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2022 Chinese automation Congress, CAC 2022

作者： Guo, Renjie Feng, Jun Yang, Huachang Luan, Dejie Yang, Guodong Li, En Institute of Automation CAS State Key Laboratory of Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China China Academy of Railway Sciences Corporation Limited Signal & Communication Research Institute Beijing100081 China

ISBN: (纸本)9781665465335

In the construction of automated marshaling yards, the automatic uncoupling operation of freight trains has always been the research and development direction. The coupler rod is the operation object of the uncoupling operation. The identification of coupler rod type and estimating position and posture are the prerequisites to realizing automatic uncoupling operation. In this paper, we propose a perception method of coupler rod by RGB image combined with the point cloud. We use an RGBD camera to synchronously collect frame-aligned RGB and depth images and generate point cloud data with colors according to the mapping relationship. Then, we use the YOLOv5 neural network to detect the collected RGB images and recognize the type of coupler rod in the image. Clear clutter in the point cloud and the bounding box is mapped to a spatial coordinate system for straight-through filtering of the point cloud. We use RANSAC for coarse registration and ICP for fine registration. The result of registration is carried out with the lower sampling point cloud model to achieve the registration of the coupler rod. Experiments show that this method can effectively segment the point cloud of the region of interest with high robustness. © 2022 IEEE.

关键词： Data fusion

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Fatigue Life Analysis of Piezoelectric Actuating Mechanism with Micro-displacement Amplifier 18

Fatigue Life Analysis of Piezoelectric Actuating Mechanism w...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zhang, Xinyuan Wang, Shaoping Wu, Xiao He, Siyuan Wang, Xingjian Niu, Yu Gavrilov, Alex I. Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Tianmushan Laboratory Xixi Octagon City Yuhang District Hangzhou310023 China Beihang University Ningbo Institute of Technology Ningbo315800 China Beihang University Research Institute of Aero-Engine Beijing100191 China Bauman Moscow State Technical University Department of Automatic Control Systems Moscow105005 Russia

ISBN: (纸本)9798350312201

Since piezoelectric actuating mechanism generally operate in high frequency response state, fatigue life has become an important factor influencing the performance and reliability of the entire drive mechanism. In order to investigate whether the designed piezoelectric ceramic actuator meets the active control requirements of the aero-engine, the paper analyzes the fatigue characteristics and fatigue life of the piezoelectric ceramic materials and the micro displacement amplification mechanism with finite element analysis software and the optimal spacing value is obtained by studying the effect of the flexible hinge spacing on the fatigue characteristics of the displacement amplifier. And then, the fatigue life of the displacement amplifier is analyzed based on the drive load spectrum of the aircraft during simulated flight, whose result is 340.93 hours. Finally, the fatigue life of the piezoelectric actuating mechanism is 32 minutes when loaded with full power, which meets the design target initially. © 2023 IEEE.

关键词： Piezoelectric actuators

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Time Synchronization in Industrial Internet of Things: A Survey

Time Synchronization in Industrial Internet of Things: A Sur...

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IEEE Information Technology, Networking, Electronic and automation control Conference

作者： Ke Zhou Xiaoming Wang Shijie Cui Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Nanning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning China

ISBN: (数字)9798350370805

ISBN: (纸本)9798350370812

Time synchronization is a fundamental strategy for many operations such as data synchronous collection, timely fault tracking, distributed control, and real-time communication in Industrial Internet of Things (IIoT). Over the years, a wide variety of protocols and technologies have been proposed for different application scenarios. The accuracy, security, robustness, low cost, and so on, are the main focus for the design of time synchronization protocol. However, so far, there is no relatively unified standard for time synchronization in IIoT. To clarify the development of time synchronization technology, this paper surveys the latest research for time synchronization in various types of networks including Precision Time Protocol and wireless sensor networks. The future development of time synchronization in IIoT is also investigated.

关键词： Surveys Wireless sensor networks Protocols Accuracy Reviews Robustness Synchronization Security Standards Industrial Internet of Things

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S2KAN-SLAM: Elastic Neural LiDAR SLAM with SDF Submaps and Kolmogorov-Arnold Networks

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IEEE Transactions on Circuits and systems for Video Technology 2025年

作者： Wang, Zhong Zhang, Lin Wang, Hesheng Shanghai Jiao Tong University State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China Tongji University School of Computer Science and Technology National Pilot Software Engineering School with Chinese Characteristics Shanghai201804 China

Traditional LiDAR SLAM approaches prioritize localization over mapping, yet high-precision dense maps are essential for numerous applications involving intelligent agents. Recent advancements have introduced methods leveraging neural fields to enhance mapping capabilities;however, these approaches still face several limitations. Firstly, concerning scene representation, they typically employ neural fields with high-dimensional features and multi-layer perceptron decoders utilizing non-continuous activation functions. This results in low learning efficiency and challenges in capturing high-frequency signals. Secondly, in terms of scene organization, these methods often treat the entire scene as a singular neural field, leading to inefficiencies, inflexibility, and difficulties in rectifying accumulated errors when mapping large-scale environments over extended periods. To tackle the first issue, we propose a lightweight continuous SDF regression approach by encoding the scene in single-valued embeddings and decoding SDF values from a Kolmogorov-Arnold Network. By minimizing discrepancies in measuring range, sampling distance, and decoded SDF values, we facilitate iterative frame-to-model tracking and bundle adjustment neural mapping. To mitigate the second challenge, we propose structuring the whole scene into multiple neural SDF submaps. By establishing node-node, node-submap, and loop closure constraints into a global pose graph, the system can create dense neural maps with global consistency across large-scale scenes. Experimental evaluations in both real-world and simulated settings indicate that our system achieves superior mapping completeness and accuracy, enhanced learning efficiency, reduced memory consumption, and greater flexibility compared to its counterparts. © 2025 IEEE.

关键词： Mapping

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Heuristic Algorithm for Solving Travelling Salesman Problem: Adding the Endpoints of the Longest Edges

Heuristic Algorithm for Solving Travelling Salesman Problem:...

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International Conference on Problems of Cybernetics and Informatics (PCI)

作者： Fidan Nuriyeva Department of Computer Science Dokuz Eylul University Izmir Turkey Laboratory of Recognition Identification and Methods of Optimal Solutions Institute of Control Systems Baku Azerbaijan

This study proposes, a new heuristic algorithm based on insertion heuristic to solve the symmetric Travelling Salesman Problem. In the proposed algorithm, firstly the two longest edges are selected and the starting tour passing through their endpoints is constructed, then the endpoints of the next longest edges are added to this tour and the solution passing through all the vertices is found. This problem is known to be NP-Hard. The proposed method was successfully tested on different-sized problems. The experimental results show that the proposed algorithm outperforms many existing methods.

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Management of Scientific Agricultural Digital Ecosystems Based on Ecosystem Classification

Management of Scientific Agricultural Digital Ecosystems Bas...

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International Conference on Management of Large-Scale System Development (MLSD)

作者： Vladimir Kulba Viktor Medennikov Laboratory of Modular Data Processing and Control Systems V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia Information and Computing Systems Department Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia

The paper considers a mathematical model for managing a scientific digital ecosystem exemplified by the agriculture case; the model enables assessing the impact science exerts on the regions’ socioeconomic position in order to build an adequate response to the advanced economies’ regime of severe sanctions against Russia. For these purposes, a systemic analysis of the subject identification and classification of ecosystems was conducted to address the critical issue of determining the basic concepts and terms of the country’s digitalization.

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Research on Predictive control Method of Permanent Magnet Synchronous Motor Based on Using Ultra-local Model

Research on Predictive Control Method of Permanent Magnet Sy...

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第43届中国控制会议

作者： Yiqiang Zhang Tao Zhang Yong Li Hualiang Zhang Guopeng Zhang Hao Wang School of Electrical Engineering Shenyang University of Technology Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The traditional finite set model predictive control has the advantages of fast response and strong robustness. The threevector model predictive current control(TV-MPCC) improves the problem of large current ripple based on single-vector model predictive current control(MPCC) and can realize deadbeat current control. Still, it cannot avoid the influence of parameter disturbance. To solve this problem, this paper constructs an ultra-local model based on the input and output information of the motor and designs an adaptive sliding mode observer to estimate the unknown part of the model. Finally, the designed threevector model-free predictive current control with adaptive sliding mode observer(TV-MFPCC-ASMO) is simulated and compared with the traditional three-vector model predictive control. It has been proved that the proposed method can effectively suppress the system disturbance when the motor parameters are mismatched and improve the motor's steady-state and dynamic performance during operation.

关键词： Permanent magnet synchronous motor Three-vector model predictive control Ultra-local model Adaptive sliding mode observer

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MvEchoSeg: One-shot In-context Learning for Multi-view Echocardiography Segmentation

MvEchoSeg: One-shot In-context Learning for Multi-view Echoc...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Guo, Yuting Duan, Ya Song, Wenfeng Li, Nannan Li, Aili Li, Shuai Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing100191 China University of Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Beijing Information Science and Technology University School of Computer Science Beijing100192 China Dalian Maritime University School of Information Science and Technology Dalian116000 China China-Japan Friendship Hospital Beijing100029 China

ISBN: (纸本)9798350386226

Echocardiography is the clinical standard for evaluation of cardiac morphology, and function, and providing hemodynamic parameters in patients with known or suspected heart disease. Due to the diversity and complexity of diagnostic tasks, comprehensive interpretation of echocardiography often requires multi-view imaging for integrated metric analysis. Deep learning methods have become the mainstream approach for echocardiography segmentation. However, achieving segmentation of multi-view echocardiography still requires a substantial amount of annotation. To remedy this, we propose a one-shot in-context learning network mvEchoSeg for multi-view echocardiography segmentation. This network requires only one annotated image for each view. Specifically, we propose a Task Prompt Identifier (TPI) module to identify the task type of the image and allocate the most precise task prompt for it, with minimal adaptation of CLIP and few-shot strategies. Additionally, we leverage a unified In-Context Model (ICM) capable of performing a diverse set of echocardiography segmentation tasks automatically. Using fine-tuning and low-rank adapters improved the performance of the pre-trained model, achieving significant results with minimal training cost. Furthermore, we collect a multi-view echocardiography dataset (MVECD) with 8 views to evaluate our method. The results show an improvement of more than 10% in the DICE score compared to the SOTA foundational medical image segmentation models. To our knowledge, this is the first exploration of a one-shot model for multi-view echocardiography segmentation. Our codes and models are available at https://***/stellating/mvEchoSeg. © 2024 IEEE.

关键词： Image segmentation

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Design and Implementation of High Precision Clock Synchronization System Based on RT1064

Design and Implementation of High Precision Clock Synchroniz...

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International Conference on Communications, Information System and computer Engineering (CISCE)

作者： Mingxu Gang Bingjun Yan Bo Hu Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

To realize the high-precision clock synchronization of various types of control equipment in the industrial process control network, a high-precision clock synchronizing system is designed and implemented. The system uses RT1064 microprocessor as the core, combined with ieee1588v2 high-accuracy clock synchronization protocol, and uses the MAC kernel integrated in rt1064 to support hardware timestamp function to achieve high-precision time synchronization between devices; Finally, the test verification platform is built to test and verify the accuracy. The test results show that the clock synchronization accuracy is within ± 400ns after the system runs stably, which meets the design requirements.

关键词： Accuracy Protocols Microprocessors Process control Media Access control Hardware Software

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Investigating the dynamic memory effect of human drivers via ON-LSTM

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Science China(Information Sciences) 2020年第9期63卷 83-93页

作者： Shengzhe DAI Zhiheng LI Li LI Dongpu CAO Xingyuan DAI Yilun LIN Department of Automation Tsinghua University Shenzhen International Graduate School Tsinghua University Department of Mechanical and Mechatronics Engineering University of Waterloo State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

It is a widely accepted view that considering the memory effects of historical information(driving operations) is beneficial for vehicle trajectory prediction models to improve prediction accuracy. However,many commonly used models(e.g., long short-term memory, LSTM) can only implicitly simulate memory effects, but lack effective mechanisms to capture memory effects from sequence data and estimate their effective time range(ETR). This shortage makes it hard to dynamically configure the most suitable length of used historical information according to the current driving behavior, which harms the good understanding of vehicle motion. To address this problem, we propose a modified trajectory prediction model based on ordered neuron LSTM(ON-LSTM). We demonstrate the feasibility of ETR estimation based on ON-LSTM and propose an ETR estimation method. We estimate the ETR of driving fluctuations and lane change operations on the NGSIM I-80 dataset. The experiment results prove that the proposed method can well capture the memory effects during trajectory prediction. Moreover, the estimated ETR values are in agreement with our intuitions.

关键词： driving behavior memory effect trajectory prediction historical information ON-LSTM

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