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2024 3rd International Conference on Aerospace, Aerodynamics and Mechatronics Engineering, AAME 2024

作者： Chen, Chen Zhou, Lilin Ye, Tianyu Li, Daokui College of Aerospace Science and Engineering National University of Defense Technology Hunan Changsha410073 China Hunan Key Laboratory of Intelligent Planning and Simulation for Aerospace Missions Hunan Changsha410073 China Aviation Engineering Institute Civil Aviation Flight University of China Sichuan Guanghan618307 China

Axially functionally graded (AFG) carbon nanotube-reinforced composite (CNTRC) emerges as a promising solution for tailoring the stiffness and strength of various beam-like structures. Applications range from optimizing the weight-to-strength ratio of airplane wings to fine-tuning the frequency of micro-beam sensors, and even alleviating stresses induced by centrifugal forces or temperature gradients in turbine blades. However, the challenge of solving variable coefficient partial differential equations (VCPDEs) arising from the axial material gradient limits conventional methods to numerical and simulation techniques. In this study, a novel perturbation approach (PA) customized for AFG-CNTRC is highlighted for solving the problem analytically, simply, and precisely. First, the vibration model of an AFG-CNTRC beam is established according to the Euler-Bernoulli theory (EBT). Second, the vibration governing equations are solved by the PA and the state space method (SSM) analytically. Finally, the adaptivity and accuracy of the PA are validated and the effects of carbon nanotubes (CNTs) distribution patterns are analyzed. It is found that increasing CNT content at either end will increase the natural frequency for symmetric boundary conditions (BCs). The frequency decreases with the degree of nonlinearity distribution of CNTs. The frequency under the C-F BC exhibits low sensitivity to parameter effects. © Published under licence by IOP Publishing Ltd.

关键词： State space methods

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Investigation of Noise Sources and Radiated Sound Power of Civil Transport Aircraft 24

Investigation of Noise Sources and Radiated Sound Power of C...

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24th International Congress on Acoustics, ICA 2022

作者： Song, Yahui Hou, Hong Yue, Shu Zhao, Yuanming Fan, Gaoyu Institute of Aircraft Flight Test Technology Chinese Flight Test Establishment Xi'an710089 China Key Laboratory of Ocean Acoustics and Sensing Ministry of Industry and Information Technology School of Marine Science and Technology Northwestern Polytechnical University Xi'an710072 China

In order to evaluate a large civil transport category aircraft noise accurately and scientifically, a series of field experiments have been carried out to identify the main noise sources and estimate their radiated sound power. A126-element logarithmic spiral microphone array is optimized to improve the sound source recognition performance. The Doppler effect of the received signal of microphone array elements is eliminated by interpolating the de-dopplerisation. The main airframe and engine noise sources are identified by beamforming algorithm, and the radiated sound power is estimated by sound intensity scaling method. The spectral characteristics analysis and quantitative separation of the main noise sources of the aircraft are implemented. The sound power estimation results of the identified engine noise source are in good agreement with the working state parameters of the engines, which verifies that the sound intensity scaling method is reliable. The flight test results show that the designed microphone array and the beamforming algorithm is well suited to assess main noise sources of the civil aircraft flyover status. These noise sources identification results provide valuable information for the further noise reduction design of the aircraft. © ICA *** rights reserved

关键词： Beamforming Noise Source Identification Sound Power Estimation

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Facile Preparation of Fe-N-C Oxygen Reduction Electrocatalysts from Metal Organic Frameworks for Zn-Air Battery

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Journal of Renewable Materials 2022年第5期10卷 1337-1348页

作者： Chengcheng Wang Dawei Luo Bingxue Hou Mortaza Gholizadeh Zanxiong Tan Xiaojie Han Shenzhen Polytechnic ShenzhenChina Key Laboratory of Energy Conversion and Storage Technologies(Southern University of Science and Technology) Ministry of Education ShenzhenShenzhenChina Aviation Engineering Institute Civil Aviation Flight University of ChinaGuanghanChina Faculty of Chemical and Petroleum Engineering University of TabrizTabrizIran

It is critical to study efficient,stable oxygen reduction reaction(ORR)electrocatalysts due to insufficient stability and expensive price of Pt/C catalysts for Zn-air ***–N–C electrocatalysts was synthesized by a facile solvent-green method and the efficiency of Fe–N–C optimized was studied as potential ORR electrocatalysts under alkaline *** indicated that it had excellent ORR activity with E_(1/2)of 0.93 V,which was competitive to that of Pt/C-JM under the same ***,the assembled Zn-air battery exhibited discharge potential and charge potential of 1.2 V,2.32 V at 5 mA cm^(−2)with high stability,***,all results illustrated that Fe–N–C is an excellent ORR electrocatalyst in the field of metal air ***,this work opens a good way to synthesize highly efficient electrocatalysts from metal organic framework and to investigate ORR mechanism of efficient chemical energy to electricity conversion.

关键词： Manuscript Fe-N-C electrocatalyst oxygen reduction reaction Zn-air battery

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RASTE: A Relation-Guided Joint Method for Aspect Sentiment Triplet Extraction 19

RASTE: A Relation-Guided Joint Method for Aspect Sentiment T...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Zhong, Linyang Shang, Jiaxing Zheng, Linjiang Hao, Fei Cao, Weiwei Sun, Hong Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society College of Computer Science Chongqing China Shaanxi Normal University School of Computer Science Xian China Civil Aviation Flight University of China Key Laboratory of Flight Techniques and Flight Safety Guanghan China Civil Aviation Flight University of China Flight Technology and Flight Safety Research Base Guanghan China

ISBN: (纸本)9798350346558

Aspect Sentiment Triplet Extraction (ASTE) is an important subtask of aspect-based sentiment analysis. It aims to extract aspect terms, corresponding sentiment polarities and related opinion terms from a sentence. The most advanced research efforts solve this problem in an end-to-end manner. However, they usually use one classifier to handle both relation detection and sentiment polarity classification tasks for aspectopinion pairs, which affects the prediction performance of the classifier. Moreover, the previous works treat subtasks equally, ignoring the differences between subtasks. In this paper, we propose a relation-guided method that models the relation detection and sentiment polarity classification subtasks differently to extract aspect sentiment triplets more effectively. Further, we capture the corresponding contextual features for each subtask separately to improve the overall performance of the model. We conducted experiments on two group benchmark datasets. Our model turns out to be one of the state-of-the-art models with effectiveness and superiority according to the experimental results. © 2022 IEEE.

关键词： Sentiment analysis

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Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

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Chinese Journal of Aeronautics 2022年第5期35卷 40-52页

作者： Quanbo GE Zhongcheng MA Jinglan LI Qinmin YANG Zhenyu LU Hong LI School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Institute of Systems Science and Control Engineering School of AutomationHangzhou Dianzi UniversityHangzhou 310018China State Key Laboratory of Industrial Control Technology and the College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science and TechnologyNanjing 210044China Chinese Flight Test Establishment Xi’an 710089China

Mobile robots are often subject to multiplicative noise in the target tracking tasks,where the multiplicative measurement noise is correlated with additive measurement *** this paper,first,a correlation multiplicative measurement noise model is *** is able to more accurately represent the measurement error caused by the distance sensor dependence ***,the estimated performance mismatch problem of Cubature Kalman Filter(CKF)under multiplicative noise is *** improved Gaussian filter algorithm is introduced to help obtain the CKF algorithm with correlated multiplicative *** practice,the model parameters are unknown or inaccurate,especially the correlation of noise is difficult to obtain,which can lead to a decrease in filtering accuracy or even *** address this,an adaptive CKF algorithm is further provided to achieve reliable state estimation for the unknown noise correlation coefficient and thus the application of the CKF algorithm is ***,the estimated performance is analyzed theoretically,and the simulation study is conducted to validate the effectiveness of the proposed algorithm.

关键词： Adaptive CKF Correlated noise Estimation accuracy Multiplicative noise Performance analysis Target tracking

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A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1424-1437页

作者： Quanbo Ge Yang Cheng Hong Li Ziyi Ye Yi Zhu Gang Yao School of Automation Nanjing University of Information Science&TechnologyJiangsu Provincial University Key Laboratory of Big Data Analysis and Intelligent SystemsNanjing University of Information Science&Technologyand the Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)Nanjing University of Information Science&TechnologyNanjing 210044China School of Department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China China Classification Society Nantong Office Nantong 226006China Chinese Flight Test Establishment Xi’an 710089China School of Mathematics Tsinghua UniversityBeijing 100084China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China Department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China IEEE

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity *** the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and *** com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

关键词： Curve similarity matching Gaussian-like noise non-parametric scheme parzen window.

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Inter-UAV State Estimation of Swarmed UAVs with Communication Constraints

Inter-UAV State Estimation of Swarmed UAVs with Communicatio...

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International Conference on Guidance, Navigation and Control, ICGNC 2024

作者： Hao, Li Song, Dongliang Yang, Yukun Zuo, Ling Li, Zhiyu Ma, Shichao Wen, Jiayun Hou, Lin Tang, Qiang Aviation Industries Corporation of China (AVIC) Xi’an Flight Automatic Control Research Institute (FACRI) Xi’an 710076 China National Key Laboratory of Science and Technology on Aircraft Control Xi’an 710076 China

ISBN: (纸本)9789819622351

This paper focuses on the inter-UAV state estimation method of swarmed UAVs with communication constraints, which mainly analyzes the incomplete state information and data missing between UAVs. Firstly, the motion state estimation method of UAVs based on extended Kalman filter (EKF) is established for the incomplete state information of UAVs with communication constraints. Secondly, aiming at the data missing between UAVs with limited communication, the state prediction method of UAVs is studied. Finally, the validity of the proposed method was verified by digital simulation experiments and real flight experiments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Communication Constraints State Estimation Swarmed UAVs

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Research on Reward Distribution Mechanism Based on Temporal Attention in Episodic Multi-Agent Reinforcement Learning 6

Research on Reward Distribution Mechanism Based on Temporal ...

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6th Asian Conference on Artificial Intelligence technology, ACAIT 2022

作者： Fang, Baofu Cao, Mingkuan Wang, Zaijun Wang, Hao Hefei University of Technology Intelligent Interconnected Systems Laboratory of Anhui Province School of Computer Science and Information Engineering Hefei China Civil Aviation Flight University of China Key Laboratory of Flight Techniques and Flight Safety Guanghan China

ISBN: (纸本)9781665453110

In episodic multi-agent reinforcement learning, we study how to distribute episodic rewards at the end of an episode by trajectory time steps to obtain high-quality and interpretable learning reward signals to guide agent training. This paper proposes a reward distribution method based on temporal attention. This method is used to characterize the influence of actions on state transitions along the trajectory, and the effect of each influence on the global reward at each time step. This method is combined with a deep deterministic strategy, and a multi-agent algorithm based on the temporal attention reward distribution mechanism is proposed to speed up the convergence speed of the agent. The effectiveness of the algorithm is verified in a multi-agent pursuit environment. Compared with other reward distribution methods, the method in this paper converges faster and obtains higher rewards. © 2022 IEEE.

关键词： Reinforcement learning

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Hierarchical Polyimide Nonwoven Fabric with Ultralow-Reflectivity Electromagnetic Interference Shielding and High-Temperature Resistant Infrared Stealth Performance

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Nano-Micro Letters 2025年第4期17卷 111-129页

作者： Xinwei Tang Yezi Lu Shuangshuang Li Mingyang Zhu Zixuan Wang Yan Li Zaiyin Hu Penglun Zheng Zicheng Wang Tianxi Liu The Key Laboratory of Synthetic and Biological Colloids Ministry of EducationSchool of Chemical and Material EngineeringInternational Joint Research Laboratory for Nano Energy CompositesJiangnan UniversityWuxi 214122JiangsuPeople’s Republic of China Jiangsu Ferrotec Semiconductor Technology Co. Ltd.Yancheng 214000JiangsuPeople’s Republic of China Guizhou Aerospace Wujiang Electro-Mechanical Equipment Co. Ltd.No.20-5Dalian Road Aerospace Industrial ParkHuichuan DistrictZunyi City 563000GuizhouPeople’s Republic of China Civil Aircraft Fire Science and Safety Engineering Key Laboratory of Sichuan Province College of Civil Aviation Safety EngineeringCivil Aviation Flight University of ChinaGuanghan 618307SichuanPeople’s Republic of China

Designing and fabricating a compatible low-reflectivity electromagnetic interference(EMI)shielding/high-temperature resistant infrared stealth material possesses a critical significance in the field of ***,a hierarchical polyimide(PI)nonwoven fabric is fabricated by alkali treatment,in-situ growth of magnetic particles and"self-activated"electroless Ag plating ***,the hierarchical impedance matching can be constructed by systematically assembling Fe_(3)O_(4)/Ag-loaded PI nonwoven fabric(PFA)and pure Ag-coated PI nonwoven fabric(PA),endowing it with an ultralowreflectivity EMI shielding *** addition,thermal insulation of fluffy three-dimensional(3D)space structure in PFA and low infrared emissivity of PA originated from Ag plating bring an excellent infrared stealth *** importantly,the strong bonding interaction between Fe_(3)O_(4),Ag,and PI fiber improves thermal stability in EMI shielding and high-temperature resistant infrared stealth *** excellent comprehensive performance makes it promising for military tents to protect internal equipment from electromagnetic interference stemmed from adjacent equipment and/or enemy,and inhibit external infrared detection.

关键词： Polyimide Electromagnetic interference shielding Low reflectivity Infrared stealth Compatibility

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MFE-Net: A remote sensing image dehazing model for the visual system of a flight simulator 6

MFE-Net: A remote sensing image dehazing model for the visua...

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6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Ge, Wenyi Wang, Bo Liu, Qi Qin, Xiaolin Tan, Shihan Wang, Shengjie Yuan, Xia College of Computer Science Chengdu University of Information Technology Chengdu610255 China Chengdu Institute of Computer Applications Chinese Academy of Sciences Chengdu610213 China Jiuzhou Air Trafic Control Sichuan Jiuzhou Investment Holding GroupCo. Ltd Mianyang621000 China The Key Laboratory of Flight Techniques and Flight Safety Civil Aviation Flight University of China Guanghan618307 China

ISBN: (纸本)9781510688018

Obtaining high-quality remote sensing images is crucial in generating a three-dimensional terrain for flight simulators. However, due to the presence of haze and other impact factors, collected remote sensing images usually suffer from blurred details, which limits its applicability real-world applications. To address this issue a deep learning-based dehazing model is proposed to advance hazy remote sensing images to build flight simulator visual systems. The encoder-decoder architecture is proposed to perform the image dehazing, in which an improved feature extraction module is designed to extract both global and local semantic features across multi-resolutions. In addition, the pixel-pixel and region-region mechanism are innovatively designed to achieve deep mapping relationships and further enhance image dehazing. Experimental results demonstrate that the proposed model outperforms other comparative baselines, achieving high-confidence dehazing in multi-scene remote sensing images, and with good generality and applicability in multi-resolution flight simulators and multi-terrain remote sensing. © 2025 SPIE.

关键词： flight simulators

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