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Hawk‐eye‐inspired perception algorithm of stereo vision for obtaining orchard 3D point cloud navigation map

CAAI Transactions on Intelligence Technology 2023年第3期8卷 987-1001页

作者： Zichao Zhang Jian Chen Xinyu Xu Cunjia Liu Yu Han College of Engineering China Agricultural UniversityBeijingChina Jiangsu Province and Education Ministry Co‐sponsored Synergistic Innovation Center of Modern Agricultural Equipment Jiangsu UniversityZhenjiangChina Key Laboratory of Spatial‐temporal Big Data Analysis and Application of Natural Resources in Megacities MNRShanghaiChina Department of Aeronautical and Automotive Engineering Loughborough UniversityLoughboroughLeicestershireUK College of Water Resources and Civil Engineering China Agricultural UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijingChina Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhenChina

The binocular stereo vision is the lowest cost sensor for obtaining 3D *** the weakness of long‐distance measurement and stability,the improvement of accuracy and stability of stereo vision is urgently required for application of precision *** address the challenges of stereo vision long‐distance measurement and stable perception without hardware upgrade,inspired by hawk eyes,higher resolution perception and the adaptive HDR(High Dynamic Range)were introduced in this *** the function from physiological structure of‘deep fovea’and‘shallow fovea’of hawk eye,the higher resolution reconstruction method in this paper was aimed at ac-curacy *** by adjustment of pupils,the adaptive HDR method was proposed for high dynamic range optimisation and stable *** various light conditions,compared with default stereo vision,the accuracy of proposed algorithm was improved by 28.0%evaluated by error ratio,and the stability was improved by 26.56%by disparity *** fixed distance measurement,the maximum improvement was 78.6%by standard *** on the hawk‐eye‐inspired perception algorithm,the point cloud of orchard was improved both in quality and *** hawk‐eye‐inspired perception algorithm contributed great advance in binocular 3D point cloud recon-struction in orchard navigation map.

关键词： adaptive high dynamic range binocular stereo vision hawk‐eye‐inspired perception point cloud of orchard super‐resolution generative adversarial network

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virtual-real fusion system integrated with multiple videos

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Ruan Jian Xue Bao/Journal of Software 2016年 27卷 197-206页

作者： Pan, Cheng-Wei Zhang, Jian-Guo Wang, Shao-Rong Wang, Guo-Ping School of Electronics Engineering and Computer Science Peking University Beijing100871 China Beijing Engineering Research Center for Virtual Simulation and Visualization Beijing100871 China

This paper proposes a method for constructing a virtual-real fusion system integrated with multiple videos aiming to create an augmented virtual environment, where images and videos captured from real world are fused to virtual scene. With the help of textures from images and motion from videos, the virtual environment is more realistic. Unmanned Aerial Vehicles are used to take photos and reconstruct the 3D virtual scene. By matching features, video frames can be registered to the virtual environment. Then images are projected to virtual scene with the method of projective texture mapping. Due to lack of the corresponding 3D models in the virtual environment, distortions will occur when images are directly projected and the viewpoint changes. This paper first detects and tracks those moving objects, then it gives multiple ways of displaying moving objects to solve the distortion problem. Fusion of multiple videos with overlapping areas in the virtual environment is also considered in this system. The experimental results show that the virtual-real fusion environment that is build based in this paper has lots of benefits and advantages. © Copyright 2016, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： virtual reality

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Visual Analysis for Wildlife Preserve based on Muti-systems

Visual Analysis for Wildlife Preserve based on Muti-systems

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IEEE Symposium on Visual Analytics Science and Technology (VAST)

作者： Lijing Lin Min Lu Guozheng Li Shuai Chen Chufan Lai Ruike Jiang Qiangqiang Liu Xiaoru Yuan Key Laboratory of Machine Perception (Ministry of Education) and School of EECS Peking University Key Laboratory of Machine Perception (Ministry of Education) and School of EECS Peking University Beijing Beijing CN Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Peking University

In the Grand Challenge of IEEE VAST Challenge 2017, we explore the systems in each mini-challenge, and combine the discoveries logically to provide a comprehensive story happened in the wildlife preserve. In this report, we present technical details for the systems, in order to discuss how to discover the events, and how to combine them to construct an overall picture considering the additional information, newsletter, in the Grand Challenge.

关键词： Trajectory Production facilities Chemicals Visual analytics Chemical sensors Sensors

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Heat transfer of non-condensable gas to pulsating heat pipe based on BP neural network model

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Huagong Jinzhan/Chemical Industry and engineering Progress 2020年第7期39卷 2574-2582页

作者： Chen, Jingyan Xu, Rongji Wu, Qingping Wang, Ruixiang Xu, Shuhui National Virtual Simulation Demonstration Center for Experimental Energy and Buildings Education Beijing University of Civil Engineering and Architecture Beijing100044 China School of Energy and Power Engineering Xi'an Jiaotong University Xi'anShaanxi710049 China

The existence of non-condensable gas will affect the heat transfer performance of pulsating heat pipe. In this paper, the thermal resistance and evaporation process of pulsating heat pipe in stable operation was analyzed with deionized water and polyacrylamide solution as working fluid. The influence of the presence of non-condensable gas on the heat transfer performance and operation characteristics of pulsating heat pipe was studied. By building a BP neural network model, the regression prediction of thermal resistance characteristics of pulsating heat pipe under different pressure conditions was made and verified. The experimental results showed that the existence of non-condensable gas will deteriorate the heat transfer characteristics of pulsating heat pipe. With the increase of heating power, the thermal resistance under different partial pressures of non-condensable gas showed a downward trend. With the increase of partial pressure of non-condensable gas, the average temperature of evaporation section of working fluid increases obviously. BP neural network can be used to make reliable regression prediction for the thermal resistance of pulsating heat pipe, and provide a judgment idea for the operation status of pulsating heat pipe. © 2020, Chemical Industry Press. All right reserved.

关键词： Heat resistance

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Effect of Annealing Pretreatment on Performance of Pulsating Heat Pipe

Effect of Annealing Pretreatment on Performance of Pulsating...

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2019 International Conference on Advanced Electrical, Mechatronics and Computer engineering(AEMCE 2019)

作者： Jia-qi SHI Rui-xiang Wang Rong-ji XU National Virtual Simulation Demonstration Center for Experimental Energy and Buildings Education School of Environment and Energy EngineeringBeijing University of Civil Engineering and Architecture

Experimental work was carried out to clarify the thermal performance of a pulsating heat pipe(PHP) with the tube body was pretreated by a muffle furnace at 500°Cfor 5 hours. It is found that the annealing of the pipe body improves the wettability of the working fluid on the tube wall, thus enhance heat transfer between the tube wall and working fluid due to the increase in the liquid film area. Experimental results show that after annealing, the PHP starts to accelerate. Comparing to the original PHP, the starting time of the surface annealed PHP can be shortened by 78 s at 30 W while the minimum starting power is reduced from 30 W to 16 W and the starting temperature can be reduced by about 10°C.

关键词： Pulsating heat pipe (PHP) Annealing pretreatment Thermal performance Thermal resistance

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Behavior analysis through collaborative visual exploration on trajectory data

Behavior analysis through collaborative visual exploration o...

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IEEE Symposium on Visual Analytics Science and Technology (VAST)

作者： Tangzhi Ye Youfeng Hao Zhenhuang Wang Chufan Lai Siming Chen Zongru Li Jie Liang Xiaoru Yuan Key Laboratory of Machine Perception (Ministry of Education) Peking University Key Laboratory of Machine Perception (Ministry of Education) and School of EECS Peking University China Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Peking University

In VAST Challenge 2015, we proposed a collaborative visual exploration system for behavior analysis over trajectory records. We discuss technical details in this report, in order to deliberate how the system supports multiple users to collaboratively analyze the same data, assist in sharing their findings, and constructing an overall picture of their insights.

关键词： Trajectory Collaboration Data visualization Visual analytics Logic gates Electronic mail

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FluidPlaying: Efficient Adaptive simulation for Highly Dynamic Fluid

FluidPlaying: Efficient Adaptive Simulation for Highly Dynam...

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virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Sinuo Liu Xiaojuan Ban Sheng Li Haokai Zeng Xiaokun Wang Yanrui Xu Fei Zhu Guoping Wang Graphics & Interaction Lab National Biomedical Imaging Center School of Computer Science Peking University School of Intelligence Science and Technology University of Science and Technology Beijing Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Peking University Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)

We present FliudPlaying, a novel dynamic level-based spatially adaptive simulation method that can handle highly dynamic fluid efficiently. To capture the subtle detail of the fluid surface, the high-resolution simulation is performed not only at the free surface but also at those regions with high vorticity levels and velocity difference levels. To minimize the density error, an online optimization scheme is used when increasing the resolution by particle splitting. We also proposed a neighbor-based splash enhancement to compensate for the loss of dynamic details. Compared with the high-resolution simulation baseline, our method can achieve over 3× speedups while consuming only less than 10% computational resources. Furthermore, our method can make up for the loss of high-frequency details caused by the spatial adaptation, and provide more realistic dynamics in particle-based fluid simulation.

关键词： Solid modeling Adaptation models Three-dimensional displays Fluid dynamics Computational modeling Conferences virtual reality

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An Improved Track Circuit Fault Prediction Method Based on Attention Mechanism and Data Adaptation

TechRxiv

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TechRxiv 2022年

作者： Na, Lan Dai, Shenghua Li, Zhaoyi Liang, Xuji The National Rail Transit Communication and Control Virtual Simulation Experiment Teaching Center School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China

Track circuit is one of the most important parts of train operation control system. In current railway transportation research area, track circuit intelligent maintenance, including fault diagnosis and prediction is mainly achieved by using deep learning (DL). However, the application of DL models in practical has a great limitation. The training of track circuit intelligent maintenance DL models requires huge amount of labeled data. And DL models are too fragile since real data and training data can hardly meet the requirement of independent and identically distributed. In this paper, attention mechanism is introduced into track circuit fault prediction model first time to make the proposed DL model. And to enhance the practical performance of the DL model, a deep data adaptation algorithm is applied to make an improved method to overcome degradation problem caused by non-identically distributed of training and real data. Moreover, it can be also applied to reduce data dependence of the DL model training. To evaluate the performance of the proposed DL model and the improved method, experiments were carried out based on real data from China Railway Shenyang Group Company Limited computer monitoring system. The experimental results show that the proposed model has a better performance than DL model without attention mechanism, the improved method has a better performance than conventional methods without deep data adaptation algorithms, and the proposed deep data adaptation algorithm has a better performance than conventional algorithms. The proposed track circuit fault prediction model can provide fault prediction results with an accuracy better than 97%. Compared with the conventional fault prediction DL model without transfer learning, the improved method can achieve a much better performance, with an improvement, in the test, of over 75%. And the proposed deep data adaptation algorithm can make an accuracy improvement, in the test, of over 30% than conventional d

关键词： Failure analysis

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The State of Charge Estimation of Lithium-ion Batteries Using an Improved Extreme Learning Machine Approach

The State of Charge Estimation of Lithium-ion Batteries Usin...

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第34届中国控制与决策会议

作者： Wei He Hongyan Ma Yingda Zhang Shuai Wang Jiaming Dou Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture National Virtual Simulation Experimental Center for Smart City Education

Accurate state of charge(SOC) estimation is of great significance for a lithium-ion battery to ensure its safe operation and prevent it from over-charging or ***,it is difficult to get an accurate value of SOC since it is an inner state of a battery cell,which cannot be directly *** order to improve the estimation accuracy of SOC,this paper develops a SOC estimation model for a lithium-ion battery using a Particle Swarm Optimization-Extreme Learning Machine(PSO-ELM) *** PSO is applied to determine the optimal value of hidden layer neurons and the learning rate since these parameters are the most critical factors in constructing an optimal ELM *** inputs to the PSO-ELM model are the battery voltage,current,and temperature,and the output is the actual SOC *** performance of the proposed model is compared with BP neural network and ELM models and verified based on the mean square error(MSE),mean absolute error(MAE),mean absolute percentage error(MAPE),and SOC *** results demonstrate that the PSO-ELM model offers higher accuracy and lower SOC error rate than ELM and BP neural network models.

关键词： Lithium-ion Battery State of Charge Particle Swarm Optimization Algorithm Extreme Learning Machine

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Surface crack width measurement based on digital image processing

Surface crack width measurement based on digital image proce...

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第34届中国控制与决策会议

作者： Zongyuan Xie Hongyan Ma Yongxue Ye Jiaming Dou Shengyan Li Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture National Virtual Simulation Experimental Center for Smart City Education

Cracks are common and dangerous hazards in *** at the defects of low accuracy and poor feasibility in traditional crack width detection,proposing a crack width measurement method based on an orthogonal skeleton ***,the crack image is processed by ***,the processed image is median filtering and threshold ***,the skeleton and outline of the crack image were extracted by this method,and the measurement and comparison of simulated cracks and actual cracks are *** simulation results show that this method has high accuracy and feasibility and can meet the accuracy of engineering practice.

关键词： OpenCV Crack width measurement Orthogonal skeleton line Image processing

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