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Chinese automation Congress (CAC)

作者： Yuanhao Shi Tianxiang Han Fangshu Cui Jie Wen Gangzhu Qiao School of Electrical and Control Engineering North University of China Taiyuan China Department of Automation Ministry of Education of China Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China School of Data Science and Technology North University of China Taiyuan China

In response to the problem that ash deposition in boilers has a great impact on production efficiency as well as production safety, a grey level theory prediction model based on time convolution networks (GM-TCN) is proposed to predict the degree of ash in boiler heated areas by using a cleaning factor to assess the ash deposition condition on the heated surfaces. The accuracy of the prediction model is improved by utilizing the features of grey level theory that can predict the developmental changes in system behavior, combined with the high-precision approximation capability of the time-convolutional network. The modelling prediction of the ash level in the heated area of boilers during the production of coal-fired power stations is investigated. Experiments demonstrate that the model can predict the cleanliness factor with high accuracy, and the predicted values are closest to the true values compared to the other two models, verifying the accuracy and reliability of the model.

关键词： Cogeneration Time series analysis Ash Production Predictive models Boilers Data models

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Insulating materials for realising carbon neutrality:Opportunities,remaining issues and challenges

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High Voltage 2022年第4期7卷 610-632页

作者： Chuanyang Li Yang Yang Guoqiang Xu Yao Zhou Mengshuo Jia Shaolong Zhong Yu Gao Chanyeop Park Qiang Liu Yalin Wang Shakeel Akram Xiaoliang Zeng Yi Li Fangwei Liang Bin Cui Junpeng Fang Lingling Tang Yulin Zeng Xingtao Hu Jiachen Gao Giovanni Mazzanti Jinliang He Jianxiao Wang Davide Fabiani Gilbert Teyssedre Yang Cao Feipeng Wang Yunlong Zi The State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Simpson Querrey Institute Northwestern UniversityEvanstonIllinoisUSA Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA Department of Information Technology and Electrical Engineering ETH ZürichZürichSwitzerland School of Electrical and Information Engineering Tianjin UniversityTianjinChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina College of Electrical Engineering Sichuan UniversityChengduChina Shenzhen Institute of Advanced Technology Chinese Academy of Sciences ShenzhenShenzhenChina School of Electrical Engineering Wuhan UniversityWuhanChina School of Integrated Circuits Tsinghua UniversityBeijingChina Jiangsu Jinxin Electric Appliance Co.Ltd. YangzhouChina Tai'an Tiancheng Safety Evaluation Co. Ltd.Tai'anChina Department Electrical Electronic and Information EngineeringUniversity of BolognaBolognaItaly National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijingChina Laplace Paul Sabatier Universityand CNRSToulouseFrance Electrical and Computer Engineering University of ConnecticutStorrsConnecticutUSA State Key Laboratory of Power Transmission Equipment&System Security and New Technology School of Electrical EngineeringChongqing UniversityChongqingChina Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)GuangzhouChina De

The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment *** material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and *** goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first *** engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are *** materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being *** the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material *** is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality *** authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.

关键词： neutral insulation extreme

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Intelligent intersection scheduling based on vehicle traffic priority

Intelligent intersection scheduling based on vehicle traffic...

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第40届中国控制会议

作者： Zhengxin Ruan Sicong Chen Yuanlong Li Liangren Shi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

This paper proposes an intelligent intersection management method based on the vehicle dynamic priority. By the information interaction between the autonomous vehicles（AVs） and the infrastructure equipment, the vehicle position and posture information is obtained in real time, and the priority of the vehicles passing through the conflict points in the scene is determined according to the order of the vehicles driving through the crossroads. Subsequently, to track the planned trajectory, we use the model predictive control（MPC） algorithm minimize the intersection delay with collision-free constraints. This guarantees the vehicles to drive through the intersection safely in the scene. Simulation experiments demonstrate the reliability and efficiency of the proposed algorithm.

关键词： Autonomous vehicle Intersection management system Vehicle-to-infrastructure communication Dynamic priority Model predictive control

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Data-Driven Distributionally Robust Mixed-Integer control through Lifted control Policy

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IEEE Transactions on Automatic control 2025年

作者： Ma, Xutao Ning, Chao Du, Wenli Shi, Yang Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China University of Victoria Department of Mechanical Engineering VictoriaBCV8W 3P6 Canada

This paper investigates the finite-horizon distributionally robust mixed-integer control (DRMIC) of uncertain linear systems. However, deriving an optimal causal feedback control policy to this DRMIC problem is computationally formidable for most ambiguity sets. To address the computational challenge, we propose a novel distributionally robust lifted control policy (DR-LCP) method to derive a high-quality approximate solution to this DRMIC problem for a rich class of Wasserstein metric-based ambiguity sets, including the Wasserstein ambiguity set and its variants. In theory, we analyze the asymptotic performance and establish a tight non-asymptotic bound of the proposed method. In numerical experiments, the proposed DR-LCP method empirically demonstrates superior performance compared with existing methods in the literature. ©1963-2012 IEEE.

关键词： Mixed-integer linear programming

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Error-state Kalman Filtering with Linearized State Constraints

TechRxiv

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TechRxiv 2023年

作者： Do, Hoang Viet Jung, Jae Hyung Park, Chan Gook Song, Jin Woo The Intelligent Navigation and Control Systems Laboratory Department of Convergence Engineering for Intelligent Drone School of Intelligent Mechatronics Engineering Sejong University Seoul05006 Korea Republic of The Department of Aerospace Engineering Automation and Systems Research Institute Seoul National University Seoul08826 Korea Republic of The Navigation and Electronic System Laboratory Department of Aerospace Engineering Institute of Advanced Aerospace Technology Seoul National University Seoul08826 Korea Republic of

In recent years, the error-state Kalman filter (ErKF) has been extensively employed across various applications, including but not limited to robotics, aerospace, and localization. However, incorporating constraints into the ErKF framework when state constraint is necessary has remained a challenging task due to its intrinsic properties. This paper explores all possible ways to achieve this goal in the context of the estimate projection method. In particular, the constraint can be enforced before or after the ErKF’s correction step. We approach the problem from a mathematical perspective by deriving analytical solutions and discussing their statistical properties. We prove that the two mentioned methods are statistically identical for a linear system with linear constraints. Conversely, the filter’s behavior remains uncertain in the presence of linearized constraints. However, we provide a special case of the nonlinear constraint, wherein the results of the linear case remain valid. To support our theorem and verify the filter’s performance when the assumptions are invalidated, we present two Monte Carlo simulations under the increasing initialization error and the constraint’s incompleteness. The simulation results clearly confirm our insights and lead to the conclusion that constraining the error-state after the correction may offer superior outcomes compared to its competitor. © 2023, CC BY.

关键词： Linearization

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An Accelerated Gossip-Based Distributed Gradient Method

An Accelerated Gossip-Based Distributed Gradient Method

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第40届中国控制会议

作者： Xiaoxing Ren Dewei Li Yugeng Xi Haibin Shao Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai Engineering Research Center of Intelligent Control and Management

This paper studies distributed optimization over the multi-agent network. We develop and analyze a novel accelerated distributed gradient descent method, termed as G-DGDlm, for gossip communication protocol. G-DGDlm uses gradient tracking technique and local memory. Specifically, each agent stores two past variables, namely, an estimate of the average gradient and an estimate of the optimal solution. G-DGDlm achieves linear convergence for strongly convex and smoot√h functions when the related works, we remove the dependence of θ on global parameters and G-DGDlm is applicable to gossip communication protocol. Numerical experiments of distributed estimation in sensor networks show the faster convergence speed of G-DGDlm in comparison with the state-of-the-art methods.

关键词： Distributed convex optimization gossip communication first-order methods

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Construction of Minecraft Virtual Reality Scene Based on Voxel Point Cloud 8th

Construction of Minecraft Virtual Reality Scene Based on Vox...

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8th International Conference on Cognitive systems and Information Processing, ICCSIP 2023

作者： Ji, Nuocheng Zhuang, Hanyang Yang, Ming The University of Michigan – Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Global Institute of Future Technology Shanghai Jiao Tong University Shanghai200240 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9789819980208

Virtual Reality is an important development direction in recent years. Minecraft, a popular sandbox game, has a great potential to become a virtual reality platform for building immersive environments. Traditional methods of building virtual reality scenes rely heavily on massive human labors and require high levels of proficiency. To address these limitations, we propose an automatic, voxelated 3D modeling method with foreground and background environment segmented that can reduce modeling costs and achieve effective application in Minecraft virtual reality scenes such as virtual campuses. The proposed method leverages the use of point cloud reconstruction using a voxelization approach. A pipeline of converting point cloud to Minecraft scene is developed. Through preprocessing, segmenting, coloring, and exporting, a Minecraft virtual reality scene can be automatically generated based on voxel point cloud. Due to the noise in point cloud may cause defect during voxelization, a denoising and smoothing method using slice scanning and voxel connectivity segmentation has been implemented. It can generate building structures with clear outlines and uniform colors. And the entire process requires low computational complexity and achieves fast generation. We conducted experiments based on this method in indoor scenes, outdoor building landmarks, and complex underground scenes, and obtained results with clear structures and smooth surfaces, saving a lot of time for subsequent detailed modeling. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： 3D modeling

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New Sensing Technologies for Monitoring Machinery,Structures,and Manufacturing Processes

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Journal of Dynamics, Monitoring and Diagnostics 2023年第2期2卷 69-88页

作者： JDMD Editorial Office Zhaoyan Fan Robert X.Gao Qingbo He Yi Huang Tianxi Jiang Zhike Peng Luc Thévenaz Yuyong Xiong Shuncong Zhong Editorial Office of JDMD Chongqing University of TechnologyChongqingPeople’s Republic of China Department of Mechanical Industrialand Manufacturing EngineeringOregon State UniversityCorvallisORUSA Department of Mechanical and Aerospace Engineering Case Western Reserve UniversityClevelandOHUSA State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghaiPeople’s Republic of China Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and AutomationFuzhou UniversityFuzhouPeople’s Republic of China Institute of Precision Instrument and Intelligent Measurement&Control Fuzhou UniversityFuzhouPeople’s Republic of China School of Mechanical Engineering Ningxia UniversityYinchuanPeople’s Republic of China EPFL Ecole Polytechnique Fédérale de Lausanne Group for Fibre OpticsSCI-STI-LT Station 111015 LausanneSwitzerland

Sensing is the fundamental technique for sensor data acquisition in monitoring the operation condition of the machinery,structures,and manufacturing *** this paper,we briefly discuss the general idea and advances of various new sensing technologies,including multiphysics sensing,smart materials and metamaterials sensing,microwave sensing,fiber optic sensors,and terahertz sensing,for measuring vibration,deformation,strain,acoustics,temperature,spectroscopic,*** on the observations from the state of the art,we provide comprehensive discussions on the possible opportunities and challenges of these new sensing technologies so as to steer future development.

关键词： fiber optic sensor metamaterials sensing microwave sensing multiphysics sensing terahertz sensing

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Visual Module R&D of the Intelligent Grabbing system of WIFI Module

Visual Module R&D of the Intelligent Grabbing System of WIFI...

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International Conference on Application of Intelligent systems in Multi-modal Information Analytics, MMIA 2020

作者： Ma, Shufang Wu, Jiang Jiao, Shuangben Xue, Bin Engineering and Technology R&D Center of Mechanical and Electrical in Colleges of Shandong Qingdao Binhai University QingdaoShandong266555 China School of Mechanical and Electrical Engineering Qingdao Binhai University QingdaoShandong266555 China Qingdao Zhongzhuang Vision Automation System Control Co. Ltd. QingdaoShandong266555 China

ISBN: (纸本)9783030514303

WiFi module intelligent grabbing system based on visual guidance is established by taking MV-CH120-10GM industrial camera and Siemens S7-200smartPLC as the hardware basis designated to realize identification and positioning grabbing of WiFi module. Hardware selection and imaging processing is studied based on visual module, and visual identity and positioning algorithm is developed by taking VisionPro9.0 as the platform. Meanwhile, logical judgment on imaging processing result is carried out by using the software Vision Studio C#. Besides, visual windows is used for inspecting image and data display. Through experimental verification, it is ultimately indicated that the visual algorithm features higher identification and positioning accuracy and satisfies the requirements of the grabbing system. © 2021, Springer Nature Switzerland AG.

关键词： Computer vision

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Automatic visual inspection system for injection molding parts of automobile center console

Automatic visual inspection system for injection molding par...

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International Conference on Application of Intelligent systems in Multi-modal Information Analytics, MMIA 2020

作者： Chi, Wenqing Xue, Bin Li, Xiaofei Zhang, Yuhang Jiao, Shuangben Engineering and Technology R&D Center of Mechanical and Electrical in Colleges of Shandong Qingdao Binhai University QingdaoShandong266555 China School of Mechanical and Electrical Engineering Qingdao Binhai University QingdaoShandong266555 China Qingdao Zhongzhuang Vision Automation System Control Co. Ltd. QingdaoShandong266555 China

ISBN: (纸本)9783030515553

For the pattern position deviation and installation error detection of injection molding parts in the automobile center console, the traditional method is to use the secondary dimensional detection equipment, which has low detection efficiency and can only realize sampling detection. In order to solve this problem, a detection method based on machine vision is proposed, which uses 4 K linear array camera with linear light source to collect the image, and the collected image is transmitted to the computer for processing. The image processing is carried out on the VisionPro 9.0 software platform. Firstly, the image of the injection molding part is corrected and the coordinate is located by the method of extracting the feature points from the image mask. Then, the script programming is used to judge. Finally, the detection of the pattern position deviation and installation error prevention on the injection molding part is realized, and the result information is displayed on the computer. Through the operation test, the accuracy of the system reaches 0.05 mm, the detection cycle is 6–10 s, the detection rate is 99.9%, the efficiency is increased by 50 times, the quality is improved by 80%, and the problems existing in the detection of the secondary detection equipment are effectively solved. © Springer Nature Switzerland AG 2021.

关键词： Computer vision

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