetic orientation, respectively. The main mechanisms of toughening epoxy resin by MSGF include debonding, pulling-out, bridging and deflecting crack.
Influence of Mixing Process of High Performance Concrete
Authors: Zhao Wu , Mao Kaicheng , Ma Ruifang , Guo Liang , Feng Zhongxu
Published: August 2019

In this paper, three kinds of concrete mixing processes are studied, which are cement coating method, cement mortar method and cement paste method. Three mixing processes were compared with conventional method to explore the effect of the mixing process under vibration stirring on the working performance and mechanical properties of fresh concrete. Concrete slump, expansion, inverted slump cylinder emptying time, gas content and compressive strength were tested on a twin-shaft vibrating mixer to compare the differences in concrete workability and mechanical properties under different mixing processes. The results show that the cement coating method and the cement paste method have obvious effects on the improvement of concrete workability and compressive strength. The cement mortar method is superior to the common process in terms of mechanical properties, and the workability is not much different.
Plastic damage and deformation defect of friction stir welding for aluminum alloy
Authors: Luo Chuanhong , Zhang Jianqiang , Wen Jungang
Published: August 2019

2219 aluminum alloy plates were welded by friction stir welding, which was a solid bonding technology to solve the traditional problems for aluminium alloy welding. The morphology, microstructure and mechanical properties of the joint were investigated. Through analyzing the flowing pattern of the plastically deformed metal in the nugget zone, the strength weakening of the joint were analyzed and summarized. The reason of weakening strength was due to the plastic deformation and damage of the metal, which resulted in the defect formation and the mutational interface. The results show that the well-formed weld beam is similar to the base metal, which has the plastic fracture morphology. However, if there are pores, holes and other welding defects in the weld beam, the fracture morphology is brittle fracture, then the tensile strength is about 70% of base metal and the elongation is about 7%, which means that the advantages of high strength aluminium alloy are not fully utilized.
Prediction of Transition Temperature of Alloy steel Austenite Based on Self-Organizing Neural Network
Authors: Zhao Wenya , Zhang Yinguo
Published: August 2019

In order to determine the key chemical elements of the austenite transformation temperature (Ac1/Ac3) of alloy steel, this paper uses stepwise regression so that the number of neurons in the input layer of Kohonen self-organizing neural network is also determined and the network structure will be optimized. The learning algorithm is improved by combining non-tutor learning and supervised learning. Based on the optimized Kohonen neural network, an Ac1/Ac3 transition temperature predictive model was established. The prediction accuracy of this model which is based on Kohonen self-organizing neural network is higher in tests.The relative error of Ac1 is less than 3.01%, and the relative error of Ac3 is also below3.02%, which is significantly better than the prediction accuracy of stepwise regression. With predicting the critical temperature of Ac1/Ac3 based on Kohonen Network, the actual heating temperature can be determined, which has important practical application value in both steel heat treatment to guarantee quality and shortening the physical experiment period.

CLC number: TP391 Document code: A
Effects of Waste Hybrid Fibers with Different Mixing Ratios on Properties of Recycled Concrete
Authors: Tian Sisi , An Hao , Hu Zhengfu , Pei Changchun
Published: August 2019

In order to improve the performance and application scope of recycled concrete and reduce environmental pollution, fly ash and recycled coarse aggregate of waste concrete were used to replace part of cement and part of natural coarse aggregate respectively, and recycled concrete of base group was mixed. The mixing amount of waste polypropylene fibers and basalt fibers was changed in recycled concrete of base group, and its fluidity and mechanical properties were analyzed. The experimental results show that the mixed fibers have little effect on the fluidity of recycled concrete, but the compressive strength, flexural strength and elastic modulus all decrease. However, they can enhance the splitting tensile strength of recycled concrete, and the strengthening effect is more obvious with the increase of the blending ratio of waste polypropylene fibers.
Polishing behavior of PS/SiO2 Core-Shell nanoparticles with different shell thickness on fused silica Chemical Mechanical Polishing
Authors: Zhang Xin , Pan Guoshun , Wang Weiqi , Guo Dan
Published: August 2019

The core-shell PS/SiO2 composite nanoparticles as abrasives with different shell thickness was researched in fused silica chemical mechanical polishing (CMP) for the first time. The polystyrene nanoparticles were prepared by using emulsifier-free polymerization method first, then the PS/SiO2 with different shell thickness were synthesized by modified Stöber method. The morphologies of PS/SiO2 monodisperse nanospheres were characterized with scanning electron microscopy (SEM). The elastic moduli of single nanoparticle was measured by atomic force microscopy (AFM). The CMP results indicated that the material remove rate (MRR) has been obviously improved with as-prepared nanospheres (21 – 31 nm/min). There was a trend that MRR is rising when the shell thickness is between 200 and 50nm and then falling when the shell thickness is 35nm. Based on the small deformation theory, the finite element analysis was used to simulate the indentation depth and radius of the contact area between the individual particle and the wafer. Then a reasonable explanation for the experimental results was put forward. This research pave a way for realizing the optimization of CMP and material precise removal in the future.
Application of In-beam Activation Analysis in Elemental Distribution Analysis
Authors: Jin Xiangchun , Han Songbai , Chen Dongfeng , He Linfeng , Xiao Caijin , Yao Yonggang , Yun Weixu , Liu Xudong , Tang Chanjuan , Yang Junkai , Wang Pingsheng , Ni Bangfa
Published: August 2019

The analysis of elemental distribution in key parts of samples is of importance in the fields of material science. A non-invasive method utilizing neutrons has been presented. The elemental distribution of materials can be obtained by measuring the gamma spectra with collimated neutron beams using in-beam neutron activation analysis. In order to verify the feasibility of neutron imaging and activation analysis in elemental distribution studies, the experimental model was calculated and verified by Monte Carlo simulations. Using the CARR reactor neutron imaging and activation analysis system, the elemental distribution experiment of the flat sample was carried out. The neutron radiography results of the flat sample and the gamma spectrum of each measurement area were analyzed. The distribution of In, Gd, Eu, Au, and B were in good agreement with the sample. Neutron radiography and in-beam activation analysis were effective tools for conducting elemental distribution studies.
Research on the discovery of opinion leaders in social networks
Authors: Zhou Chufeng , Guan Xinxin , Li Yeli , Zeng Qingtao
Published: August 2019

Since entering the era of Wed 2.0, social networks have been an indispensable part of human life. At present, these social networks are the main source of information dissemination and alienation, and they play a key role in the process of dissemination and are the central users of social networks. Central users have an incredible ability to communicate in their community, and their knowledge and experience of things have a great impact on other users in the community. This research mainly uses the analysis method of social network to analyze the community and find the central users in the community. We use Louvain algorithm to identify the community structure in social networks, and on this basis we use PageRank algorithm to analyze the central users in each community.
Research based on big data analysis of medical industry
Authors: chen lijun , lin Jiaying , yi Zhang
Published: August 2019

In recent decades, institutions in every country and every place have produced a large amount of structured, unstructured and semi-structured data with different (heterogeneous) structures. The healthcare sector faces the need to manage big data from a variety of sources known for generating large amounts of heterogeneous data. In the medical and health industry, various big data analysis tools and technologies have been developed to deal with these massive data. In this article, we will discuss the impact of big data on healthcare and health, as well as the various big data processing tools available in the Hadoop system. We also explored the conceptual architecture of medical big data analysis, including data collection histories from different branches, genomic databases, electronic health records, text/image, and clinical decision support systems.
The Research of Reliability of CX-1B-5 Connectors Coupling in AIT process of spacecraft
Authors: Zhang Wei , Wang Dongmei , Zhao Peirong , Xie Xilong , Zuo Na
Published: August 2019

This paper reviews the applications of CX-1B-5 connectors in assembly and integration process of spacecraft. Wire breakage near the solder joint is the common phenomenon of the connection failure, through fracture morphology and fault tree analysis, tensile force after repeated bending which is a key factor leads to the fatigue fracture. Because the bending of the wire at the root of the solder joint is unavoidable, wire insulation thickening method and anti-wicking tools are used to improve the reliability of CX-1B-5 connectors coupling, with the test showing the bending fatigue resistance improved by 110% by using anti-wicking tools.
An overview of profiling side channel analysis based on machine learning
Authors: Song Shijie , Chen Kaiyan , Ma Jiawei
Published: August 2019

It has made a real issue in cryptographic security with the widespread use of them which attracts more attention now. This paper summarizes the most distinguishing profiling type attack in the side channel of cryptographic chips.The principle steps of the traditional profiling side channel analysis are introduced firstly,then the exposed problems are directed in discussion.It fits well to solve the problems using the algorithm in machine learning. So what undoubtedly added in is that the profiling side channel analysis is based on machine learning. Also the situation and the progress are both the significance in the paper.The disadvantages and the future of its development are mentioned at the end.
Experimental study on the damage law of the shape of the tool nose by the times and duration of micro-discharge
Authors: Yang Yichong , Jin Xin , Zhang Zhijing , Zheng Zhongpeng , Liu Yuzhu
Published: August 2019

The micro-discharge tool setting method is to apply a certain voltage between the tool and the tool set. When the distance between the tool and the tool set is less than the discharge gap, the medium between the tool and the tool set discharges and the voltage decreases, monitoring the voltage signal and recording the machine coordinates when the voltage changes times to complete the tool setting process. In this paper, the influence of the times and duration of the discharge on the tool clearance and the shape of the tool nose during the micro-discharge tool setting process is studied. The research shows that the tool clearance is related to the discharge duration. When the duration of the discharge is less than 4s, the tool clearance becomes smaller with the increase of the times of tool setting process, and the governing tool nose damage is breakage by the discharge current impact. When the discharge duration is greater than or equal to 4s, the tool clearance becomes larger as the number of times of tool setting process increases. The burr that grows at the nose of the tool changes the nose shape. The above research provides support for the subsequent micro-discharge tool setting tool to achieve high-precision non-destructive tool setting process and optimize tool setting parameters.
Contrastive Analysis of Two Connection Modes of Enclosure Wallboards and Steel Frames
Authors: Zhang Hua , Li jianwen , dong zhimin
Published: August 2019

According to the application status of the connection between enclosure wallboards and steel frames in the cold area, a new type of connection mode is designed in this paper. The seismic performance indexes of the two connections such as bearing capacity, energy dissipation and ductility, etc. are obtained through the experimental study of the reduced-scale specimens. Both connection modes can meet the local seismic fortification requirements, but the new connection mode has more advantages than the original connection in many aspects.
Sensorless Control for PMSM Based on Multi-Innovation Two-Stage Extended Kalman Filter Algorithm
Authors: Wu Fei
Published: August 2019

Permanent magnet synchronous motors (PMSM) have been widely used in robotics, CNC machine tools, and aerospace, aerospace and marine fields due to its small size, high efficiency and high power density, and good operating performance. With the development of sensorless control technology, sensorless control has been widely used in many special areas. This paper is aiming at the sensorless control of permanent magnet synchronous motor, the sensorless control system of permanent magnet synchronous motor based on Multi-innovation Two-Stage Extended Kalman Filter (MI-TSEKF) algorithm is studied and implemented.
Spatial non-stationarity and heterogeneity of metropolitan housing prices: the case of Guangzhou, China
Authors: Chen Shaopei , Fang Ming , Zhuang Dachang
Published: August 2019

Taking a case study of the city of Guangzhou, this paper applies sophisticated approaches, including spatial autocorrelation analysis models, traditional regression models and Geographically Weighted Regressing (GWR) model to analyse and discuss the spatial non-stationarity and heterogeneity characteristics of housing prices, in term of the data of the average annual housing prices of each sub-district/town from 2009 to 2015. In this study, four types of influence factors, i.e., location condition (distance to central business district (CBD)), traffic access level, commercial service facility and public service facility are selected. As results, the spatial-temporal evolution characteristic of the housing prices in Guangzhou is closely related to the layout and development of the urban areas. Furthermore, among the selected factors, location condition is the most important factors affecting the housing prices, followed by commercial service facility, traffic access level and public service facility. Specifically, based on the GWR model analysis, the spatial patterns of the regression coefficients of location condition and the public service facility illustrate “east strong and west weak” of the housing prices in Guangzhou. By contraries, “west strong and east weak” of housing prices according to the traffic access level and commercial service facility. The overall pattern of spatial non-stationarity and heterogeneity of housing prices presents the circle structure characteristics with the centre of the CBD in Guangzhou.
Emotional analysis System of book review based on Neural network
Authors: Sun Yanxiong , Li Yeli , Zeng Qingtao , Bian Yuning
Published: August 2019

Contemporary society, is an era of the Information explosion. The explosive growth of book publishing makes readers choose a good book, and publishers choose to publish a book with a market, which has become a very important topic. Aiming at the non-effective analysis of the current book publishers to obtain the real feelings of the users on the book, this paper puts forward that the neural network as the main algorithm is enough to classify the user’s comments emotionally. In the collection of data, through the award-winning books and the two-star score under the book review, take different weights of the calculation, the emotional words of the eigenvectors to plump. And after the book evaluation is pre-processed, the user’s credibility parameters are added to the input word vector. As a result, the accuracy of classification and judgment of the whole system is improved, the consumption of human, material and financial resources is reduced, and the resource can be invested in how to improve the level of publications, which will add to the cause of book publishing in China.
Three-dimensional landscape modeling of Quancheng Square in Jinan city
Authors: Qian S J , Chang Z Q , Liu X M , Wang Y Q
Published: August 2019

Nowadays, with the booming of tourism industry and the rapid development of modern urban construction, two-dimensional scene expression is quite far from satisfying people’s requirements for travelling, sightseeing, shopping and other aspects. Compared with the two-dimensional scene expression, three-dimensional scene expression can provide people with more realistic scenes display and more quality services. Therefore, we carried out three-dimensional landscape belt modeling in Quancheng Square for delivering people more vivid scenery and more details of the sights of Quancheng Square. The modeling procedure consists of three major parts, including the iconic objects modeling by SketchUp, the entire three-dimensional scene modeling and three-dimensional spatial analysis by Skyline. People can clearly learn about the landscape of Quancheng Square through the 3D models and obtain more travelling information of the landscape. Thus, it has been widely applied in many fields, such as virtual tourism, tourism resources management, urban planning and the study of dynamic changes in urban environment.
Computer simulation of crossing line based geometric illusions
Authors: Dai Lingchen , Yu Jinhui
Published: August 2019

Computer modelling of visual illusions may offer useful insights into visual illusions from different perspectives. Focusing on crossing line based geometric illusions where target lines illusorily change their shapes under the influence of context elements, we show that, by taking into account the crossing angles between target and context lines and the distance between intersection points along the target lines, it is possible to simulate some typical crossing line based geometric illusions with a simple model. Compared with a recent work which requires the context lines to be differential, our model eliminates this restriction so that it is applicable to simulating many more crossing line based geometric illusions.
Face Recognition Based on Joint Sparse Representation of Multiple Features for Public Safety
Authors: Wei Li , Yongbin Zhao , Jieping Han , Zhiru Zhang , Hai Yu
Published: August 2019

A face recognition method based on joint sparse representation of multiple features is proposed in this paper. First, principle component analysis (PCA), kernel PCA (KPCA), and non-negative matrix factorization (NMF) are used to extract feature vectors of face images. The three features could provide complementary descriptions for face images. Then, in the classification stage, joint sparse representation is employed to classify the three features thus considering their correlations. Finally, the total reconstruction errors of the three features on different kinds of training classes are calculated to determine the label of test sample. Experiments are conducted on AR and Yale-B databases to validate the effectiveness of the proposed method.
Research and Design on Knowledge Base of NCCN-Based Cancer CDSS
Authors: Zhao Jiang-sheng , Xi Huang , Lv-qing Yang
Published: August 2019

At present, China faces a severe situation in which the incidence of malignant tumors is rising. At the same time, the search engines obtain a large amount of useless or even false medical information, and the tensions between doctors and patients are worsening every day. In order to enable patients to quickly and easily obtain the most authoritative and effective treatment solution, we are in imminent need of the research and development of tumor clinical diagnosis decision-making system. This system is based on NCCN’s latest clinical practice guidelines for malignant tumors, using the decision-making support system approach for research and development. This paper researches and analyzes the practice guidelines and gives the structure design for the knowledge base.
Unsupervised Learning of Visual Odometry with Depth Warp Constraints
Authors: Shi Haibin , Guo Menghao , Xu Zhi , Zou Yuanbin
Published: August 2019

Visual Odometry (VO) is one of the important components of Visual SLAM system. Some impressive work on the end-to-end deep neural networks for 6-DoF VO has appeared. We propose two-part cascade network structure to learn depth from binocular image and to infer ego-motion from consecutive frames. We propose depth warp constraints to make the Network learning more geometrically information. A lot of experiments on KITTI data set show that our model is superior to previous unsupervised methods and has comparable results with the supervised method, verifying that such a depth warp constraints perform successfully in the unsupervised deep method which is an important complement to the geometric method.
Design of Enterprise KB Assessment System Oriented to Operating Process
Authors: Ran Li , Yan Wang , Honglin Chang
Published: August 2019

Enterprise KM has the characteristics of complexity and long-term. Periodic self-assessment of KB system becomes the basis of self-innovation and continuous progress. In this paper, based on the process of KM, a four-dimensional assessment system of enterprise KB for assessing the operating and management of enterprise KB is constructed by combining qualitative analysis with quantitative statistical calculation. The four dimensions of systematization, knowledge precipitation, link rate, persistence and several sub-indicators are extracted from the four levels covering the platform, basis, means and objectives of enterprise KB and operating. An analysis method for cumulative results of assessment is also derived. Through the investigation and analysis of KB in four enterprises, the value of the assessment system is proved.
YOLO-RD: A lightweight object detection network for range doppler radar images
Authors: Zhou Long , Wei Suyuan , Cui Zhongma , Ding Wei
Published: August 2019

Under the condition of limited memory and computing power of radar aircraft equipment, large-scale object detection network based deep learning can not be deployed. Based on the darknet framework, Our paper proposes a lightweight object detection network for range doppler(RD) radar images: YOLO-RD, and builds a lightweight RD dataset: mini-RD, for efficient network training. Firstly, YOLO-RD extracts features from the input image through a series of small convolutional. Secondly, the dense block connection module is used to design the backbone extraction network. Finally, the prediction layer is combined with multi-scale features for prediction. Experiments show that YOLO-RD has achieved good results on the mini-RD dataset with a smaller memory budget, with a detection accuracy of 97.54%.
Using Deep Learning Techniques for Sandwich Panels with Truss Core Damage Detection
Authors: Wang Yabo , Lu Lingling , Song Hongwei
Published: August 2019

In the previous study, the accuracy of damage detection for the sandwich structures with truss core (SPTC) was affected by the selected damage index, Other than this, human subjective judgment could also not directly determine the degree and the location of damage for SPTC. In this paper, the deep learning method is applied to identify the damage for SPTC, and the dataset of the training deep learning model is obtained based on the dynamic method. This paper adopts to the Caffe, which is a deep learning open source framework, object detection model Faster R-CNN is utilized to study the lattice sandwich plate. The damage data set, the optimal hyperparameters for training the deep learning model, and the optimal ratios of the test set and training set for damage dataset are also studied. It is difficult to detect the damage of SPTC applying to the deep learning algorithms, so the good results cannot be gotten. In this paper, the method of Faster R-CNN has used extracts the deep features of the defective target by ZF that is a kind of Convolutional Neural Network (CNN), the method effectively solves the problem that the traditional algorithm cannot effectively detect the damage. As to the damage of SPTC that the traditional algorithms could also identify, the deep learning algorithm is excelled, the experimental mean average precision(mAP) can be raised to 90%. At the same time, the deep learning method can effectively identify locations and size of the damage in SPTC, the method is proven that the accuracy is higher and the speed is faster for damage detection. In the future, a real-time damage monitoring system is possible, and the theory is worth exploring further.
Research on Application of Microlecture to Teaching Reform of Higher Normal Education
Authors: Shuping Li , Taotang Liu , Jie Zhao
Published: August 2019

The progress in computer sciences and information technology provides more teaching modes. Recently, the microlecture has drawn extensive attentions, which could make the knowledge points clear in a shorter teaching time than traditional ways. In addition, it is not limited by time and space. This study makes some explanations and discussions on microlecture in order to apply it to higher normal education. First, the basic concept of microlecture is presented to explain the background. Afterwards, the teaching mode and advantages of microlecture are discussed. Accordingly, its potential in higher normal education can be inferred. Finally, some feasible ways are suggested to apply microlecture to the higher normal education. Conclusions are drawn based on all these analyses. And it is promising that microlecure could make contributions to the teaching reform of higher normal education.
Integrating knowledge-based engineering in body-in-white lightweight design
Authors: Tang Peicheng
Published: August 2019

During the vehicle design process, the body-in-white (BIW) lightweight design needs to consider factors from multiple aspects, such as topology, mechanical properties of the material, thickness parameters, BIW stiffness, modality and crashworthiness. At present, the commonly used BIW lightweight technology around the world includes the application of high-strength lightweight material, the optimization of vehicle structure as well as application of new molding and connection technology. The optimization of vehicle structure changes the mechanical properties of the components by selecting shape parameters of the components (such as the geometric characteristics of the components), in order to achieve lightweight design or performance optimization design. Since BIW contains a large number of structural components and design variables, designing BIW is always time-consuming and knowledgeable-extensive, which requires the collaboration of multidisciplinary engineers. This paper reviews the main methods of lightweight design of BIW and focuses on the application of knowledge engineering. Additionally, the paper introduces the effectiveness of knowledge reuse in practical cases.
3D-Finite Element Analysis for Influences of PCM Inserted in Garment on Body Temperature Responses
Authors: Ye Jialin , Li Fengzhi , Liu Weihua
Published: August 2019

To investigate the influences of the PCM micro-capsules in the garment on the body temperature responses, a mathematical model of heat and moisture transfer in garments inserted PCM micro-capsules is developed. The model is solved by the finite element method. Then, this garments model is interfaced with the thermal regulatory model of the human body based on the 3D FEM. Furthermore, the temperature distribution of garment and human body is simulated by using the model. The results show that garment with PCM can significantly delay the temperature rise compared with garment without PCM.
Research of the Principle and Method for the Long-term Preservation of the Product Structure Design Information of the Launch Vehicle
Authors: Wang Teng , Nie Rongmei
Published: August 2019

Aimed at the long term preservation of the product structure design information in the launch vehicle 3D model, the article researches the feasibility of long-term preservation solutions for the product 3D model information, and raises a suitable method to preserve the structure design information of the 3D model . At the end of the article, an information automatic reading module and 3D model visualization module is developed which is based on the OpenCascade to solve the long term preservation of the product 3D model structure design information.
Chaotic Search Optimal Design and Modeling of Permanent Magnet Synchronous Linear Motor
Authors: Fei Yang Yi , Cun Zhou Zheng , Bin Wang Hong , Chen Jin Xiao
Published: August 2019

This paper presents an electromagnetic finite element model of permanent magnet synchronous linear motor and distortion rate of the air gap flux density waveform is analyzed in detail. By designing the sample space of the parameters, nonlinear regression modeling of the orthogonal experimental design is introduced. We put forward possible air gap flux density waveform sine electromagnetic scheme. Parameters optimization of the permanent magnet synchronous linear motor is also introduced, which is based on chaotic search and adaptation function. Simulation results prove that the pole shifting does not affect the motor back electromotive symmetry based on the structural parameters, which provides a novel way for the optimum design of permanent magnet synchronous linear motor and other engineering.
Research on Key Technologies of MEMS-based 3D Imaging LIDAR Vision System
Authors: Li Lianchun , Qian Keyuan , Zhou Jingkun
Published: August 2019

In this paper, a new type of 3D imaging light detection and ranging (LIDAR) vision system based on Micro-Electro-Mechanical System (MEMS) mirror and novel optical system is proposed. The co-aperture transceiver optical system offers a compact architecture and wide Field-of-View (FOV), which also solves the problem of stray light affecting the system. Thanks to the MEMS and the optical system, the detecting FOV is greatly enlarged and the system volume is much smaller compared to the traditional system. The whole system is designed and verified by simulations and experiments.
Finite element analysis and experimental research on multi-wheel planetary intermittent type spinning mechanism for internally-externally toothed parts with thin-wall cup-shaped
Authors: Guo Yaming , Li Mingzhe , Huang Tao , Luo Wei , Lu Bo , Zhang Rui , Guan Ruoyang , Zhao Xing
Published: August 2019

In this paper, a multi-wheel planetary intermittent type spinning process was investigated through finite element analysis(FEA) and process experiment. The spinning deformation mechanism of cup-shaped internally-externally toothed parts was studied by simulating the planetary spinning process. The distribution of the transient stresses in the contact zones between the roller and blank, and the equivalent plastic strains after spinning were analyzed. The location and causes of defects were determined through analyzing three-dimensional stress and equivalent strain. By comparing the distribution of workpiece thickness after spinning with the simulation result, it has indicated that this research is favorable for developing the technological forming criterion to guide the practical manufacture processes.
Motion design and Stability study of Biped Robot
Authors: Limei Zhao , Xiaotie Ma
Published: August 2019

Biped robot is one of many kinds of humanoid robot, with upper and lower limb structure of multiple degrees of freedom, humanoid appearance and friendly human-computer interaction interface. Robobasic programming language is used to set the rotation angle and direction of each steering gear, so as to carry out motion design and flexibly control the robot. Then, through the theoretical analysis of zero moment point (ZMP), the ideal motion trajectory of the robot in different environments can be determined to ensure that the robot can realize simple machine movements similar to those of human beings on the basis of stable motion.
Study and Application of Intelligent Control Technology in Local Fan of Coal Mine
Authors: Jing Zhao
Published: August 2019

Local ventilator is an important equipment in the process of underground coal mine excavation, and its reliability and efficiency directly affect the safety of gas emission. Because of the characteristics of large lag, non-linearity and multi-disturbance of local fan control system, the traditional PID control method can not achieve the desired control effect, so an intelligent control technology, i.e. fuzzy control, is put forward and applied to the local fan control system, and the fuzzy control algorithm is improved. The improved fuzzy controller can pass through the local part according to the gas concentration in the heading face. The speed of fan is adjusted in real time to ensure the safety of underground working environment, and the fuzzy control of gas concentration and frequency conversion speed regulation of local fan is realized. The fuzzy control not only improves the ventilation control performance and automation level, but also has remarkable energy-saving effect and better control performance.
Optimal Design of Gap Sensor for High-Speed Maglev Train
Authors: Liu Xiankai , Miao Xin , Jin Hao , Jing Yongzhi , Wang Fengchao
Published: August 2019

The gap sensor plays an important role in high-speed maglev train which is able to measure the variation of trains’ suspension gap. The magnetic fields distribution is different clearly when the sensor is opposite to different position in a tooth-groove period of stator railway. The fluctuation of equivalent inductance leads to the slot-effect. The slot-effect is an important factor affecting the stability of the high-speed maglev train suspension control system. The distribution of magnetic field intensity of the flat rectangular coil in different gaps and positions is analysed, and the mechanism of slot-effect is revealed. A new coil is proposed in this paper and this optimized coil can create a smaller slot error than the flat rectangle coil. The simulation results show that the slot error of optimized coil is always less than the error of original coil in any gap distance. The slot error is reduced by half at the working air gap from 8mm to12mm. The slot error of the optimized coil reaches a maximum at 2mm and reaches its minimum at the rated suspension gap 10mm.
Application of High-frequency EMI on Shell SHM with Diverse Radians
Authors: Zhang Xin , Zhang Yu-xiang , Tang Tao , Zhao Jian-gang , Liu Wan-lei
Published: August 2019

Exploring the application of electric-mechanical impedance (EMI) on structural health monitoring (SHM) of diverse systems or structures, especially the radian shell is very necessary to achieve the rapid online monitoring of structural damage. This paper studies the application of EMI on damage detection of shell structure with different radians. Using the piezoelectric equations of piezo-material lead zirconate titanate (PZT), the admittance values of aluminum shell before and after structural damage were got in a given frequency domain. Then by designing experiments based on Agilent 4294A instrument and analyzing the changes of admittance-frequency spectra before and after damage, it concluded the corresponding relationship between the sensitive detection frequency and the radian of the aluminum plate under given thickness; on the meantime, it is found that the damage index (DI) - root mean square deviation (RMSD) can be a judgment standard of damage by analyzing the data of special frequency band, which will has strong guiding significance for the selection of damage detection frequency and damage judging in arc structure hereafter.
Predicting Virtual Machine Resource Consumption Based on Optimized Grey Model
Authors: Aiwu Shi , Di Gao , Kai He
Published: August 2019

In order to relatively change the computing specifications of virtual machines (VMs for short) for the changing resource consumption of VMs, and reduce the impact of the changes, this paper proposes the optimized grey GM(1, 1) model to predict the resource consumption of VMs. Because VM resources may fluctuate greatly in a short time, the initial data are smoothed first, and then modeled, the model edge value is optimized according to the characteristics of cloud environment. Experiments show that the accuracy and stability of the prediction model can be improved by sorting out the initial data and optimizing the model. The prediction value is helpful to design the allocation scheme of VM resources, improve the utilization rate of physical resources in cloud environment.
Research on Genetic Algorithm Fault Diagnosis in Chemical Process
Authors: Li Zhihua , Chen Jing
Published: August 2019

Aiming at the high false positive rate of traditional PCA (principal component analysis) algorithm in chemical process fault diagnosis, an algorithm combining GA (genetic algorithm) and PCA algorithm is proposed. Optimize the training samples of the PCA algorithm. In this method, when selecting training samples, not only the specific data is selected, but the selected data is optimized by the GA. Select a set of best performing data as a new training sample. Experiments using continuous stirred tank reactor data show that the improved PCA algorithm can effectively reduce the false positive rate compared with the traditional PCA algorithm.
Design of OFDM Joint Synchronization Algorithm Based on Cyclic Prefix
Authors: Liu Mengyang , Wang Hongjuan , Li Yeli , Bian Yuning
Published: August 2019

By studying the Maximum Likelihood (ML) algorithm and applying it to Orthogonal Frequency Division Multiplexing (OFDM) system, we analyze its performance. OFDM system has obvious advantages over other wireless communication systems, but it also has disadvantages, such as being sensitive to synchronization errors. The ML algorithm can solve this shortcoming of OFDM system. ML algorithm uses the redundant information carried by the cyclic prefix in OFDM code element. At the same time, ML algorithm calculates its maximum likelihood estimation algorithm to complete the code element timing synchronization and carrier frequency synchronization. Compared with other synchronization algorithms, ML algorithm can complete initial capture and synchronous tracking in one step, so it is widely used in OFDM systems. In this paper, we build a traditional OFDM system and apply the ML algorithm to OFDM synchronization simulation. By changing the design of relevant parameters, we describe the ML algorithm in detail and obtain the same results as the theory.
Some new theorems of α-admissible mappings on c-distance in cone metric spaces over Banach algebras
Authors: Yan Han , Yi-duo Bian , Chang-ji Shan
Published: August 2019

In this work, we introduce some new fixed point results of α-admissible mappings on c-distance in cone metric spaces over Banach algebras, which are significant extensions and generalizations of many important known results. Furthermore, we give an example to illustrate our main results.
A Double Threshold Collaborative Detection Algorithm Based on Mutual Trust Degree Correction
Authors: Lujie ZHANG , Dechun GUO
Published: August 2019

This paper proposes a double threshold detection algorithm based on mutual trust degree correction, in order to reduce the probability of missed detection. First, the algorithm performs mutual trust correction on the local detection statistic of the information fusion center, next, performs information fusion. The algorithm reduces the influence of a single user on the detection result, which is caused by the weight distribution in the information fusion process. The algorithm makes the weight distribution in the information fusion process more reasonable and balanced. The simulation results show that the detection performance of the double threshold detection algorithm modified by the mutual trust matrix is better than that of the traditional double threshold detection algorithm.
Impact of Confusion Factor on Simulation of An Agent-based Panic Crowd Evacuation Model
Authors: Chen Xiaowei , Wang Jian
Published: August 2019

Aiming at how panic and chaos affect pedestrian behavior and evacuation efficiency, we propose a panic crowd evacuation model based on entropy. Boltzmann entropy and Shannon entropy are used to simulate people’s escape behavior in panic disorder. The simulation results suggest that the proposed model can effectively reflect the negative impact of chaos on evacuation, which leads to longer evacuation time. Compared with Shannon Entropy, Boltzmann Entropy is more sensitive to the number of persons and helpful to identify the evacuation bottleneck area. This work provides a new insight for understanding how crowds behave in an emergency evacuation.
Research on the Security Data Transmission based on Linux
Authors: Li ShuLiang , zhang Jie , Liu Youzhu
Published: August 2019

This paper develops system software in application layer based on Linux operating system. Linux operation system in this paper. Different transmission modes are adopted in different parts to improve the transmission efficiency in the network. The data capture encryption method is used for the file data, and the storage transmission method is used for the image data. It designs an identity authentication protocol and key exchange protocol based on digital certificate and digital sign technology, to avoid the sophistication and filch and improve the reliability of the identity authentication and the security of the key exchange. The common algorithms of symmetric encryption, asymmetric encryption and information digest are studied by using OpenSSL standard library function to realize data encryption module of the system.
Research on reliability evaluation method of active distribution network
Authors: Yue Chao , Qi Qiumin , Wang Yu , Wang Bojun , Zhang Xilong
Published: August 2019

The operation time of active distribution network is affected by distributed power supply, which brings complex problems including power quality, power supply reliability and relay protection, among which the reliability problem is particularly prominent. This paper discusses the component mathematical model, evaluation index and evaluation method for the reliability evaluation of active distribution network.