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Recent advancement of flow-induced piezoelectric vibration energy harvesting techniques:principles,structures,and nonlinear designs

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Applied Mathematics and Mechanics(English Edition) 2022年第7期43卷 959-978页

作者： Dongxing CAO Junru WANG Xiangying GUO S.K.LAI Yongjun SHEN Faculty of Materials and Manufacturing Beijing University of TechnologyBeijing 100124China Beijing Key Laboratory of Nonlinear Vibrations and Strength of Mechanical Structures Beijing 100124China School of Automation Beijing Information Science and Technology UniversityBeiing 100192China Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityKowloonHong KongChina Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center The Hong Kong Polytechnic UniversityKowloonHong KongChina State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China

Energy harvesting induced from flowing fluids(e.g.,air and water flows)is a well-known process,which can be regarded as a sustainable and renewable energy *** addition to traditional high-efficiency devices(e.g.,turbines and watermills),the micro-power extracting technologies based on the flow-induced vibration(FIV)effect have sparked great concerns by virtue of their prospective applications as a self-power source for the microelectronic devices in recent *** article aims to conduct a comprehensive review for the FIV working principle and their potential applications for energy ***,various classifications of the FIV effect for energy harvesting are briefly introduced,such as vortex-induced vibration(VIV),galloping,flutter,and wake-induced vibration(WIV).Next,the development of FIV energy harvesting techniques is reviewed to discuss the research works in the past three *** application of hybrid FIV energy harvesting techniques that can enhance the harvesting performance is also ***,the nonlinear designs of FIV-based energy harvesters are reported in this study,e.g.,multi-stability and limit-cycle oscillation(LCO)***,advanced FIV-based energy harvesting studies for fluid engineering applications are briefly ***,conclusions and future outlook are summarized.

关键词： vibration-driven energy harvesting flow-induced vibration(FIV) piezoelectric approach nonlinear design

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Accurate Identification and Localization of Transmission Lines under Complex Lighting for Distribution Network Power Supply Operation Robots

Accurate Identification and Localization of Transmission Lin...

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2024 China automation Congress, CAC 2024

作者： Liu, Tianhe Chen, Xin Hu, Chenyu Jian, Xu Li, Shengzu Wang, Gang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Distribution Department State Grid Hubei Electric Power Co. Ltd. Wuhan Power Supply Company 430070 China

ISBN: (纸本)9798350368604

Accurate identification and position of transmission lines is critical for robots to safely and effectively perform distribution network operations. However, such tasks are often challenged by complex lighting conditions, where depth information can be easily lost. Transmission lines have limited texture features and reflective surfaces, making it difficult to match image feature points. To address these challenges, this paper proposes a visual perception system for weak texture targets under complex lighting, based on an "eye-on-hand" configuration and a depth complementation algorithm. Furthermore, a high-precision identification and localization method for transmission line grasping points is developed, utilizing the fusion of binocular visual color maps and depth maps. The proposed method has been shown to effectively solve the problem of identifying and localizing the grasping points of transmission lines under complex lighting conditions. Experiments demonstrated that the method can improve the localization accuracy to within ±4mm, outperforming other algorithms. The method is characterized as simple and efficient, and it enhances the environmental adaptability of distribution network robots. © 2024 IEEE.

关键词： Binocular vision

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A Family of Deployable Single-Loop Metamorphic Mechanisms for Aerospace Manipulators: Synthesis, Network, and Analysis

SSRN

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SSRN 2024年

作者： Zhang, Yang Kang, Xi Li, Bing State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen518052 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518052 China

Guided by predetermined degrees of freedom for different desired tasks, the type synthesis of single-loop metamorphic mechanisms (SLMMs) has long posed a challenge. Owing to the complexity and coupling of their overconstraints and the variability of constraints arising from bifurcation motions, it is difficult to ensure geometric coordination and synchronous motion for a network of multiple SLMMs. Here, we propose an approach to type synthesize SLMMs using the atlas method. A novel family of SLMMs is further synthesized. The mobility analysis of a selected 7R SLMM is carried out via screw theory. The kinematics and bifurcation phenomena are analyzed and verified through numerical simulation using computer-aided design models. To evaluate the performance of the SLMMs, the mapping relationship between key design parameters and performance indicators, such as the grasping angle, folding angle, and mechanical advantage, is studied. A networking method is then proposed by considering the geometric coordination conditions and variation of the overconstraints of SLMMs. Prototypes of an SLMM and manipulator with optimal geometrical parameters are developed to verify the feasibility and correctness of the proposed method and kinematic analysis. © 2024, The Authors. All rights reserved.

关键词： Manipulators

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Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection

arXiv

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arXiv 2024年

作者： Jiang, Weibo Ren, Weihong Tian, Jiandong Qu, Liangqiong Wang, Zhiyong Liu, Honghai State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science China Department of Statistics and Actuarial Science The University of Hong Kong Hong Kong

Human-Object Interaction (HOI) detection plays a vital role in scene understanding, which aims to predict the HOI triplet in the form of . Existing methods mainly extract multi-modal features (e.g., appearance, object semantics, human pose) and then fuse them together to directly predict HOI triplets. However, most of these methods focus on seeking for self-triplet aggregation, but ignore the potential cross-triplet dependencies, resulting in ambiguity of action prediction. In this work, we propose to explore Self- and Cross-Triplet Correlations (SCTC) for HOI detection. Specifically, we regard each triplet proposal as a graph where Human, Object represent nodes and Action indicates edge, to aggregate self-triplet correlation. Also, we try to explore cross-triplet dependencies by jointly considering instance-level, semantic-level, and layout-level relations. Besides, we leverage the CLIP model to assist our SCTC obtain interaction-aware feature by knowledge distillation, which provides useful action clues for HOI detection. Extensive experiments on HICO-DET and V-COCO datasets verify the effectiveness of our proposed SCTC. Copyright © 2024, The Authors. All rights reserved.

关键词： Distillation

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A Track Association Algorithm Based on Transitive Closure Fuzzy Clustering

A Track Association Algorithm Based on Transitive Closure Fu...

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International Conference on Guidance, Navigation and Control, ICGNC 2020

作者： Huang, Yinghao Zhang, Kaihua Wang, Jing Cai, Yunze Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Shanghai Academy of Spaceflight Technology Shanghai201100 China

ISBN: (纸本)9789811581540

Aiming at track association before and after multi-target track interruption, a track associating method on the basis of transitive closure fuzzy clustering is proposed. Firstly, the method converts the traditional track fuzzy similarity matrix into a fuzzy equivalent matrix by squaring method, and split sub-blocks of the equivalent matrix. Then the method calculates final track correlation matrix based on correlating threshold function related to track interruption duration, and obtains correct track association by the correlation matrix. The simulation proves that, the proposed method improves association accuracy comparing with other association algorithms based on fuzzy theory, and presents a more significant advantage in the case that targets maneuver and tracks cross. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy clustering

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CoIn-SafeLink: Safety-critical Control With Cost-sensitive Incremental Random Vector Functional Link Network

arXiv

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arXiv 2025年

作者： Hu, Songqiao Liu, Zeyi He, Xiao Shen, Zhen Department of Automation Tsinghua University Beijing100084 China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences China

Control barrier functions (CBFs) play a crucial role in achieving the safety-critical control of robotic systems theoretically. However, most existing methods rely on the analytical expressions of unsafe state regions, which is often impractical for irregular and dynamic unsafe regions. In this paper, a novel CBF construction approach, called CoIn-SafeLink, is proposed based on cost-sensitive incremental random vector functional-link (RVFL) neural networks. By designing an appropriate cost function, CoIn-SafeLink achieves differentiated sensitivities to safe and unsafe samples, effectively achieving zero false-negative risk in unsafe sample classification. Additionally, an incremental update theorem for CoIn-SafeLink is proposed, enabling precise adjustments in response to changes in the unsafe region. Finally, the gradient analytical expression of the CoIn-SafeLink is provided to calculate the control input. The proposed method is validated on a 3-degree-of-freedom drone attitude control system. Experimental results demonstrate that the method can effectively learn the unsafe region boundaries and rapidly adapt as these regions evolve, with an update speed approximately five times faster than comparison methods. The source code is available at https://***/songqiaohu/CoIn-SafeLink. Copyright © 2025, The Authors. All rights reserved.

关键词： Aircraft control

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Two-Stage OD Flow Prediction for Emergency in Urban Rail Transit

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IEEE Transactions on intelligent Transportation systems 2024年第1期25卷 920-928页

作者： Zhu, Guangyu Ding, Jiacun Wei, Yun Yi, Yang Xu, Sendren Sheng-Dong Wu, Edmond Q. Beijing Jiaotong University Key Lab. of Transport Industry of Big Data Application Technologies for Comprehensive Transport The Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing100044 China Beijing Mass Transit Railway Operation Corporation Ltd. Beijing100014 China Yangzhou University College of Information Engineering Yangzhou225127 China National Taiwan University of Science and Technology Automation and Control Center The Graduate Institute of Automation and Control Taipei106335 Taiwan Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

Urban rail transit (URT) is vulnerable to natural disasters and social emergencies including fire, storm and epidemic (such as COVID-19), and real-time origin-destination (OD) flow prediction provides URT operators with important information to ensure the safety of URT system. However, hindered by the high dimensionality of OD flow and the lack of supportive information reflecting the real-time passenger flow changes, study in this area is at the beginning stage. A novel model consisting of two stages is proposed for OD flow prediction. The first stage predicts the inflows of all stations by Long Short-Term Memory (LSTM) in real time, where the dimension is reduced compared with predicting OD flows directly. In the second stage, the notion of separation rate, namely, the proportion of inbound passengers bounding for another station, is estimated. Finally, The OD flow is predicted by multiplying the inflow and separation rate. Experiments based on Hangzhou Metro dataset show the proposed model outperforms the contrast model in weighted mean average error (WMAE) and weighted mean square error (WMSE). Results also suggest that the proposed prediction model performs better on weekdays than on weekends, and with greater accuracy on larger OD flows. © 2000-2011 IEEE.

关键词： Forecasting

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Graph Attention Networks Unleashed: A Fast and Explainable Vulnerability Assessment Framework for Microgrids

arXiv

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arXiv 2025年

作者： Liu, Wei Zhang, Tao Lin, Chenhui Li, Kaiwen Wang, Rui College of System Engineering the National University of Defense Technology the Xiangjiang Laboratory the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology HKL-MSI2T Changsha410073 China State Key Laboratory of Power Systems Department of Electrical Engineering Tsinghua University Beijing100084 China

Independent microgrids are crucial for supplying electricity by combining distributed energy resources and loads in scenarios like isolated islands and field combat. Fast and accurate assessments of microgrid vulnerability against intentional attacks or natural disasters are essential for effective risk prevention and design optimization. However, conventional Monte Carlo simulation (MCS) methods are computationally expensive and time-consuming, while existing machine learning-based approaches often lack accuracy and explainability. To address these challenges, this study proposes a fast and explainable vulnerability assessment framework that integrates MCS with a graph attention network enhanced by self-attention pooling (GAT-S). MCS generates training data, while the GAT-S model learns the structural and electrical characteristics of the microgrid and further assesses its vulnerability intelligently. The GAT-S improves explainability and computational efficiency by dynamically assigning attention weights to critical nodes. Comprehensive experimental evaluations across various microgrid configurations demonstrate that the proposed framework provides accurate vulnerability assessments, achieving a mean squared error as low as 0.001, real-time responsiveness within 1 second, and delivering explainable results. Copyright © 2025, The Authors. All rights reserved.

关键词： Microgrids

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Fast least-squares prestack time migration via accelerating the explicit calculation of Hessian matrix with dip-angle Fresnel zone

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Petroleum Science 2022年第3期19卷 1031-1047页

作者： Bo-Wu Jiang Jiang-Jie Zhang Hao Zhang Wen-Kai Lu College of Mechanical and Electrical Engineering Beijing University of Chemical TechnologyBeijing100029China The Institute for Artificial Intelligence(THUAI) Beijing100084China State Key Laboratory of Intelligent Technology and Systems Beijing100084China Beijing National Research Center for Information Science and Technology(BNRist) Beijing100084China The Department of Automation Tsinghua UniversityBeijing100084China Key Laboratory of Petroleum Resource Research Institute of Geology and GeophysicsChinese Academy of SciencesBeijing100029China Institute of Geomechanics Chinese Academy of Geological SciencesBeijing100081China

Amplitude versus offset analysis is a fundamental tool for determining the physical properties of reservoirs but generally hampered by the blurred common image gathers(CIGs).The blurring can be optimally corrected using the blockwise least-squares prestack time migration(BLS-PSTM),where common-offset migrated sections are divided into a series of blocks related to the explicit offsetdependent Hessian matrix and the following inverse filtering is iteratively applied to invert the corresponding ***,calculating the Hessian matrix is *** present a fast BLS-PSTM via accelerating Hessian calculation with dip-angle Fresnel zone(DFZ).DFZ is closely related to optimal migration aperture,which significantly attenuates migration swings and reduces the computational cost of ***,our fast BLS-PSTM is implemented as a two-stage ***,we limit the aperture for any imaging point with an approximated the projected Fresnel zone before calculating the Hessian ***,we determine whether a seismic trace contributes to the imaging point via DFZ during calculating the Hessian *** tests on synthetic and field data validate the distinct speedup with higher-quality CIGs compared to BLS-PSTM.

关键词： Prestack time migration Fresnel zone Hessian Least squares migration Migrated gather

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Analysis of Spiral Scanning Amplitude Modulation Methods for Two-photon Endomicroscopy 10

Analysis of Spiral Scanning Amplitude Modulation Methods for...

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10th Symposium on Novel Optoelectronic Detection technology and Applications

作者： Cui, Haodong Wang, Conghao Liu, Huilan Zhang, Xiulei Hu, Yanhui Fu, Qiang Wu, Runlong Wang, Aimin Feng, Lishuang School of Instrumentation and Optoelectronic Engineering Beihang University Beijing100191 China Beijing100191 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Transcend Vivoscope Biotech Co. Ltd. Beijing100049 China Beijing Key Laboratory for Optoelectronics Measurement Technology Beijing Information Science and Technology University Beijing100192 China State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronics Peking University Beijing100871 China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

Two-photon endomicroscopy is a high-resolution label-free imaging technique for biological tissues. This paper analyzes sinusoidal and triangular amplitude modulation methods for spiral scanning two-photon endomicroscopy. In the theoretical modeling section, the mathematical model of PZT fiber scanner is established, and the distortion of fiber scanning trajectory caused by two amplitude modulated sine wave signals is simulated and evaluated. In the experimental verification section, a test platform is constructed to measure the scanning trajectory distortion driven by these amplitude modulated sine wave signals. Finaly, spiral scanning two-photon endomicroscopic imaging of in-vivo GFP mice brain tissues using sinusoidal amplitude modulated signals are demonstrated. © 2025 SPIE.

关键词： Amplitude modulation

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