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Brillouin optical correlation domain analysis based on a phase-chaos laser

advanced Photonics Nexus 2024年第6期3卷 106-116页

作者： Lintao Niu Yahui Wang Jing Chen Haochen Huang Lijun Qiao Mingjiang Zhang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control SystemMinistry of EducationTaiyuanChina Taiyuan University of Technology College of Physics and OptoelectronicsTaiyuanChina Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering TaiyuanChina

The physical mechanism of gain motivation is the main theoretical bottleneck that restricts the signal-to-noise ratio(SNR)and results in a mono-merit implementation for the existing stimulated Brillouin scattering-based fiber sensors.A phase-chaos laser(PCL)is proposed and introduced in the Brillouin optical correlation domain analysis(BOCDA)scheme to promote the SNR and achieve a high-accuracy *** PCL characteristics are presented,and a theoretical model of chaos gain accumulation and extraction is ***,the simulation results reveal that the SNR is improved by 5.56 dB,and the signal-to-background noise ratio(SBR)of the Brillouin gain spectrum(BGS)is promoted by 8.28 dB with a 100-km sensing ***,the PCL is experimentally *** the proof-of-concept experiment,the accuracy of the Brillouin frequency shift is upgraded to 0.64 MHz,and the SBR of BGS is improved by 10.77 *** PCL provides a new research direction for optical chaos,and the PCL-BOCDA showcases a promising future for optimal-merit-coupling sensing and its application.

关键词： phase-chaos laser distributed fiber sensing stimulated Brillouin scattering high signal-to-noise ratio

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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Electromagnetic-acoustic Beam Compressor by Double-physical-fields Null Medium

Electromagnetic-acoustic Beam Compressor by Double-physical-...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Ran Sun Fei Sun Yichao Liu Zeyu Zhang Chao Yang Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

In this study, double-physical-fields null medium, i.e., a subwavelength air channels surrounded by a carefully arranged metal plates, is utilized to design an electromagnetic-acoustic beam compressor capable of simultaneously compressing electromagnetic waves and acoustic waves. Numerical simulation results verify its ability to simultaneously produce the expected compression ratios for both electromagnetic waves and acoustic waves. Moreover, the compression ratio precisely matches the geometric size ratio of the input and output planes of the compressor. This work may have potential applications in electromagnetic-acoustic coupling systems and electromagnetic-acoustic processing/detection.

关键词： Couplings Electric potential Electromagnetic scattering Metals Numerical simulation Acoustic beams Electromagnetics

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LI-DPS: A Long Sequence Dual Prediction Scheme Based on Informer for Efficient High-Frequency Data Transmission 50

LI-DPS: A Long Sequence Dual Prediction Scheme Based on Info...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Wu, Yu Yang, Bo Zhu, Dafeng Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665464543

High-frequency time-series data such as vibration signals will consume a lot of communication resources and require very high network bandwidth. Reducing the amount of data transmission while ensuring its availability is particularly important and challenging in high-frequency scenarios. Dual prediction scheme (DPS) can significantly reduce the amount of data transmission while ensuring data accuracy. However, traditional DPS cannot be applied to high-frequency scenarios due to the limitation of the mechanism design and model inference speed. We propose a novel long sequence DPS to efficiently reduce the volume of high-frequency data transmission in real time. To overcome the accuracy degradation due to gradient vanishing in long sequence prediction, we also propose an attention-based prediction model. Furthermore, we propose Informer to reduce the model’s computational complexity and enable fast inference and deployment on resource-constrained edge gateways. Experiments based on the real-world dataset show that the proposed scheme can efficiently cope with high-frequency data, reduce its transmission volume, and ensure data accuracy. © 2024 IEEE.

关键词： Prediction models

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A Dual-function Quasi-static Magnetic Device with Cloaking and Concentrating Functions Simultaneously

A Dual-function Quasi-static Magnetic Device with Cloaking a...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Hanchuan Chen Yichao Liu Fei Sun Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

In previous study, many single-function static/quasi-static magnetic devices, such as cloak and concentrator, have been designed base on transformation optics. However, few have explored devices capable of simultaneously generating two different functions on the static/quasi-static magnetic field. In this study, we propose a dual-function quasi-static magnetic device, which can create a concealed region and concentrated region for quasi-static magnetic field simultaneously. The dual-function quasi-static magnetic device is designed via twice extreme spatial stretching transformation and magnetic null medium, which can be realized by using arrays of superconductors and ferromagnetic materials in specific arrangement. The simulated results verify the performance of the proposed dual-function quasi-static magnetic device, which can simultaneously achieve cloaking and concentrating effect for the magnetic field from DC to 1000 Hz. The quasi-static magnetic field can be enhanced 9 times than the background magnetic field when the side lengths of the internal square pillar and external square pillar of the proposed structure are selected as a = 10 mm and b = 90 mm, respectively. Moreover, the concentrating ratio obtained from theoretical calculation fits well with the results obtained through numerical simulation. The dual-function quasi-static magnetic device designed in this study may have essential application in medical testing for special occasions.

关键词： Performance evaluation Magnetic devices Superconducting magnets Ferromagnetic materials Optics Numerical simulation Magnetic fields

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Defect Analysis of Power Equipment Based on Information Extraction Model 6

Defect Analysis of Power Equipment Based on Information Extr...

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2021 6th International Conference on Information Science, Computer Technology and Transportation, ISCTT 2021

作者： Mu, Jinshuang Gao, Zhanjun Zhou, Fengyuan Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Shandong Jinan250061 China

ISBN: (纸本)9783800757282

In operation and maintenance, State Grid has accumulated a large amount of historical equipment defect text data. For problems such as difficulty in text data mining. This paper established a text information extraction model at first. Extract important information such as equipment defect phenomena and defect locations from historical defect data. Based on it, establishing convolutional neural network (CNN) to achieve defect level classification. By comparing classification effect before and after information extraction, results indicate that text information extraction model can improve accuracy of defect level classification model. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Data mining

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Wind and PV Power Ramp Events Prediction Based on Long Short-Term Memory Network

Wind and PV Power Ramp Events Prediction Based on Long Short...

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2023 IEEE Sustainable Power and Energy Conference, iSPEC 2023

作者： Wang, Zengwei Li, Zhendong Liu, Yutian Ma, Huan The Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China The State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350322699

With the increasing penetration rate of renewable generation, the challenges arising from its randomness and intermittent nature are becoming more pronounced. In particular, wind and photovoltaic power ramp events pose a serious threat to the secure and stable operation of power systems, and even lead to frequency instability and load shedding. Based on the long short-term memory neural networks (LSTM), this paper proposes a novel renewable power ramp events (RPREs) forecasting approach. First, filter the key tie-lines. Second, the LSTM network was driven by the known time series of wind, PV, load, and tie-line power to forecast the tie-line power for the next hour, thereby determining the adjustable capacity of the tie-line. Finally, the regulatory capability of the grid is considered to judge the occurrence of a power ramping event. Case study demonstrates that the proposed method can effectively predict power ramping events and meets the requirements of online assessment. © 2023 IEEE.

关键词： LSTM photovoltaic power ramping events forecasting wind power

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Distributed Neighbor Selection on Matrix-weighted Networks 38

Distributed Neighbor Selection on Matrix-weighted Networks

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Wei, Haoyu Pan, Lulu Shao, Haibin Li, Dewei 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 Department of Automation Shanghai200240 China

ISBN: (纸本)9798350303636

This paper explores distributed neighbor selection in matrix-weighted networks, where a matrix-valued weight captures the interdependencies among agents' states. We demonstrate the feasibility of preserving and, in certain cases, improving the convergence rate of matrix-weighted networks by having agents exclusively engage with a subset of their neighbors. Leveraging the inherent monotonicity of Laplacian matrix eigenvectors, we introduce a novel neighbor selection criterion that reduces network connections while enhancing convergence rates. Existing neighbor selection strategies often require acquiring information from all nodes before making decisions. In order to propose a distributed neighbor selection strategy for matrix-weighted networks, we establish a numerical relationship between Laplacian eigenvectors and a locally measurable metric. In essence, this paper extends prior findings from scalar-weighted networks to matrix-weighted networks. © 2023 IEEE.

关键词： convergence rate Distributed neighbor selection Laplacian matrix matrix-weighted networks

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Design of a Novel Autonomous Docking system With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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SSD object detection algorithm based on knowledge map

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International Journal of Wireless and Mobile Computing 2024年第2期27卷 152-160页

作者： Huang, Li Wang, Xiaofeng Lu, Jianhua Hu, Wei Zhang, Changrong College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China Key Laboratory of Metallurgical Equipment and Control Technology of the Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China

With the pervasive integration of artificial intelligence into all aspects of human life, talent emerges as a primary resource. Upon analysing the current state of talent training in higher education institutions, issues such as dispersed knowledge points, overlapping content, a singular practice approach and ineffective evaluation have been identified. In response to these challenges, this paper proposes a multidisciplinary and comprehensive practical teaching methodology grounded in the knowledge graph framework. It delves into diverse paths for practical teaching and assessment, including aspects like teaching objectives, problem decomposition, resource integration, implementation methods and performance evaluation. The practical application of the SSD algorithm in researching service robot indoor object detection serves as an illustrative example. Employing the holistic practical teaching approach facilitated by the knowledge graph, this model guides students in acquiring object detection expertise, thereby enhancing their comprehensive development. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Object detection

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