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2024 CPSS and IEEE International Symposium on Energy Storage and Conversion, CPSS and ISESC 2024

作者： Wu, Mingkang Feng, Xingyu Zhu, Yihua Wang, Chenchen Luo, Chao Li, Kai Electric Power Research Institute China Southern Power Grid Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangdong Province Guangzhou City China School of Electrical Engineering Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350380514

As the grid strength gradually weakens, there is an urgent need to enhance the weak grid adaptability and precise control capability of photovoltaic-energy storage (PV-ES) systems. This paper analyzes the basic principles of the PV-ES virtual synchronous generator (PV-ES VSG) control scheme under the common DC bus. A flexible control scheme for grid-connected PV-ES systems is proposed based on DC-link voltage synchronization control (DVSC). Compared to existing PV-ES VSG control schemes, the proposed scheme can significantly improve the control flexibility of the energy storage and increase the diversity of its control algorithms, while maintaining similar power support capabilities and grid-connected performance. This improvement not only optimizes the performance of the energy storage unit in the power grid, but also reduces its burden and pressure on DC bus voltage control. Simulation results based on MATLAB/Simulink and the experiment results based on the Hardware-In-Loop (HIL) platform validate the effectiveness and rationality of the proposed scheme. The comparison with the PV-ES VSG also shows the advantages of the proposed scheme. © 2024 IEEE.

关键词： Synchronous generators

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Research on Task Scheduling Algorithms for Cloud-Edge Collaboration 19th

Research on Task Scheduling Algorithms for Cloud-Edge Collab...

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19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Lu, Shuai Zhou, Haibo Zhao, Shuaishuai Xu, Wangbei Fang, Kai Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China College of Mathematics and Computer Sciences Zhejiang A&F University Hangzhou311300 China

ISBN: (纸本)9783031651229

With the advent of the 5G era, the development of IoT technology has been accelerated. Due to the continuous increase in the amount of data waiting to be processed from the edge, edge nodes may struggle to handle such a vast amount of data. Therefore, the technology of cloud-edge collaboration has emerged, and how to achieve cloud-edge collaborative task scheduling has become a current research hotspot. This article provides a detailed exposition of the relevant work on task scheduling in the cloud-edge environment, and outlines the common optimization objectives in the cloud-edge collaboration scenario. The methods used to solve task scheduling problems are classified and summarized, including heuristic, heuristic algorithm based on linear programming, and meta-heuristic algorithms. The advantages and disadvantages of each algorithm are analyzed. Finally, the development trends of large-scale task scheduling in the cloud-edge environment are discussed, providing valuable insights for achieving real-time performance, efficiency, and energy conservation in the Internet of Things. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Scheduling algorithms

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Estimation of smoke echo signal using single-photon lidar 13

Estimation of smoke echo signal using single-photon lidar

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13th International Conference on Information Optics and Photonics, CIOP 2022

作者： Zhang, Yinbo Li, Sining Sun, Jianfeng Jiang, Peng Zhou, Shuaijun Zhang, Xin Hou, Yue Zhang, Hailong National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9781510660632

The non-uniform distribution of smoke and laser spot seriously limits the imaging ability of single-photon lidar through smoke. To this end, based on the collision theory between photons and smoke particles, this paper establishes the time-domain distribution model of scattered photons (Gamma), which considers the lidar system parameters and the characteristics of smoke particles. The shape parameter and inverse scale parameter are defined as the maximum scattering number K and the average scattering number β, respectively. The indoor test effectively illustrates the estimation ability of the model for smoke. The parameter estimation results show that the average scattering number β and the maximum scattering number K increase linearly with the increase of attenuation coefficient. This study is of great significance for the suppression of smoke backscattering and is expected to improve the weather adaptability of single-photon lidar. © 2022 SPIE.

关键词： Backscattering

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Research on Image Segmentation of Power Line Based on Encoder-Decoder Network 16th

Research on Image Segmentation of Power Line Based on Encode...

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16th Annual Conference of China Electrotechnical Society, CES 2021

作者： Sun, Haotian Fang, Zhijian Wei, Zhiguo Xie, Fei School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9789811915277

Power line network is the main carrier of the power system, and the smooth patrol inspection plays a crucial role in the fault prevention of the power line network. With the emergence of the patrol inspection UAV, how to detect the target of the power line through the picture and carry out accurate positioning has become a major research focus of the intelligent power system. A method for detecting and locating power lines based on an encoding lightweight decoder network (EDN-light) is proposed in this paper. It provides a foundation for the research and development of intelligent inspection of power line network, such as detection and identification, fault location, and guarantee of operation safety, and puts forward a new solution to the fault location diagnosis of power line using image. By EDN-light network, it focuses on detecting high level target and eliminating irrelevant information such as background, the convolutional layer of the encoder is used for extracting features, and the deconvolutional layer of the decoder for reconstructing images. The EDN-light network can improve the detection accuracy, and generate high-quality segmentation object suggestions. Use Turkish Electricity Transmission Corporation's aviation power line network dataset and self-made dataset to train the model to improve the generalization ability of the model. Experiments have found that due to the fully convolutional network design, it can carry out multi-scale input, For power line image segmentation and detection, the accuracy is better, and the evaluation indicators of the proposed models have increased. And due to the design of the lightweight decoder, Without retraining the network, the learned model can be extended to unknown linear category targets without repeated training. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

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An Order Demodulation Analysis Method for Planetary Gearboxes

An Order Demodulation Analysis Method for Planetary Gearboxe...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Chen, Jiwei Xie, Ruitong Zhu, Songsong Zhao, Mengxiong Wang, Zhiyuan Zhang, Mian Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

In addressing challenges such as the speed change of planetary gearbox (PG) during operation and the complexity in extracting fault features, an order demodulation analysis method based on order tracking (OT) and variational mode decomposition (VMD) is proposed. Non-stationary time domain signals are transformed into relatively stable angular domain signals through angular resampling. The intrinsic mode function (IMF) is obtained by demodulation of the angular multi-component signal using the VMD method. The instantaneous order of a proper IMF is calculated via Hilbert Transform. The sensitive single component is selected by matching the meshing order and the central order of the instantaneous order. Finally, the amplitude of the characteristic order components extracted from the instantaneous order spectrum was used as features and Support Vector Machine (SVM) was employed for the classification of four different conditions in the sun gear. Comparing the results of the proposed method with Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), the experimental results demonstrate the effectiveness of the proposed method in diagnosing PGs under non-stationary conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Epicyclic gears

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Study on Rotating Speed control of Dissimilar Metal Friction Stir Welding based on Fuzzy PID 6

Study on Rotating Speed Control of Dissimilar Metal Friction...

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2021 6th International Conference on Applied Mechanics and Structural Materials, AMSM 2021

作者： Liu, Yongning Qiao, Zhifeng Liu, Qingjian Huang, Jiahao Fu, Kang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China

The demand for lightweight vehicles that achieve energy conservation and emission reduction continues to grow. Aluminum alloys were commonly applied to the automotive industry to reduce the structural quality of the entire vehicle. However, the cost of aluminum alloy was higher than that of steel, so the industry considered the use of aluminum in combination with low-cost materials such as steel. Traditional welding technology was limited by the great physical difference between aluminum alloy and steel. Friction Stir Welding, a solid phase welding technology, can overcome the connection problem of aluminum and its alloys with steel, but the process parameters of FSW directly affect the welding quality. This paper established the FSW process of two different metals of DC05 and AL6061. Aimed to get a good welding joint, the error of tool speed is reduced by fuzzy PID system established in this paper, and the tool speed is controlled stably. Simulink simulation was established, and compared with the simulation results, fuzzy PID control can control the precision and stability of the tool speed of FSW, improve the welding quality, and provide a certain theoretical basis for the tool speed control. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Friction stir welding

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Multimodal Multilevel Attention for Semi-Supervised Skeleton-Based Gesture Recognition

SSRN

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SSRN 2024年

作者： Liu, Jinting Gan, Ming-Gang He, Yuxuan Guo, Jia Hu, Kang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

Although skeleton-based gesture recognition based on supervised learning has made promising achievements, the reliance on large amounts of annotation for training poses a significant cost. This paper addresses semi-supervised gesture recognition, aiming to learn feature representations effectively from unlabeled data. To resolve this problem, we propose a novel multimodal multilevel attention network to achieve semi-supervised learning. This model uses an attention mechanism to polymerize multimodal and multilevel complementary semantic information of the hand skeleton, designing a multimodal multilevel contrastive loss to measure the similarity of features for semi-supervised learning. Specifically, our method explores the relationships between joint, bone, and motion to learn more discriminative feature representations. Considering the hierarchy of the hand skeleton, the skeleton data is divided into multilevel (i.e., hand-level, finger-level, and joint-level) to capture complementary semantic information. Furthermore, a multimodal contrastive loss measure similarity among multilevel representations. The proposed method outperforms the semi-supervised skeleton-based gesture recognition tasks, according to extensive experimentation on two challenging datasets from SHREC-17 and DHG 14/28 datasets. © 2024, The Authors. All rights reserved.

关键词： Gesture recognition

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Hypersonic Re-entry Vehicle Fault-Tolerant control Against Actuator Failure via Integral Sliding Mode

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Journal of Beijing Institute of Technology (English Edition) 2021年第ZK期30卷 111-120页

作者： Guo, Fuhui Lu, Pingli School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

A fault-tolerant control (FTC) scheme is proposed based on integral sliding mode(ISM) for attitude control of hypersonic re-entry vehicle (HRV) under partial loss of actuator effectiveness. First, the inner/outer loop mathematical model of HRV in the present of actuator failure is given with specific analysis on torque. Then prescribed performance approach is introduced to the ISM controller design by error transformation. Specifically, the transformation error rather than tracking error is chosen as the sliding variable to establish the sliding mode surface and reaching law. As a result, the attitude tracking error of HRV is limited into the expected range. Meanwhile, the transient process and the steady state behavior are both considered. Considering that the unknown fault information of actuator can cause adverse effect on HRV, an extended state observer(ESO) is adopted to estimate the unknown actuator failure. Thus the observer result is served as compensation for the loss of the controlled system performance. Simulation results show that the proposed scheme can fulfil the tracking task with prescribed performance. © 2020 Journal of Beijing Institute of Technology

关键词： Actuators

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Research on Identification Strategy of Fault-Sensitive Frequency for Planetary Gearboxes

Research on Identification Strategy of Fault-Sensitive Frequ...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Xie, Ruitong Zhang, Mian Chen, Jiwei Zhu, Songsong Wang, Zhiyuan Zhao, Mengxiong Xiang, Hongbiao Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

Planetary gearboxes find extensive application in wind power generation, aerospace, industrial production and other fields. Harsh operational conditions and prolonged periods of continuous work often lead to various gear damages. Therefore, it is important to continuously monitor the health status of planetary gearboxes. However, the fault-sensitive frequencies of planetary gearboxes used in the existing signal models and fault diagnosis indicators are calculated theoretically or searched artificially. In response to this, this paper proposes a strategy for identifying fault-sensitive frequencies in planetary gearboxes intelligently by combining spectral amplitude analysis with three models: Random Forest (RF), Support Vector Machine (SVM) and Deep Neural Network (DNN). Experiments are carried out to verify the effectiveness and superiority of the proposed strategy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep neural networks

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Research on intelligent Credibility Evaluation Method of Aircraft HWIL Simulation system Based on complex Network 17th

Research on Intelligent Credibility Evaluation Method of Air...

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17th Chinese intelligent systems Conference, CISC 2021

作者： Huapin, Geng Ni, Li Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electromechanical Engineering Institute Beijing China Beijing University of Aeronautics and Astronautics Beijing China

ISBN: (纸本)9789811663192

Simulation credibility is an effective means to measure the effectiveness and correctness of simulation, and it is the cornerstone of simulation. According to the uncertainty of physical effect model and the complex interaction of model information in aircraft HWIL simulation system, The idea of time-varying directed weighted network and uncertainty measurement is introduced into the process of credibility evaluation of simulation system based on complex network and credibility evaluation theory;the credibility evaluation model of time-varying topological structure based on uncertainty measurement of model information interaction is established to quantitatively evaluate the credibility of simulation system. Taking a typical HWIL simulation system as an example, the effectiveness of the credibility evaluation method of simulation system based on complex network is fully tested. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hardware-in-the-loop simulation

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