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2024 10th International Conference on Applied Materials and Manufacturing Technology, ICAMMT 2024

作者： Wu, Junjie Ji, Yulei Zhong, Lei Wang, Yuhan State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China Shanghai TOP Numerical Control Technology Co. Ltd Shanghai201100 China

The increasing demand for highly efficient and precise machining in the aerospace industry is leading to increasingly stringent requirements for machine tool accuracy measurement and compensation technologies. However, existing methods can only measure the accuracy of machine tools after they have been shut down, using instruments that do not measure the kinematic errors during the machining process. To address this issue, a method for real-time prediction of kinematic errors in a five-axis machine tool has been proposed to enhance machining accuracy and efficiency. The method employs a neural network-based predictive model, which has been trained and validated through experimental testing and data collection using internal sensors of the machine tool. The study reveals that this predictive model can effectively forecast the kinematic errors, through real-time compensation, and can reduce errors by 60-86%, significantly enhancing machine performance. © Published under licence by IOP Publishing Ltd.

关键词： Aerospace industry

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Optimal Sensor Placement for Full-Set TDOA Localization Accounting for Sensor Location Errors

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Zhang, Chengjie Han, Xinyang Kong, He Ho, K.C. Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China University of Missouri Electrical Engineering and Computer Science Department ColumbiaMO65211 United States

The positioning accuracy of a signal source is influenced by where the sensors are deployed. Studies in the literature for the optimal sensor placement (OSP) of localization often ignore the presence of sensor position errors. In practice, however, it is impossible to place the sensors precisely at the desired locations. This work designs OSP by accounting for the presence of Gaussian sensor position errors that are independent and identically distributed (IID), with the full set of Time Difference of Arrival measurements corrupted by Gaussian IID noise. The criterion is the A-optimality equal to the trace of the source position Cramer-Rao Bound (CRB). We show that the presence of sensor position errors introduces a multiplication factor to the same criterion for the case without sensor position errors. The latter factor is dependent on the ratio of the sensor position error power to the range difference noise power but independent of the sensor positions, implying that the A-optimality OSP in the presence of sensor position errors is the same as in the absence. To our knowledge, this is the first time such results have been derived. Simulation studies validate the derived OSP, show the minimal OSP performance gap with sensor positioning error and without, and illustrate the better source localization accuracy by OSP. © 1965-2011 IEEE.

关键词： Cramer-Rao bounds

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Gesture Recognition of sEMG Based on Res-LSTM 17th

Gesture Recognition of sEMG Based on Res-LSTM

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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Design and development of power balance monitoring and alarm system of engine room's generator sets for offshore platform 10

Design and development of power balance monitoring and alarm...

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10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

作者： Li, Ao Hu, Lei Zhu, Siwei Yang, Yuchen Li, Zhilong School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuhan China Laboratory of Electronic Control System for Low-Speed Engine National Engineering Laboratory of Power Systems of Ships and Ocean Engineering Wuhan China Key Laboratory of Marine Power Engineering and Technology Granted by MOT Wuhan University of Technology Wuhan China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

Aiming at the problem of power unbalance caused by insufficient combustion of crude oil or uneven operation of multiple cylinders in offshore platform generator sets, the power balance monitoring method and the strategy are studied with the integration of thermal parameters, instantaneous speed, torsional vibration and indicator diagram, the hardware design of sensor arrangement and monitoring scheme based on multiple generator sets are carried out, the online monitoring and alarm system software for the power balance of offshore platform generator sets is developed, the real-time monitoring function of the working status of each cylinder of offshore platform generator sets is conducted, the risk of the possibility of a series of failures caused by the power unbalance of the lame cylinder with the decline of the working performance is reduced. Simultaneously, it is a good technical means to make maintenance decisions according to the situation for the engine room manager. © 2022 IEEE.

关键词： Monitoring

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Design and Analysis of Terminal Guidance Law for Kinetic Interceptors based on Pulse Engine

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Journal of Electronic Research and Application 2024年第5期8卷 95-108页

作者： Shixin Li Jia Ma Shuai Yue School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China Aerospace System Engineering Shanghai Shanghai 201100China Shanghai Key Laboratory of Spacecraft Mechanism Shanghai 201108China National Key Laboratory of Space Intelligent Control Beijing 100048China

A new terminal guidance law is proposed based on a solid propellant pulse engine and an improved proportional navigation method to address the terminal guidance issue for kinetic *** this basis,the start-stop curve of the pulse motor during the terminal guidance process is designed,along with its start-up *** effectiveness of the proposed guidance strategy is verified through simulation.

关键词： Pulse engine Terminal guidance law Kinetic interceptor Proportional navigation method

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MARS: Multi-Agent Deep Reinforcement Learning for Real-Time Workflow Scheduling in Hybrid Clouds with Privacy Protection 30

MARS: Multi-Agent Deep Reinforcement Learning for Real-Time ...

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30th IEEE International Conference on Parallel and Distributed systems, ICPADS 2024

作者： Cheng, Long He, Haoyang Gu, Yan Liu, Qingzhi Zhao, Zhiming Fang, Fang North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering Beijing China Wageningen University and Research Information Technology Group Netherlands University of Amsterdam Research Group of Multi-Scale Networked Systems Netherlands

ISBN: (纸本)9798331515966

Scheduling workflows in hybrid cloud environments presents significant challenges due to the inherent complexity of workflows and the dynamic nature of cloud resources. This complexity is further increased when attempting to balance workflow performance with privacy protection. Recent efforts have leveraged deep reinforcement learning (DRL) to address these challenges. However, most of these approaches rely on single-agent models, which can lead to security issues and scalability problems due to their centralized processing. Specifically, the properties of workflows are transferred to the single agent, which risks leaking privacy information. Our paper addresses these issues by introducing MARS, a real-time workflow scheduling method that prioritizes privacy protection in hybrid clouds. MARS leverages multi-agent deep reinforcement learning (MADRL) to optimize the workflow scheduling of cloud virtual machines (VMs). The benefit of our solution is that it relies on the collaborative learning of multi-agents on multiple VMs, which could assign user data to specific cloud servers for privacy protection while sharing training experiences between agents. In our implementation, MARS aims to reduce workflow completion time and operational costs while complying with strict privacy protection guidelines. The experimental results demonstrate that MARS can significantly surpass existing methods, reducing makespan by an average of 53.18% and costs by 61.98% compared to basic techniques, and achieving 20.26% and 25.71% improvements over the latest advanced methods, respectively. © 2024 IEEE.

关键词： Deep reinforcement learning

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Review of Research Advances in CFD Techniques for the Simulation of Urban Wind Environments

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Fluid Dynamics & Materials Processing 2022年第2期18卷 449-462页

作者： Pengfei Ju Mingrui Li Jingying Wang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education(Tianjin University of Technology) Tianjin300384China School of Energy and Power Engineering Shandong UniversityJinan250061China Shandong Engineering Laboratory for High-Efficiency Energy Conservation and Energy Storage Technology&Equipment Shandong UniversityJinan250061China

Computational fluid dynamics(CFD)has become the main method for the prediction of the properties of the external wind environment in cities and other urban contexts.A review is presented of the existing literature in terms of boundary conditions,building models,computational domains,computational grids,and turbulence *** specific issues,such as the accuracy/computational cost ratio and the exploitation of existing empirical correlations,are also examined.

关键词： Computational fluid dynamics wind environment pre-processing settings

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New energy urban rail vehicle hybrid energy storage control system

New energy urban rail vehicle hybrid energy storage control ...

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2024 International Conference on Renewable Energy Technology and Electrical engineering, RETEE 2024

作者： Yan, Zhaokun Yan, Shubin Huang, Biyi Wu, Taiquan School of Electrical and Control Engineer North University of China Taiyuan030051 China School of Electrical Engineering Zhejiang University of Water Resources and Electric Power Hangzhou310018 China Zhejiang-Belarus Joint Laboratory of Intelligent Equipment and System for Water Conservancy and Hydropower Safety Monitoring Hangzhou310018 China

With the increasing demand for urban transportation and the gradual strengthening of environmental protection awareness,new energy urban rail transportation has gradually become the future trend of urban development. The hybrid energy storage system is one of the key technologies to achieve the goals of energy saving and emission reduction of new urban rail vehicles, improving operation efficiency and comfort. In the traction stage of urban rail vehicles, the energy storage unit composed of lithium batteries and supercapacitors is jointly supplied with the power grid. In the braking stage, the energy storage unit composed of lithium batteries and supercapacitors is a common way for urban rail vehicles to recover *** study validates the efficacy of employing fuzzy control methodology to enhance the performance of the energy storage system. The experimental results show that the fuzzy control method can better balance the load distribution between lithium batteries and supercapacitors, thus extending their service life and improving the overall system *** on the SOC energy management strategy of supercapacitors, urban rail vehicle power is allocated to supercapacitors and lithium-ion batteries via a low-pass filter. system power is adjusted based on supercapacitor SOC, determining capacitor charging/discharging states and suppressing system output power. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Fuzzy control

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Cascading Failure Screening Based on Gradient Boosting Decision Tree for HVDC Sending-End systems with High Wind Power Penetration

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IEEE Transactions on Power systems 2025年

作者： Liu, Tianhao Yan, Jiongcheng Liu, Yutian Chung, Chi Yung Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Kowloon Hong Kong

In LCC-HVDC sending-end AC systems, cascading failures combined with the dynamic response of wind turbines (WTs) can lead to HVDC commutation failures. The resulting transient voltage disturbances cause WT tripping in sending-end systems. Cascading failures that involve the interaction between WTs and HVDC significantly limit the wind power transmitted by HVDC systems. This paper proposes an online cascading failure screening method based on gradient boosting decision tree (GBDT) for HVDC sending-end systems with large-scale WTs. First, a confidence level-based WT tripping model is proposed for cascading failure risk assessment considering a typical cascading failure propagation pattern. Then, Monte Carlo tree search is improved using a contrastive pruning technique to generate evenly distributed samples of cascading failures offline. Dynamic insecure scenarios are quickly identified using an improved support vector machine. Finally, GBDT is utilized to screen for cascading failures online by predicting subsequent high-risk failures using operating features. A dynamic weighting technique is proposed for GBDT to improve the fault prediction accuracy. Simulation results of a modified New England test system and the Ningxia provincial power grid in western China demonstrate that the proposed method can quickly screen for cascading failures considering the dynamic interaction between WTs and HVDC. © 1969-2012 IEEE.

关键词： Risk assessment

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Invulnerability Evaluation of UAV Swarms Communication Network Based on Node Influence

Invulnerability Evaluation of UAV Swarms Communication Netwo...

引用

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Hou, Yueqi Liang, Xiaolong Qi, Duo Zhang, Jiaqiang Ren, Baoxiang Li, Ye Aviation Swarm Technology and Operational Application Laboratory Air Traffic Control and Navigation College Air Force Engineering University Xi’an710051 China Shaanxi Key Laboratory of Meta-Synthesis for Electronic and Information System Xi’an710051 China Air Traffic Control and Navigation College Air Force Engineering University Xi’an710051 China

ISBN: (纸本)9789811581540

Aiming at the damage of UAV swarms communication network in the denied environment, this paper proposes a method of invulnerability evaluation based on the node influence. Considering the node connectivity and its position in the network topology, the network efficiency reductions after node deletion and node degree are taken to measure the node influence. Based on the node influence, a network invulnerability entropy model is established, which can better represent the significance and dispersion of nodes with different influence in the network, to measure the network invulnerability when nodes are attacked. The simulation results show that the proposed method can better distinguish the difference of invulnerability between two UAV swarm communication networks with similar performance, and provide a theoretical basis for the design and optimization of the network structure. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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