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Angle-Based SLAM on 5G mmWave Systems: Design, Implementation, and measurement

IEEE Internet of Things Journal 2023年第20期10卷 17755-17771页

作者： Yang, Jie Wen, Chao-Kai Xu, Jing Que, Hang Wei, Haikun Jin, Shi Southeast University Sch. of Automat. and the Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China National Sun Yat-sen University Institute of Communications Engineering Kaohsiung804 Taiwan Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Nanjing210096 China

Simultaneous localization and mapping (SLAM) is a key technology that provides user equipment (UE) tracking and environment mapping services, enabling the deep integration of sensing and communication. The millimeter-wave (mmWave) communication, with its larger bandwidths and antenna arrays, inherently facilitates more accurate delay and angle measurements than sub-6 GHz communication, thereby providing opportunities for SLAM. However, none of the existing works have realized the SLAM function under the 5G new radio (NR) standard due to specification and hardware constraints. In this study, we investigate how 5G mmWave communication systems can achieve situational awareness without changing the transceiver architecture and 5G NR standard. We implement 28-GHz mmWave transceivers that deploy OFDM-based 5G NR waveform with 160-MHz channel bandwidth, and we realize beam management following the 5G NR. Furthermore, we develop an efficient successive cancellation-based angle extraction approach to obtain angles of arrival and departure from the reference signal received power measurements. On the basis of angle measurements, we propose an angle-only SLAM algorithm to track UE and map features in the radio environment. Thorough experiments and ray tracing-based computer simulations verify that the proposed angle-based SLAM can achieve submeter-level localization and mapping accuracy with a single base station and without the requirement of strict time synchronization. Our experiments also reveal many propagation properties critical to the success of SLAM in 5G mmWave communication systems. © 2014 IEEE.

关键词： 5G mobile communication systems

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Adaptive Differentially Private Robust Federated Learning Against Backdoor Attacks 1

Adaptive Differentially Private Robust Federated Learning Ag...

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1st International Conference on Intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Yao, Ruixiang Wen, Hong Hou, Wenjing Ma, Wendi Sun, Fan Zhao, Ziang School of Aeronautics and Astronautics University of Elec.Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781643685779

In federated learning systems, malicious attackers can manipulate training datasets by injecting backdoor triggers to achieve data poisoning. Addressing this vulnerability, this paper proposes a new defense method, the adaptive differential privacy stochastic gradient descent (ADP-SGD) algorithm, which increases the Euclidean distance between malicious and benign updates to enhance aggregation efficiency. Experiments were conducted on typical datasets, and the results show that combining ADP-SGD with the m-Krum aggregation algorithm can effectively defend against backdoor attacks in complex attack environments. While ensuring the accuracy of the main task, it significantly reduces the success rate of backdoor attacks, especially under the condition of unknown proportions of malicious participants, proving to be effective and robust. © 2025 The Authors.

关键词： Federated learning

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SBRDF Hyperspectral Ray Tracing Rendering for 3D Representation Based on Target Surface Material 8th

SBRDF Hyperspectral Ray Tracing Rendering for 3D Representat...

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8th International Symposium of Space Optical Instruments and Applications, ISSOIA 2023

作者： Yi, Jia Jiang, Huilin Wang, Xiaoyong Ying, Du Graduate School Changchun University of Science and Technology Changchun130022 China School of Physics Changchun University of Science and Technology Changchun130022 China Beijing Institute of Space Mechanics and Electricity Beijing100190 China National and Local Joint Engineering Research Center of Space Optoelectronics Technology Changchun University of Science and Technology Changchun130022 China Fundammontal Science On Space-Ground Laser CommunicationTechnology Laboratory Changchun University of Science and Technology Changchun130022 China Key Laboratory of Education Ministry Optoelectronics Measurement and Control and Optical Shapingba China

ISBN: (纸本)9789819767175

Spectral technology is one of the key means for long-distance non-contact detection and identification of materials. It is an important force for ground-based detection satellites which can play a role in monitoring satellite operation status and safety, and identifying satellite types except for radar. However, for complex targets detected at ultra long distances, the detection object is equivalent to a point source, and the distribution of surface materials is not clear. Usually, material spectral unmixing can only focus on the distribution of planar materials, making it difficult to analyze the target structure. This article uses the spectral BRDF function to construct a hyperspectral ray tracing rendering 3D representation method based on the relationship between illumination, target surface normals, and detection points. It obtains a 3D rendering of a single material on a composite target, laying the foundation for analyzing the structural features of long-distance point target detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Rendering (computer graphics)

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Study of aircraft skin defect detection and characterization methods

Study of aircraft skin defect detection and characterization...

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International Conference on Information, communication and Networks (ICICN)

作者： Xinfeng Wang Qing Liu Kun Jia Yan Zhang Haiyin Zhang Jia Zhen Kaida Shang School of Automation and Information Engineering Xi’an University of Technology Xi’an China Xi’an Aerocomm Measurement and Control Technology Co. Ltd Xi’an China

With the development of modern vehicle functions and technologies, surface geometry defects such as dents and cracks generated during the assembly and service of a vehicle not only endanger flight safety and reduce load capacity but also limit its functional characteristics. Accurate detection of surface geometry defects is critical, and these defects must be controlled within a small margin of error. However, conventional methods have difficulty meeting practical requirements in terms of detection accuracy and measurement size. In this paper, based on the analysis of the structural characteristics of the aircraft surface, an aircraft skin defect detection and characterization method is proposed, which processes the defect point cloud data, combines the segmentation algorithm of area growth to detect defects, and analyzes the geometric analysis and characterization through the depth of defects to achieve the accurate measurement of defects, and the experimental results show that the measurement of round holes with different depths of standard parts, the measurement results and the true value of The error are less than 0.05mm; the measurement of the outer surface of the aircraft engine compartment can detect different types of defects such as scratches or dents, and the method in this paper can be extended to the defect detection field of other large industrial equipment

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Cooperative control for Low-Voltage Ride-Through Based Improved Active Crowbar of Dfigm

SSRN

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SSRN 2024年

作者： Zhang, Yu Li, Kai Gao, Hanying Kang, Shouqiang Sun, Yutian Wang, Peng College of Electrical and Electronic Engineering Harbin University of Science and Technology Harbin China College of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin China Harbin Large Motor Research Institute Harbin China College of Electrical and Electronic Engineering Nanyang Technological University Singapore

To solve the low voltage fault problem of doubly-fed induction generator-motor (DFIGM), this paper proposes a cooperative control strategy based on improved current tracking control (ICTC) and improved active crowbar topology. The strategy adopts ICTC in the case of slight dip fault. Under the constraints of rotor voltage and current, the tracking coefficient is optimized by particle swarm optimization (PSO) algorithm. The improved active crowbar is operated when severe dip fault occurs, which decreases the negative sequence component, reduces the total harmonic distortion (THD) of the point of common coupling (PCC) current. Taking a 10 MW DFIGM as a model, the magnetic flux variation characteristics are analyzed, and the cooperative control method in this paper is compared with the inductance emulating control (IEC) and the traditional crowbar in the case of symmetrical voltage dip fault and interphase voltage dip fault. The simulation experimental results verify the effectiveness and applicability of the proposed method. © 2024, The Authors. All rights reserved.

关键词： Asynchronous generators

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AI-aided power electronic converters automatic online real-time efficiency optimization method

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Fundamental Research 2023年第3期5卷 1111-1116页

作者： Tang, Yuanhong Cao, Di Xiao, Jian Jiang, Chenying Huang, Qi Li, Yunwei Chen, Zhe Blaabjerg, Frede Hu, Weihao Power System Wide-area Measurement and Control Sichuan Provincial Key Laboratory School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu 611731 China MORNSUN Guangzhou Science & Technology Co. Ltd. Guangzhou 510663 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu 611731 China Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China Quzhou 324000 China Department of Chengdu State Grid Corporation of China Chengdu 610599 China Southwest University of Science and Technology Mianyang 621010 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2V4 Canada Department of Energy Technology Aalborg University Aalborg 9220 Denmark

Energy losses during the conversion and supply of electric power are considered a significant issue and cannot be estimated. Improvement in the efficiency of energy conversion systems is highly restricted because of their internal nonlinearity and complexity. Thus, inspired by the successful utilization of robotic chemists, we demonstrate a pioneering concept of artificial intelligence (AI)-aided automatic online real-time optimization of a power electronics converter using a dual active bridge (DAB) converter as an example. An optimal modulation strategy was obtained through repeated automatic exploration experiments on a practical DAB converter platform. Specifically, the DAB experimental platform operated autonomously around the clock for approximately 71 h. It performed 120,000 consecutive experiments (12,000 episodes) within a six-variable experimental space driven by a deep deterministic policy gradient (DDPG) algorithm. The proposed AI-aided automatic online real-time optimization method achieved significantly improved efficiency of power conversion and supply. Consequently, zero carbon emissions may be obtained in the future. © 2023

关键词： Artificial intelligence Automatic online real-time exploration DC-DC converter Dual active bridge converter Energy conversion system Power electronics

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Temperature Response Analysis of Intelligent OPPC Cable Core Based on Finite Element Simulation

Temperature Response Analysis of Intelligent OPPC Cable Core...

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International Conference on Optical communications and Networks (ICOCN)

作者： Wenping Xie Ming Nie Yongchun Liang Xiaoyu Luo Yu Han Hongwei Li Xiaohui Tang Electric Power Research Institute of Guangdong Power Grid Co. Ltd. Guangzhou China Harbin University of Science and Technology Harbin China Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication Engineering Harbin China

ISBN: (数字)9798350367652

ISBN: (纸本)9798350367669

The Optical Fiber Composite Overhead Conductor (OPPC) cable is a special type of power optical cable that combines overhead conductor and communication capabilities. It has advantages such as strong wind resistance, good corrosion resistance, high bandwidth transmission, low loss transmission, and high reliability. However, as the OPPC cable operates for a long time power transmission, its long-term working temperature has a significant impact on transmission performance and lifespan. Therefore, monitoring the temperature of the OPPC cable and internal fibers can improve the transmission capacity of the line, ensure good thermal stability, and provide important references for fault warning and maintenance. This study aims to explore the temperature characteristics of the OPPC cable through actual monitoring and analysis, providing guidance and decision-making basis for practical applications.

关键词： Temperature sensors Temperature measurement Resistance Optical fibers Temperature Optical fiber cables communication cables

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Survey on Foundation Models for Prognostics and Health Management in Industrial Cyber-Physical Systems

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2024年 2卷 264-280页

作者： Liu, Ruonan Zhang, Quanhu Han, Te Yang, Boyuan Zhang, Weidong Yin, Shen Zhou, Donghua Shanghai Jiao Tong University Department of Automation Shanghai200240 China Tianjin University College of Intelligence and Computing Tianjin300350 China Beijing Institute of Technology Center for Energy and Environmental Policy Research Beijing100081 China Beijing Institute of Technology School of Management Beijing100081 China Beijing Laboratory for System Engineering of Carbon Neutrality Beijing100081 China Nanjing University Center for Advanced Control and Smart Operations Suzhou215163 China Hainan University School of Information and Communication Engineering Haikou570228 China Shanghai Jiaotong University Department of Automation Shanghai200240 China Norwegian University of Science and Technology Trondheim7491 Norway

Industrial Cyber-Physical Systems (ICPS) integrating disciplines such as computer science, communication technology, and engineering, have become a crucial component of modern manufacturing and industry. However, ICPS faces numerous challenges during long-term operation, including equipment faults, performance degradation, and security threats, etc. To achieve efficient maintenance and management, prognostics and health management (PHM) has been widely applied in the critical tasks of ICPS such as fault prediction, health monitoring, and maintenance decision-making. The emergence of large-scale foundation models (LFMs) like BERT and GPT marks a significant advancement in artificial intelligence (AI) technology, demonstrating substantial application potential in multiple fields. The accumulation of AI technology, rapid development of LFMs, and the abundance of industrial data and industrial process knowledge provide the foundational conditions for the construction and advancement of industrial LFMs. However, there is currently a lack of consensus on applying LFMs of PHM in ICPS, necessitating a systematic review and roadmap to clarify future development directions. To bridge this gap, this survey provides a comprehensive survey and understanding of the recent advances in LFMs of PHM in ICPS. It provides valuable references for decision makers and researchers in the industry, and helps to further improve the reliability, availability and safety of ICPS. © 2023 IEEE.

关键词： Cyber Physical System

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Research on Resonance Suppression Method of Multi-Inverter Parallel System Based on Improved Fcs-Mpc

SSRN

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SSRN 2024年

作者： Chunhui, Liang Li, Jinfa Zuo, Xiaoyang Huang, Chenglong Liu, Renjie School of Electrical and Information Engineering Changchun Institute of Technology Changchun130025 China National local joint Engineering Research Center for Measurement and Control and Safe Operation Technology of Intelligent Distribution Network Changchun130103 China

A mathematical model of the multi-NPC three-level LCL inverter system is constructed with the goals of suppressing the resonance of the multi-inverter grid-connected system, improving the output power quality, and improving the pure output current waveform on the grid side of the system. Firstly, The system's resonance characteristics are studied by the equivalent NORTON model of multiple inverters in parallel. Secondly, because of the resonance existing in the multi-inverter parallel system, by integrating active damping and improving the Finite control Set Model Predictive control (FCS-MPC) method, realize the harmonic design in both the low- and high-frequency domains. It can successfully reduce the resonance phenomenon and raise the system's general stability. Meanwhile, It is possible to greatly lower the harmonic distortion rate and enhance the output current waveform. Finally, two parallel NPC three-point flat LCL filters inverters were built for simulation analysis, and the suggested analysis method's viability and accuracy were confirmed. © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Self-supervised Visual Odometry Based on Geometric Consistency

Self-supervised Visual Odometry Based on Geometric Consisten...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Rujun Song Jiaqi Liu Kaisheng Liao Zhuoling Xiao Bo Yan School of Information and Communication Engineering University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory Chengdu China

Learning-based monocular visual odometry (VO) has lately drawn significant attention for its robustness to camera parameters and environmental variations. Unlike most self-supervised learning-based methods, our approach simultaneously focuses on the adjacent and interval co-visibility correspondence to improve the pose estimation. To handle different pixel displacements, we apply the Multi-scale Feature Fusion component for the full exploration of latent motion features. Besides, the Interval Feature Guided Refinement component is incorporated to adaptively exploit the continuity of camera motions and steer the network for retaining pose consistency in the time domain. Extensive experiments on the KITTI and Malaga datasets have demonstrated the promising performance of our approaches. The proposed method produces competitive results against classic algorithms and outperform state-of-the-art methods by up to 23.9 % and 15.4 % on average translational and rotational evaluation.

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