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Experimental and numerical studies on buckling and post-buckling behavior of T-stiffened variable stiffness panels

Chinese Journal of Aeronautics 2024年第10期37卷 459-470页

作者： Yan HUANG Yahui ZHANG Bin KONG Jiefei GU Zhe WANG Puhui CHEN State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China AVIC Aviation Power Control System Research Institute Wuxi 214063China Chengdu Aircraft Design and Research Institute Aviation Industry Corporation of ChinaChengdu 610091China School of Mechanical Engineering Jiangnan UniversityWuxi 214122China School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China China National Key Laboratory of Strength and Structural Integrity Aircraft Strength Research Institute of ChinaXi’an 710065China

Currently,experimental research on variable stiffness design mainly focuses on *** ensure adaptability in practical application,it is imperative to conduct a systematic study on stiffened variable stiffness structures,including design,manufacture,experiment,and *** on the minimum curvature radius and process schemes,two types of T-stiffened panels were designed and *** compression tests have been carried out and the results indicate that the buckling load of variable stiffness specimens is increased by 26.0%,while the failure load is decreased by 19.6%.The influence mechanism of variable stiffness design on the buckling and failure behavior of T-stiffened panels was explicated by numerical *** primary reason for the reduced strength is the significantly increased load bearing ratio of *** experimental investigations of stiffened variable stiffness structures are very rare,this study can be considered a reference for future work.

关键词： Variable stiffness composite Buckling Post-buckling Finite element method Stiffened panels

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Deep Learning Based Fault Diagnosis for Chemical Process with Statistical Feature Fusion 42

Deep Learning Based Fault Diagnosis for Chemical Process wit...

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42nd Chinese control Conference, CCC 2023

作者： Zhang, Lei Xia, Hao Cha, Bao School of Control Science and Control Engineering Dalian University of Technology Dalian116024 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610091 China

ISBN: (纸本)9789887581543

The existing fault diagnosis methods based on deep neural networks mostly rely on process data for fault classification and diagnosis, which makes it difficult to distinguish minor faults with similar data features. Therefore, this paper proposes a deep learning-based fault diagnosis model that combines statistical indicators and neural networks. By analyzing and calculating the relevant information entropy to screen the statistical signal features of time domain and frequency domain, we can extract more hidden information from the raw data, and use the convolutional autoencoder to compress the statistical indicators for feature extraction, and use CNN network to extract features from raw data. Finally, the two sets of features are fused and input into the LSTM network to obtain temporal information for fault diagnosis. Tests conducted on the Tennessee Eastman (TE) process show that the proposed model outperforms typical classifiers and improves the diagnostic accuracy of minor faults. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Failure analysis

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Adaptive Virtual Synchronous Machine control Strategy for MMC Interconnect Converter Based on Distributed Measurement 9

Adaptive Virtual Synchronous Machine Control Strategy for MM...

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9th Asia Conference on Power and Electrical engineering, ACPEE 2024

作者： Lu, Shaoqun Xiang, Zhengrong Zhong, Kunyan Meng, Jinxue Dang, Yinning Guangxi Science&Technology Normal University School of Mechanical and Electrical Engineering Laibin China Hunan Vocational Institute of Technology Hunan Engineering Laboratory for Photovolatic System Control and Optimization Xiangtan China

ISBN: (纸本)9798350309638

Aiming at the problem of poor stability and response of traditional voltage source control, an adaptive virtual synchronous machine control strategy for Modular Multilevel Converter (MMC) interconnect converter based on distributed measurement is proposed. Through the introduction of virtual synchronous machine control, the interconnect converter can actively participate in grid stabilisation, and its adaptive strategy is adopted to enhance control system suppression capability on frequency oscillation, and the distributed measurement-based MCC control method can solve the insufficient flexibility and scalability of the traditional MMC centralised control strategy. The experimental results show that a large inertia in the DC bus dynamic process helps to enhance the voltage stability of the DC microgrid system. The AC microgrid bus frequency also has a large inertia, which contributes to the AC microgrid frequency stability. The transmitted power has greater inertia during load variations, especially when the load variations are greater. In addition, the distributed measurement-based MMC interconnect converter excels in steady-state control performance, balancing the capacitive voltages of the sub-modules and maintaining stable operation of the system through steady-state distributed control. © 2024 IEEE.

关键词： Balancing

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Fuzzy-Cycle: Visible to Infrared Ship Image Translation Based on CycleGAN 6

Fuzzy-Cycle: Visible to Infrared Ship Image Translation Base...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： He, Long Yu, Yue Liu, Chang Sun, Yangyang Jiang, Feng Hu, Xiaoning Pan, Chengwei Dong, Xiwang School of Artificial Intelli-gence Beihang University Beijing China Beijing Institute of Control and Electronic Technology Beijing China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University School of Artificial Intelligence Institute of Unmanned System Beijing China

ISBN: (纸本)9798350356618

Detecting targets in infrared ship images is crucial for various applications, such as maritime rescue and ship inspection. Training contemporary mainstream detection and segmentation models, however, requires large-scale, high-quality infrared ship image datasets. In open-world maritime confrontation scenarios, the complex and variable environment, scarcity of target ships, and limited acquisition conditions make it challenging to construct high-quality infrared ship image datasets. To address this issue, this paper proposes an unpaired visible-infrared ship image translation model based on CycleGAN, named Fuzzy-Cycle. The model introduces a fuzzy cycle loss to encourage the model to learn feature mapping rules between different domains while minimizing attention to unnecessary features. Additionally, the method employs U-Net as the generator network to retain shallow image features during upsampling and selects PatchGAN as the discriminator network, embedding Haar wavelet transform to enhance the discriminator's ability to analyze image frequency domain features. Experiments on the VAIS dataset demonstrate that the proposed algorithm outperforms mainstream unpaired image transfer models, showing excellent performance in the task of visible-infrared ship image translation. Furthermore, zero-shot image translation experiments on the HRSC2016 dataset prove the generalizability and reliability of the proposed method. © 2024 IEEE.

关键词： Wavelet transforms

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SAR Image Registration Based on Feature Points Using Improved CSP-DenseNet 6

SAR Image Registration Based on Feature Points Using Improve...

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6th IEEE International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2023

作者： Wang, Ziwei Yang, Yanjiao Qu, Guangzhou Chi, Qingxi Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9798350325485

Synthetic aperture radar (SAR) image registration is widely used in integrated navigation system with development of guidance system in sensors and other applications. However, there exists some difficulty because of the quality and imaginary principle of SAR images. In this article, a brand-new method based on feature points using improved CSP-DenseNet is proposed to solve the problems of SAR image registration with weak and noisy texture. Deep features of interest points in SAR images are extracted using the proposed network from the crops of search image and template image respectively. The method has an advantage of preserving abundant feature information in SAR images under the influence of insufficient image information and noise of SAR images. The CSP-DenseNet architecture has a cross-stage construction optimizing fused by CSP-Net and DenseNet to extract matching features. The network is partially connected in specific convolutional layers for feature reusing and computation resources saving. Then, Brute Force Matcher and RANSAC voting are successively applied for a larger number of matching pairs and high-precise matching vertexes. Experimental results on various SAR image matching methods show that the proposed method provides better performance than other approaches compared. © 2023 IEEE.

关键词： Synthetic aperture radar

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Angle Tracking control Strategy for Steering-by-Wire system with Dual Steering Actuator Motors 41

Angle Tracking Control Strategy for Steering-by-Wire System ...

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第41届中国控制会议

作者： Xuhang Zhang Linhui Zhao Guohuang Ji Zhiyuan Liu Department of Control Science and Engineering Harbin Institute of Technology Intelligent Power System Co. Ltd.

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Steering-by-wire(SBW) is a key technology to realize angle tracking for autonomous vehicles,and it directly affects the performance of active *** reliability performance of SBW system can be greatly improved by adopting dual motor steering ***,the dual-motor SBW vehicle often loses its stability due to the external interference,and the asynchronous response between the dual steering actuator motors will further deteriorate the stability of the *** purpose of this paper is to establish a method of angle tracking for the dual-motor steering by wire ***,the model of SB W was established and its validity was proofed by comparing the steering performance between the SBW and the traditional mechanical steering ***,by considering parameters uncertainties and difference of wheel load torque of the dual steering actuator motors,the steering angle tracking control strategy of dual motor SBW was *** paper established methods for the synchronization control of dual motor and closed-loop control of angle *** the angle synchronization error was decreased by current compensation *** validation results show that the proposed control strategy can decrease the synchronization error of dual motor and ensure the reliability of angle tracking.

关键词： Steering-by-wire Dual-motor Angle tracking Synchronization control

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Dynamic Event-Triggered Fixed-Time Consensus Analysis of Multi-Agent systems Under Input Delays and Switching Topologies 3

Dynamic Event-Triggered Fixed-Time Consensus Analysis of Mul...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Zhang, Yu Li, Yajing Ran, Guangtao Yu, Hao Ma, Guangfu Department of Automation Shenzhen518055 China Shanghai Institute of Aerospace System Engineering Shanghai200241 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9798331540319

This paper proposes a dynamic event-triggered control method for first-order multi-agent systems with input delays and disturbances under switching topologies. The controller design and its properties of dynamic event-triggered fixed-time consensus are presented in detail. Furthermore, agents can achieve consensus in a fixed time for any initial conditions and topologies that comply with the control protocol. Zeno behavior is avoided. Simulation examples demonstrate the effectiveness of the proposed algorithm and simulate scenarios in which the communication environment deteriorates due to external disturbances affecting the MASs. © 2024 IEEE.

关键词： Multi agent systems

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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A Method for Marine Ship Formation Intention Recognition based on BiConvLSTM-Attention 3

A Method for Marine Ship Formation Intention Recognition bas...

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3rd International Conference on Electronic Information engineering and Computer science, EIECS 2023

作者： Xi, Yunqiao Zhang, Junping Liu, Jian Wang, Linlin Xu, Hongfeng Chen, Linxiu Jiang, Jixiang Harbin Institute of Technology School of Electronics and Information Engineering Harbin China Institute of Electrical and Mechanical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316674

To solve the problem that current dynamic intention recognition methods fail to make full use of time domain variation information between multi-temporal group targets, which leads to low accuracy of intention recognition. This paper proposes a bidirectional convolutional long short term memory-attention network for marine formation target intention recognition. The network takes the multi-source trajectory data of the marine ship formation target as the input, extracts and uses the target change rule and time domain characteristics of the Marine formation data, and trains the model to have the ability to independently learn the weight of information in different time periods. The simulation results show that the method has good performance and can meet the needs of practical application. © 2023 IEEE.

关键词： intention recognition long short-term marinship formation temporal features

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