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arXiv 2021年

作者： Wang, Guangming Hu, Yunzhe Wu, Xinrui Wang, Hesheng Department of Automation Key Laboratory of System Control Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

Scene flow estimation is the task to predict the point-wise or pixel-wise 3D displacement vector between two consecutive frames of point clouds or images, which has important application in fields such as service robots and autonomous driving. Although many previous works have explored greatly on scene flow estimation based on point clouds, there are two problems that have not been noticed or well solved before: 1) Points of adjacent frames in repetitive patterns may be wrongly associated due to similar spatial structure in their neighbourhoods;2) Scene flow between adjacent frames of point clouds with long-distance movement may be inaccurately estimated. To solve the first problem, a novel context-aware set convolution layer is proposed in this paper to exploit contextual structure information of Euclidean space and learn soft aggregation weights for local point features. This design is inspired by human perception of contextual structure information during scene understanding with repetitive patterns. The context-aware set convolution layer is incorporated in a context-aware point feature pyramid module of 3D point clouds for scene flow estimation. For the second problem, an explicit residual flow learning structure is proposed in the residual flow refinement layer to cope with long-distance movement. The experiments and ablation study on FlyingThings3D and KITTI scene flow datasets demonstrate the effectiveness of each proposed component. The qualitative results show that the problems of ambiguous inter-frame association and long-distance movement estimation are well handled. Quantitative results on both FlyingThings3D and KITTI scene flow datasets show that the proposed method achieves state-of-the-art performance, surpassing all other previous works to the best of our knowledge by at least 25%. Copyright © 2021, The Authors. All rights reserved.

关键词： Feature extraction

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Relay Satellite Assisted LEO Constellation NOMA Communication system

arXiv

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arXiv 2024年

作者： Zhang, Xuyang Yue, Xinwei Han, Zhihao Li, Tian Shen, Xia Wang, Yafei Liu, Rongke Key Laboratory of Information and Communication Systems Ministry of Information Industry China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang Hebei050081 China Beijing100191 China School of Electronic and Information Engineering Beihang University Beijing100191 China Shenzhen Beihang Emerging Industry Technology Research Institute Shenzhen518063 China

This paper proposes a relay satellite assisted low earth orbit (LEO) constellation non-orthogonal multiple access combined beamforming (R-NOMA-BF) communication system, where multiple antenna LEO satellites deliver information to ground non-orthogonal users. To measure the service quality, we formulate a resource allocation problem to minimize the second-order difference between the achievable capacity and user request traffic. Based on the above problem, joint optimization for LEO satellite-cell assignment factor, NOMA power and BF vector is taken into account. The optimization variables are analyzed with respect to feasibility and non-convexity. Additionally, we provide a pair of effective algorithms, i.e., doppler shift LEO satellite-cell assisted monotonic programming of NOMA with BF vector (D-mNOMA-BF) and ant colony pathfinding based NOMA exponential cone programming with BF vector (A-eNOMA-BF). Two compromise algorithms regarding the above are also presented. Numerical results show that: 1) D-mNOMA-BF and A-eNOMA-BF algorithms are superior to that of orthogonal multiple access based BF (OMA-BF) and polarization multiplexing schemes;2) With the increasing number of antennas and single satellite power, R-NOMA-BF system is able to expand users satisfaction;and 3) By comparing various imperfect successive interference cancellation, the performance of A-mNOMA-BF algorithm exceeds D-mNOMA-BF. Copyright © 2024, The Authors. All rights reserved.

关键词： Satellite communication systems

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Wind Speed Data Repairing Method Based on Bidirectional Prediction

Wind Speed Data Repairing Method Based on Bidirectional Pred...

引用

Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Xincheng Shen Yi Qu Shaoxiong Huang Zhi Li Kaifeng Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China State Grid Anhui Electric Power Co. Ltd Hefei China

ISBN: (数字)9781728190044

ISBN: (纸本)9781728190051

In order to repair the lost data in distributed wind power system, this paper puts forward a wind speed data repairing model based on a new bidirectional prediction method. This model consists of two one-way prediction models. In each prediction model, the original wind speed data are decomposed into several intrinsic mode functions (IMFs) and a residue signal by ensemble empirical mode decomposition (EEMD) method. Then the Savitzky-Golay (SG) filter is used to reduce noise for high-frequency IMFs. Next the long short-term memory (LSTM) model and autoregressive integrated moving average (ARIMA) model are combined to predict low-frequency IMFs and the noise reduction results respectively. At the end, all those forecast results are added and form a one-way result. By weighted average of two one -way results, the repairing result is calculated. The experimental results from multiple prediction cases show that this method can get more accurate results.

关键词： Wind speed Distributed databases Predictive models Maintenance engineering Wind power generation Data models Wind forecasting

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Optimal Resource Allocation for UAV-Relay-Assisted Mobile Crowdsensing

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IEEE Transactions on Communications 2024年

作者： Yang, Xiaolong Fu, Yaru Zheng, Jianchao Xu, Zhan Shao, Ruihao Wu, Yuan Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100101 China Beijing Information Science and Technology University School of Information and Communication Engineering Beijing100101 China Hong Kong Metropolitan University School of Science and Technology Hong Kong999077 Hong Kong Academy of Military Science Beijing100091 China University of Macau State Key Laboratory of Internet of Things for Smart City The Department of Computer and Information Science Macau China

In this paper, we exploit an emergency mobile crowdsensing (MCS) framework that utilizes unmanned aerial vehicles (UAVs) in collaboration with uncrashed base stations (BSs) to enhance sensing and communication efficiency. In the proposed framework, mobile users (MUs) equipped with sensors collect data, while UAVs, deployed as aerial relays, collaborate with uncrushed BSs to facilitate the transmission and aggregation of the sensed data from all MUs. However, the limited resources significantly affect the deployment of UAVs and the design of the UAV-relay-assisted MCS system. Moreover, selecting MUs for sensing tasks and allocating bandwidth among them are crucial factors that determine MUs' sensing capabilities and the data transmitting policies. Incorporating with foregoing essential factors, we formulate a comprehensive problem that jointly optimizes the MU selection, bandwidth allocation, UAV deployment, as well as strategies for sensing and transmitting data, aiming to improve the total reward of agent. The formulated problem poses high challenges due to the coupling between the sensing, transmission, as well as the UAVs deployment policies. To deal with this problem, we first derive the optimal transmission power and sensing data size under given MU selection, bandwidth allocation, and UAVs deployment strategy. The original optimization problem is subsequently decomposed into three folds, corresponding to finding the optimal MU selection, bandwidth allocation solution, as well as the deployment of UAVs. Meanwhile, a joint dynamic programming and a swap-then-compare enabled algorithm is proposed to obtain the optimal MU selection and bandwidth allocation policies. Next, the successive convex approximation (SCA) techniques are used to find the optimal locations for the UAVs. Extensive numerical results verify that the proposed joint algorithm can significantly outperform several benchmark approaches. © 1972-2012 IEEE.

关键词： Bandwidth

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The DRTS-Net Framework: Enhanced Probabilistic Health Perception for Wind Turbine Bearings Under complex Operating Conditions With Improved Interpretability

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IEEE Transactions on Instrumentation and measurement 2025年 74卷

作者： Yang, Tongguang Li, Guanchen Huo, Jinzhao Li, Xiaoyong Zhou, Xianwen Han, Qingkai Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China Johns Hopkins University Department of Mechanical Engineering BaltimoreMD21218 United States Foshan University School of Mechatronic Engineering and Automation Foshan528225 China SCNU Environmental Research Institute Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety MOE Key Laboratory of Theoretical Chemistry of Environment South China Normal University School of Environment Guangzhou510006 China SCNU Qingyuan Institute of Science and Technology Innovation Company Ltd. Qingyuan511517 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Shenyang110819 China

Health perception in mechanical systems is a crucial aspect of prognostics and health management (PHM). Deep learning models have been successfully applied to health perception in wind turbine bearings. However, due to the time-varying, redundant, and noisy characteristics of time-series data representing bearing wear, existing models face significant challenges, particularly in terms of generalization and interpretability. Moreover, although most current models have provided health perceptions, they overlook the strong stochastic nature of bearing degradation data, and thus fail to deliver reliable predictions of uncertainty information. To address these technical challenges, this study introduces a novel Deep residual temporal-spatial framework (DRTS-Net) for probabilistic health perception of wind turbine bearing wear states. This article creatively designs spatiotemporal information fusion module for extracting features from bearing degradation data. Inspired by improvements in residual network structures, the DRTS-Net integrates an attention mechanism and a soft thresholding mechanism from the deep residual shrinkage network to optimize the feature extraction process. This integration aims to mitigate the interference from minor redundant features in the degradation data. The framework incorporates Gaussian process regression in the output layer to yield the probability distribution of single-health perception values for bearing features. A comparative study was conducted using the same bearing health state dataset against current mainstream deep learning methods for bearing health assessment. Results demonstrate that the proposed DRTS-Net achieves superior performance in high-precision health perception, high-reliability probabilistic health perception. © 1963-2012 IEEE.

关键词： Stochastic systems

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Knowledge-Based Scene Text Recognition for Industrial Applications

Knowledge-Based Scene Text Recognition for Industrial Applic...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Guowei Deng Jingzheng Tu Cailian Chen Jianping He Xinyi Le Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai China

ISBN: (纸本)9781728119496

Scene text recognition (STR) methods combined with semantic information have made great progress to recognize texts in natural scenes, most of which are daily words. However, research on mining semantic information in industrial texts attracts less attention. Since industrial texts follow a different semantic pattern defined by industry standards, it challenges many existing methods to conduct accurate semantic reasoning. In this paper, we abstract the industry standards into two aspects of prior knowledge: the grouping property and the prior lexicon. Correspondingly, a knowledge-based language model is proposed with several group-wise correlation modules and a lexicon-based reasoning module to learn semantic rules from both data and the prior knowledge. Besides, we transfer the prior knowledge into data by generating synthetic pure text datasets according to the industry standards’ rules, which introduces more prior knowledge to the language model. Furthermore, a novel STR framework is presented by combining the knowledge-based language model and an attention-based vision model. For evaluation, two industrial text datasets called CIN and SB are collected from real-world industrial field surveillance. Experiments indicate that our method’s word-level accuracy outperforms state-of-the-art methods with 15% and 10.61% on CIN and SB datasets respectively.

关键词： Industries Correlation Text recognition Surveillance Semantics Knowledge based systems Data models

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QMIX Algorithm for Coordinated Welding of Multiple Robots

QMIX Algorithm for Coordinated Welding of Multiple Robots

引用

作者： Liangchuang Liao Yang-Yang Chen School of Electronic Science & Engineering Southeast University Robot Department Jiangsu Automation Research Institute School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

This paper considers the coordinated welding control based on deep multi-agent reinforcement *** discrete-time states and actions with local observation for the welding robots and the characteristics of the weld lines(e.g.,the starting points of the weld lines and the ending points of the weld lines) are defined,which is suitable to use the monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX) algorithm.A novel reward composed of trajectory optimization,collision avoidance and the task done is designed,which is proved by the simulation in the grid-world environment.

关键词： Deep multi-agent reinforcement learning Welding robots QMIX

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Damping Torque Analysis of the PLL Low-Frequency Components for Grid Following VSG

Damping Torque Analysis of the PLL Low-Frequency Components ...

引用

2022 International Conference on Cyber-Physical Social Intelligence, ICCSI 2022

作者： Zhou, Yichen Li, Sha Sun, Jiahui Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Electrical and Electronic Engineering North China Electric Power University Jilin China Guangdong Power Grid Corporation Dongguan Power Supply Bureau China Southern Power Grid Guangdong Dongguan China North China Electric Power University Electrical and Electronic Engineering Hebei Baoding China

ISBN: (数字)9781665498357

ISBN: (纸本)9781665498357

Phase-locked loop (PLL) is the key tool for the grid-connected inverter to track the frequency and phase of the grid voltage when synchronizing with the power grid. Therefore, the stability of PLL is particularly important. This paper proposes a damping torque analysis method to study the stability of the low-frequency component of PLL for the grid following a virtual synchronous generator (VSG). Firstly, the small signal model is established for the grid following VSG with a dual-loop structure. Secondly, the damping torque analysis method is provided especially for the stability analysis of PLL low-frequency components. And the corresponding stability criterion is constructed. Finally, significant factors that affect the stability of PLL low-frequency components are studied by the test system and the corresponding mechanism is revealed, including the influence of line reactance, PLL control parameters, and virtual damping. Results show that the stability of PLL is greatly dominated by the low-frequency component, whose stability can be improved by adopting a smaller integral coefficient of PLL, smaller virtual inertia, and larger virtual damping D. © 2022 IEEE.

关键词： Stability criteria

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A Unified NOMA Framework in Beam-Hopping Satellite Communication systems

arXiv

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arXiv 2024年

作者： Zhang, Xuyang Yue, Xinwei Li, Tian Han, Zhihao Wang, Yafei Ding, Yong Liu, Rongke The Key Laboratory of Information and Communication Systems Ministry of Information Industry The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The 54th Research Institute of China Electronics Technology Group Corporation Hebei Shijiazhuang050081 China The School of Electronic and Information Engineering Beihang University Beijing100191 China Shenzhen Institution of Beihang University Shenzhen518063 China The Baicells Technologies Co. Ltd Beijing100095 China

This paper investigates the application of a unified non-orthogonal multiple access framework in beam hopping (U-NOMA-BH) based satellite communication systems. More specifically, the proposed U-NOMA-BH framework can be applied to code-domain NOMA based BH (CD-NOMA-BH) and power-domain NOMA based BH (PD-NOMA-BH) systems. To satisfy dynamic-uneven traffic demands, we formulate the optimization problem to minimize the square of discrete difference by jointly optimizing power allocation, carrier assignment and beam scheduling. The non-convexity of the objective function and the constraint condition is solved through Dinkelbach’s transform and variable relaxation. As a further development, the closed-from and asymptotic expressions of outage probability are derived for CD/PD-NOMA-BH systems. Based on approximated results, the diversity orders of a pair of users are obtained in detail. In addition, the system throughput of U-NOMA-BH is discussed in delay-limited transmission mode. Numerical results verify that: i) The gap between traffic requests of CD/PD-NOMA-BH systems appears to be more closely compared with orthogonal multiple access based BH (OMA-BH);ii) The CD-NOMA-BH system is capable of providing the enhanced traffic request and capacity provision;and iii) The outage behaviors of CD/PD-NOMA-BH are better than that of OMA-BH. Copyright © 2024, The Authors. All rights reserved.

关键词： Satellite communication systems

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Exponential Synchronization of Chaotic Lur'e systems using Sampled-Data PI control

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IFAC-PapersOnLine 2023年第2期56卷 9787-9792页

作者： Hong-Zhang Wang Xing-Chen Shangguan Du Xiong Chuan-Ke Zhang School of Automation China University of Geosciences Wuhan 430074 P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 P. R. China

In this paper, an exponential synchronization design method for chaotic Lur'e systems is developed. Firstly, a sampled-data based proportional-integral (PI) type controller is used in the slave system to achieve the synchronization. Next, the synchronization problem of the chaotic Lur'e system is transformed into the stabilization problem of the synchronization error system. Then, by introducing virtual vectors for reconstruction, a new augmented error system is obtained. As a result, the synchronization design based on sampled-data PI type controller can be achieved using the existing sampling system method. And based on this, a criterion for exponential synchronization design is obtained using the Lyapunov functional method. Finally, the effectiveness of the developed method is demonstrated by numerical example.

关键词： Chaotic Lur'e systems sampled-data PI control exponential synchronization system augmentation method

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