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Towards additive manufacturing oriented geometric modeling using implicit functions

Visual Computing for Industry,Biomedicine,and Art 2018年第1期1卷 95-110页

作者： Qingde Li Qingqi Hong Quan Qi Xinhui Ma Xie Han Jie Tian School of Engineering and Computer Science University of HullHull HU67RXUK Software School Xiamen UniversityXiamenChina School of Computer Science and Control Engineering North University of ChinaTaiyuanChina Intelligent Bioinformatics Systems Division Institute of AutomationThe Chinese Academy of SciencesBeijingChina

Surface-based geometric modeling has many advantages in terms of visualization and traditional subtractive manufacturing using computer-numerical-control cutting-machine ***,it is not an ideal solution for additive manufacturing because to digitally print a surface-represented geometric object using a certain additive manufacturing technology,the object has to be converted into a solid ***,converting a known surface-based geometric representation into a printable representation is essentially a redesign process,and this is especially the case,when its interior material structure needs to be *** specify a 3D geometric object that is ready to be digitally manufactured,its representation has to be in a certain volumetric *** this research,we show how some of the difficulties experienced in additive manufacturing can be easily solved by using implicitly represented geometric *** surface-based geometric representation is subtractive manufacturing-friendly,implicitly described geometric objects are additive manufacturing-friendly:implicit shapes are 3D printing *** implicit geometric representation allows to combine a geometric shape,material colors,an interior material structure,and other required attributes in one single description as a set of implicit functions,and no conversion is *** addition,as implicit objects are typically specified procedurally,very little data is used in their specifications,which makes them particularly useful for design and visualization with modern cloud-based mobile devices,which usually do not have very big storage ***,implicit modeling is a design procedure that is parallel computing-friendly,as the design of a complex geometric object can be divided into a set of simple shape-designing tasks,owing to the availability of shape-preserving implicit blending operations.

关键词： Additive manufacturing 3D printing-friendly CAD Implicit function Isosurface Level-set Function-based shape modeling Implicit modeling

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Data-Driven Modeling & Analysis of Dynamic Wake for Wind Farm control: A Comparison Study

Data-Driven Modeling & Analysis of Dynamic Wake for Wind Far...

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Chinese Automation Congress (CAC)

作者： Zhenyu Chen Bart M Doekemeijer Zhongwei Lin Zhen Xie Zongming Si Jizhen Liu Jan-Willem van Wingerden State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control Computer and Engineering North China Electric Power University Beijing China Delft Center for Systems and Control (DCSC) Faculty of Mechanical Maritime and Materials Engineering (3mE) Delft University of Technology The Netherlands CHN ENERGY (Shandong) New Energy Co. Ltd Jinan PR China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

For the study of wind farm and wake effect, the steady-state wake models like FLORIS were proposed and used during wind farm operations to achieve higher wind power utilization and conversion. However, the dynamic performance of the wake should also be involved in favor of better optimizations. In this paper, a data-driven analysis and modeling method, dynamic mode decomposition (DMD), is used to construct dynamic flow model with high-fidelity flow data. Two DMD-derived models are constructed based on flow data in three-dimensional and two-dimensional spaces, respectively. The obtained models and respective flows are compared in the time and frequency domain. Results show that both models have apparent differences in the frequency domain, but the dominant wake characteristics' consistency is maintained.

关键词： Wind turbines Wind farms Analytical models Mathematical model Computational modeling Solid modeling Wind speed

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Multi-objective optimization of wind farm dispatch problem by double-layer particle swarm optimization algorithm 8

Multi-objective optimization of wind farm dispatch problem b...

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8th IEEE Data Driven control and Learning Systems Conference, DDCLS 2019

作者： Guo, Qiang Huang, Congzhi Xue, Zhiwei Zhang, Longying Lu, Xiaohui Zhang, Songtao State Grid Shanxi Electric Power Research Institute Taiyuan030001 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China State Grid Shanxi Electric Power Company Taiyuan030001 China

ISBN: (纸本)9781728114545

In the process of power dispatch of the wind turbines, the frequent start-up and shut-down will accelerate the performance degradation of the wind turbines. The strategy of adjusting the power output of each wind turbine through the pitch angle of the blade control system will also reduce the stability margin of wind turbines. In order to reduce the loss caused by frequent changes of start-up and shut-down and improve the stability margin of wind turbines, the double-layer particle swarm optimization (DLPSO) algorithm is proposed, including the binary particle swarm optimization (BPSO) algorithm in the outer layer, and the self-adjusting chaotic particle swarm optimization (SACPSO) algorithm in the inner layer. The wind turbine dispatch model is established, wherein the times of start-up and shut-down, and the mean value of the power limitation index are taken into account in the objective function. Based on the wind turbine dispatch model, the DLPSO algorithm is employed to solve the wind turbine dispatch problem. Extensive experimental results are finally presented to demonstrate the validity and effectiveness of the proposed DLPSO algorithm and the wind turbine dispatch model. © 2019 IEEE.

关键词： Multiobjective optimization

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Performance Analysis of Dual-Hop Mixed FSO/mmWave Systems

Performance Analysis of Dual-Hop Mixed FSO/mmWave Systems

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IEEE International Conference on Communications Workshops, ICC

作者： Yan Zhang Jiayi Zhang Liang Yang Dinh-Thuan Do Bo Ai School of Electronic and Information Engineering Beijing Jiaotong University Beijing China College of Computer Science and Electronic Engineering Hunan University Changsha China Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Vietnam State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

The combination of free-space optical (FSO)-based backhaul links and millimeter wave (mmWave)-based access links is considered as a key enabling technique to provide enhanced mobile broadband in ultra dense networks. In this paper, the generalized end-to-end performance of a dual-hop mixed FSO/mmWave relaying system is evaluated. The FSO link is assumed to follow the Gamma-Gamma fading with pointing error impairments, while the mmWave link experiences the fluctuating two-ray fading. Both heterodyne detection and indirect modulation/direct detection are accounted for in the FSO link. Using both amplify-and-forward and decode-and-forward relaying schemes, novel closed-form expressions for the outage probability and average bit error probability (BER) are derived in terms of bivariate Fox's H-functions. Furthermore, an asymptotic analysis for the outage probability and the average BER is provided to show the diversity order and other important engineering insights. Finally, the accuracy of our derived results is validated through Monte-Carlo simulations.

关键词： Radio frequency Fading channels Signal to noise ratio Relays Optical transmitters Power system reliability Probability

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Method for Latency Measurement of Visual Feedback-Based Master–Slave Minimally Invasive Surgical Robot

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Transactions of Tianjin University 2018年第4期24卷 375-386页

作者： Jinhua Li Jingchao Shen He Su Shuxin Wang Jianmin Li School of Mechanical Engineering Tianjin UniversityTianjin 300350China College of Computer and Control Engineering Nankai UniversityTianjin 300350China Key Laboratory for Mechanism Theory and Equipment Design of Ministry of

To measure the latency between human motion stimulation and stereo image display response in a visual feedback-based minimally invasive surgical(MIS) robotic system,a method was proposed by comparing the orientations of input and output events through image-processing technology. This method used a black bar to keep pace with the measured joint rotating at a number of speeds. During tests,an external camera was placed in front of the apparatus with a proper visual field,so that it can simultaneously view orientations of both bars fixed on the corresponding joints. After quantitatively analyzing the accuracy of the proposed measurement method,the method was applied to a visual feedback-based master–slave robotic system with two-degrees-of-freedom. Experimental results show that the latency of the overall system was approximately 250 ms,and the opposite clearance of the measured joint was in the range of 1.7°–1.9°.

关键词： Minimally invasive surgical(MIS)robot Latency measurement Real time Visual feedback

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Short-term Wind Power Prediction Method Based on Wavelet Packet Decomposition and Improved GRU 1

Short-term Wind Power Prediction Method Based on Wavelet Pac...

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1st International Conference on Advanced Algorithms and control engineering, ICAACE 2018

作者： Zu, X.R. Song, R.X. School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Accurately predicting wind power in wind farms is of great significance to ensure the safe and stable operation of the power system. A novel short-term wind power forecasting method (WPD-GRU-SELU) based on wavelet packet decomposition (WPD) and improved gated recurrent unit (GRU) is proposed. Firstly, this method uses WPD to decompose the time series of wind power into several sub-sequences with different frequencies. Then the sub-sequences of different frequency components are predicted by using the improved GRU neural network, which uses the scaled exponential linear units(SELU) as the activation function to squash the hidden states to calculate the output. Finally, the output datum of GRU neural networks are reconstructed to obtain the complete wind power predicting results. Experiments illustrate that the WPD-GRU-SELU model have a more accurate forecast to the short-term wind power prediction compared with other RNN models. © Published under licence by IOP Publishing Ltd.

关键词： Wavelet decomposition

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Network Traffic Classification Based on Deep Learning 1

Network Traffic Classification Based on Deep Learning

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1st International Conference on Advanced Algorithms and control engineering, ICAACE 2018

作者： Shu, Jun Hua Jiang, Jiang Sun, Jing Xuan School of Control and Computer Engineering North China Electric Power University Beijing102206 China

With the rapid development of the Internet, the network has been expanding. In order to allow network operators to provide better quality of service, but also the effective supervision and management of the network, identify the traffic type of network traffic classification technology has become a hot topic in recent years. In this paper, a method of network traffic classification based on deep learning is proposed. Compared with the traditional machine learning method, the accuracy of network traffic classification based on deep learning has been improved obviously. © Published under licence by IOP Publishing Ltd.

关键词： Quality of service

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A Data Fusion Algorithm and Simulation Based on TQMM 11th

A Data Fusion Algorithm and Simulation Based on TQMM

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11th EAI International Conference on Simulation Tools and Techniques, SIMUTools 2019

作者： Zhang, Ke Wang, Zeyang Li, Huiling School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Science and Technology on Electronic Information Control Laboratory Chengdu610000 China Sichuan Jiuzhou Electronic Technology Co. Ltd. Mianyang621000 China School of Communication and Information Engineering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9783030322151

Asynchronous data fusion is more practical than synchronous data fusion, the model of track-to-track fusion in this case has been established and the concept of Track Quality with Multiple Model (TQMM) was put forward, furthermore a data fusion algorithm is proposed, in which the TQMM is used to assign weights, to improve tracking precision in asynchronous multi-sensor data fusion system. The simulation results show that the algorithm has a better tracking performance compared with original algorithms. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2019.

关键词： Sensor data fusion

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Temperature prediction of combustion layers for 660MW ultra supercritical unit through the VIP-SR

Temperature prediction of combustion layers for 660MW ultra ...

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2018 IEEE International Conference on Information and Automation, ICIA 2018

作者： Li, Xinli Zhu, Yun Yang, Guotian Liu, He School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9781538680698

The temperature of furnace is the key to the safety of boiler and energy conservation. In this paper, the prediction modeling of temperature of different combustion layers (bottom, middle and upper) are proposed based on the variable importance in the projection(VIP) of partial least square (PLS) combined with stepwise regression (SR) for the 660MW ultra supercritical unit. The temperature of different combustion layers are measured through the infrared temperature measurement devices. The variables are selected by using the variable importance in the projection, which are important factors of affecting the temperature. Combined with stepwise regression method, the temperature prediction models of three layers are established in the low load operation of boiler. At the same time, temperature modeling using support vector machines (SVM) is compared with VIP-SR method. According to the operation data of power plant, the simulation results have shown the effectiveness of the proposed method. © 2018 IEEE.

关键词： Combustion

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Generative Adversarial Networks (GAN) powered fast magnetic resonance imaging - Mini review, comparison and perspectives

arXiv

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arXiv 2021年

作者： Yang, Guang Lv, Jun Chen, Yutong Huang, Jiahao Zhu, Jin National Heart & Lung Institute Imperial College London LondonSW7 2AZ United Kingdom Cardiovascular Research Centre Royal Brompton Hospital LondonSW3 6NP United Kingdom School of Computer and Control Engineering Yantai University Yantai China Department of Physiology Development and Neuroscience University of Cambridge CB2 3EG United Kingdom School of Optics and Photonics Beijing Institute of Technology Beijing China Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom

Magnetic Resonance Imaging (MRI) is a vital component of medical imaging. When compared to other image modalities, it has advantages such as the absence of radiation, superior soft tissue contrast, and complementary multiple sequence information. However, one drawback of MRI is its comparatively slow scanning and reconstruction compared to other image modalities, limiting its usage in some clinical applications when imaging time is critical. Traditional compressive sensing based MRI (CS-MRI) reconstruction can speed up MRI acquisition, but suffers from a long iterative process and noise-induced artefacts. Recently, Deep Neural Networks (DNNs) have been used in sparse MRI reconstruction models to recreate relatively high-quality images from heavily undersampled k-space data, allowing for much faster MRI scanning. However, there are still some hurdles to tackle. For example, directly training DNNs based on L1/L2 distance to the target fully sampled images could result in blurry reconstruction because L1/L2 loss can only enforce overall image or patch similarity and does not take into account local information such as anatomical sharpness. It is also hard to preserve fine image details while maintaining a natural appearance. More recently, Generative Adversarial Networks (GAN) based methods are proposed to solve fast MRI with enhanced image perceptual quality. The encoder obtains a latent space for the undersampling image, and the image is reconstructed by the decoder using the GAN loss. In this chapter, we review the GAN powered fast MRI methods with a comparative study on various anatomical datasets to demonstrate the generalisability and robustness of this kind of fast MRI while providing future *** Codes 68T01 Copyright © 2021, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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