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IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Li, Sijie Wu, Zhengxing Wang, Jian Feng, Yukai Tan, Min Yu, Junzhi School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing China

In nature, the bottlenose dolphin employs a prevalent intermittent-flapping behavioral strategy to enhance swimming efficiency during long-distance journeys. Taking inspiration from this natural mechanism, a newly-designed bioinspired underwater vehicle (BUV) based on dorsoventral propulsion is developed to investigate the specific intermittent-propulsion mode. First, a BUV prototype is designed, incorporating morphological characteristics resembling those of adult bottlenose dolphins, which features robust sensing capabilities, redundant actuation surfaces, and a passive peduncle joint for mitigation of the head-nodding motion. Second, a dynamic model for assessing the intermittent propulsion's cost of transport and velocity in a balanced perspective is established. In-depth investigations are conducted to analyze the impact of parameters in the intermittent-propulsion mode under varying flapping and gliding drag coefficients, which offer a novel and reasonable explanation for the exceptional duty cycle observed in bottlenose dolphins by biologists. Finally, numerous aquatic experiments are conducted to validate the remarkable energy-saving advantages of the proposed intermittent-propulsion mode of the BUV. These results present a new solution for efficient and sustainable long-distance navigation of BUVs, highlighting their potential for effective marine exploration. IEEE

关键词： Secondary batteries

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Atomically thin MoS_(2)with ultra-low friction properties based on strong interface interaction

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Friction 2025年第4期13卷 139-148页

作者： Xinjian He Tongtong Yu Zishuai Wu Changhe Du Haoyu Deng Yongkang Zhao Shuang Li Yange Feng Liqiang Zhang Zhinan Zhang Daoai Wang State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of SciencesLanzhou 730000China Center of Materials Science and Optoelectronics Engineering University of ChineseAcademy of SciencesBeijing 100049China Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai Yantai 265503China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China Qingdao Center of Resource Chemistry and New Materials Qingdao 266100China

Atomically thin lubrication materials with anti-friction properties are crucial for reducing energy consumption and extending the servicelifeofmicro/nanoelectromechanical systems(MEMS/NEMS).However,achieving atomically thin films with ultra-low friction properties at the atomic/nanoscale even at the micrometer scale presents significant *** this study,large-size and high-quality monolayer MoS_(2)(ML MoS_(2))was grown on SiO2/Si substrate by chemical vapor deposition(CVD)*** with mechanically exfoliated ML MoS_(2),the CVD-grown ML MoS,(CVD-MoS_(2))exhibits an ultra-lower friction coefficient(0.00904).Based on the stick-slip effect and Prandtl-Tomlinson(P-T)model,the reduction of puckering effect indicates stronger interaction and lower interface potential barrier in tip,CVD-MoS_(2),and SiO,/Si substrate ***,combining with the density functional theory calculations,the stronger interface adhesion and higher overall charge redistribution degree of CVD-MoS_(2)can also be used to explain its ultralow friction *** work will provide theoretical guidance for designing ultra-thin lubricating materials with ultra-low friction properties.

关键词： chemical vapor deposition(CVD) MoS_(2) ultra-thin ultra-low friction interface interaction

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ROS2 Real-time Performance Optimization and Evaluation

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Chinese Journal of Mechanical engineering 2023年第6期36卷 36-50页

作者： Yanlei Ye Zhenguo Nie Xinjun Liu Fugui Xie Zihao Li Peng Li State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China Beijing Key Lab of Precision/Ultra-Precision Manufacturing Equipments and Control Tsinghua UniversityBeijing 100084China

Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion *** ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are *** ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application *** ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux ***,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time *** achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and *** real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT *** paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 *** comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.

关键词： ROS Real-time system optimization Preempt_RT Real-time performance evaluation of ROS2

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MSC-APFNN: Fault Diagnosis Deep Transfer Network for Rotating Machine based on Multi-scale Convolutional Extraction and Adaptive Pruning Fuzzy Inference system

MSC-APFNN: Fault Diagnosis Deep Transfer Network for Rotatin...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Zhou, Yanrun Lei, Zihao Wen, Guangrui Su, Yu Zhang, Zhifen National Key Lab of Aerospace Power System and Plasma Technology Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Xi’an710049 China Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an710049 China

ISBN: (纸本)9789819639687

Intelligent fault diagnosis on mechanical transmission system of the train is of great importance to ensure the efficient operation of high-speed trains. However, due to the complex and changeable operation conditions (OCs), it is difficult to ensure the uniformity of the data distribution obtained by real-time acquisition, which sets a higher standard for the design of intelligent algorithms. Empowered by deep transfer learning (DTL) methods, the fuzzy inference system provides an effective solution to the abovementioned problem. In this paper, an Adaptive Pruning Fuzzy Inference system (APFIS) is proposed predicated on the fuzzy theory and the basic structure of fuzzy neural network, along with the hybrid model MSC-APFNN constructed by combining the multi-scale convolutional network with the proposed APFIS. This model can be employed as a backbone for the application to transfer diagnostic detection of rotating systems based on adversarial networks. Experimental results demonstrate that the proposed model achieves excellent diagnostic results under variable operating conditions, which provide a novel insight into the optimization of the traditional convolutional and fully-connected deep network structure and offer a promising avenue for the research of fuzzy decision-making in the context of fault diagnostics for high-speed trains. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Fuzzy neural networks

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Thermal management for thermoset automated fiber placement based on infrared heater structure arrangement

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Chinese Journal of Aeronautics 2022年第1期35卷 173-183页

作者： Han WANG Weiwei WANG Haijin WANG Huiyue DONG Yinglin KE A State Key Laboratory of Fluid Power and Mechatronic System School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China

Layup temperature is a vital factor that affects the production quality of automated fiber placement for thermoset *** high quality production,this paper proposes a new prediction model of layup temperature by considering the structure of infrared heater of automatic fiber placement *** model was first verified by comparing with the temperature results of layup *** a prediction on the effects of heater structure arrangement on layup temperature was conducted in the *** research shows that the length of infrared tube and the radian of reflective-film have significant influences,rather than other *** to this investigation,a heater structure-based heating strategy was presented in the paper to efficiently achieve constant temperature control in variable speed layup process.

关键词： Automated fiber placement Heating strategy optimization Infrared heater structure Thermal management Variable speed

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Preparation,Mechanical and Biological Properties of Inkjet Printed Alginate/Gelatin Hydrogel

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Journal of Bionic engineering 2021年第3期18卷 574-583页

作者： Tian Jiao Qin Lian Tingze Zhao Huichao Wang Dichen Li State Key Laboratory for Manufacturing System Engineering Xi'an Jiaotong UniversityXi'an 710049China

3D printing has made remarkable progress in soft tissue reconstruction enabling the custom design of complex material implants with patient specific *** aim of this study was to inkjet print mechanically reinforced biocompatible ***,we developed a double crosslinked ink by optimizing the rheological properties of solutions of sodium alginate(NaAlg),NaAlg/transglutaminase(TG),CaCl_(2)and gelatin/CaCl_(2).The results showed that a two-component ink system comprising NaAlg(4%w/v)/TG(0.8%w/v)and gelatin(4%w/v)/CaCl_(2)(3%w/v)gave optimum *** mechanical and biological properties of printed alginate/gelatin hydrogels prepared from inks with different gelatin contents,and incorporated fibroblasts,were characterized by Scanning Electron Microscope(SEM),mechanical testing and laser confocal *** compressive moduli of alginate/gelatin hydrogels could be adjusted from 19.2 kPa±1.2 kPa to 65.9 kPa±3.3 kPa by increasing the content of *** incubation for 7 d,fibroblasts had permeated all printed hydrogels and the rate of proliferation increased with increasing gelatin *** highest cell proliferation rate(497%)was obtained in a hydrogel containing 4.5%(w/v)*** study offers a new strategy for the fabrication of 3D structures used to mimic the function of native tissues.

关键词： biofabrication inkjet printing double crosslinking ink mechanical and biological properties hydrogel preparation

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Remaining useful life prediction for train bearing based on an ILSTM network with adaptive hyperparameter optimization

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Transportation Safety and Environment 2024年第2期6卷 75-86页

作者： Deqiang He Jingren Yan Zhenzhen Jin Xueyan Zou Sheng Shan Zaiyu Xiang Jian Miao State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures Guangxi Key Laboratory of Manufacturing System&Advanced Manufacturing Tec hnologySc hool of Mec hanical EngineeringGuangxi Univ ersityNanning 530004GuangxiChina Zhuzhou CRRC Times Electric Co. Ltd.Zhuzhou 412001HunanChina

Remaining useful life(RUL)prediction for bearing is a significant part of the maintenance of urban rail transit *** RUL is closely linked to the reliability and safety of train running,but the current prediction accuracy makes it difficult to meet the re-quirements of high reliability *** at the problem,a prediction model based on an improved long short-term memory(ILSTM)network is ***,the variational mode decomposition is used to process the signal,the intrinsic mode function with stronger representation ability is determined according to energy entropy and the degradation feature data is constructed com-bined with the time domain ***,to improve learning ability,a rectified linear unit(ReLU)is applied to activate a fully connected layer lying after the long short-term memory(LSTM)network,and the hidden state outputs of the layer are weighted by attention *** Harris Hawks optimization algorithm is introduced to adaptively set the hyperparameters to improve the performance of the ***,the ILSTM is applied to predict bearing *** experimental cases,the better perfor-mance in bearing RUL prediction and the effectiveness of each improving measures of the model are validated,and its superiority of hyperparameters setting is demonstrated.

关键词： train bearing remaining useful life prediction long short-term memory(LSTM) attention mechanism Harris Hawks op-timization(HHO)

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Deep learning-based multi-source precipitation merging for the Tibetan Plateau

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Science China Earth Sciences 2023年第4期66卷 852-870页

作者： Tianyi NAN Jie CHEN Zhiwei DING Wei LI Hua CHEN State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhan 430072China Hubei Provincial Key Lab of Water System Science for Sponge City Construction Wuhan UniversityWuhan 430072China

Due to its complex and diverse terrain, precipitation gauges in the Tibetan Plateau(TP) are sparse, making it difficult to obtain reliable precipitation data for environmental studies. Data merging is a method that can integrate precipitation data from multiple sources to generate high-precision precipitation data. However, the more commonly used methods, such as regression and machine learning, do not usually consider the local correlation of precipitation, so that the spatial pattern of precipitation cannot be reproduced, while deep learning methods do incorporate spatial correlation. To explore the ability of using deep learning methods in merging precipitation data for the TP, this study compared three methods: a deep learning method—a convolutional neural network(CNN) algorithm, a machine learning method—an artificial neural network(ANN) algorithm, and a statistical method based on Extended Triple Collocation(ETC) in merging precipitation from multiple sources(gauged, grid,satellite and dynamic downscaling) over the TP, as well as their performance for hydrological simulations. Dynamic downscaling data driven by global reanalysis data centered on the TP were introduced in the merging process to better reflect the spatial variability of precipitation. The results show that:(1) in terms of the meteorological metrics, the merged data perform better than the gauge interpolation data. By using data merging, the error between the raw multi-source and gauged precipitation can be reduced, and the precipitation detection capability can be greatly improved;(2) The merged precipitation data also perform well in the hydrological evaluation. The Xin’anjiang(XAJ) model parameter calibration experiments at the source of the Yangtze River(SYR) and the source of the Yellow River(SHR) were repeated 300 times to remove uncertainty in the model parameter results. The median Kling-Gupta Efficiency Coefficients(KGE) of simulated runoff from the merged data of the ANN, CNN and ETC me

关键词： Tibetan Plateau Precipitation data merging Deep learning Dynamic downscaling

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Building stabilized Cu_(0.17)Mn_(0.03)V_(2)O_(5−□)·2.16H_(2)O cathode enables an outstanding room‐/low‐temperature aqueous Zn‐ion batteries

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Carbon Energy 2024年第8期6卷 25-35页

作者： Ao Wang Dai‐Huo Liu Lin Yang Fang Xu Dan Luo Haozhen Dou Mengqin Song Chunyan Xu Beinuo Zhang Jialin Zheng Zhongwei Chen Zhengyu Bai Key Laboratory of Green Chemical Media and Reactions Ministry of EducationCollaborative Innovation Center of Henan Province for Green Manufacturing of Fine ChemicalsSchool of Chemistry and Chemical EngineeringHenan Normal UniversityXinxiangHenanChina The State Key Laboratory of Catalysis(SKLC) Power Battery and System Research CenterDalian Institute of Chemical PhysicsChinese Academy of SciencesDalianChina

Vanadium oxide cathode materials with stable crystal structure and fast Zn^(2+) storage capabilities are extremely important to achieving outstanding electrochemical performance in aqueous zinc‐ion *** this work,a one‐step hydrothermal method was used to manipulate the bimetallic ion intercalation into the interlayer of vanadium *** pre‐intercalated Cu ions act as pillars to pin the vanadium oxide(V‐O)layers,establishing stabilized two‐dimensional channels for fast Zn^(2+) *** occupation of Mn ions between V‐O interlayer further expands the layer spacing and increases the concentration of oxygen defects(Od),which boosts the Zn^(2+) diffusion *** a result,as‐prepared Cu_(0.17)Mn_(0.03)V_(2)O_(5−□)·2.16H_(2)O cathode shows outstanding Zn‐storage capabilities under room‐and lowtemperature environments(e.g.,440.3 mAh g^(−1) at room temperature and 294.3 mAh g^(−1)at−60°C).Importantly,it shows a long cycling life and high capacity retention of 93.4%over 2500 cycles at 2 A g^(−1) at−60°***,the reversible intercalation chemistry mechanisms during discharging/charging processes were revealed via operando X‐ray powder diffraction and ex situ Raman *** strategy of a couple of 3d transition metal doping provides a solution for the development of superior room‐/lowtemperature vanadium‐based cathode materials.

关键词： aqueous zinc‐ion batteries Cu_(0.17)Mn_(0.03)V_(2)O_(5−□)·2.16H_(2)O oxygen defects room‐/lowtemperature performance stabilized nanostructure

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Bug localization based on syntactical and semantic information of source code

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Journal of systems engineering and Electronics 2023年第1期34卷 236-246页

作者： YAN Xuefeng CHENG Shasha GUO Liqin College of Computer Science Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 211106China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China

The existing software bug localization models treat the source file as natural language, which leads to the loss of syntactical and structure information of the source file. A bug localization model based on syntactical and semantic information of source code is proposed. Firstly, abstract syntax tree(AST) is divided based on node category to obtain statement sequence. The statement tree is encoded into vectors to capture lexical and syntactical knowledge at the statement ***, the source code is transformed into vector representation by the sequence naturalness of the statement. Therefore,the problem of gradient vanishing and explosion caused by a large AST size is obviated when using AST to the represent source code. Finally, the correlation between bug reports and source files are comprehensively analyzed from three aspects of syntax, semantics and text to locate the buggy code. Experiments show that compared with other standard models, the proposed model improves the performance of bug localization, and it has good advantages in mean reciprocal rank(MRR), mean average precision(MAP) and Top N Rank.

关键词： bug report abstract syntax tree code representation software bug localization

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