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Performance Analysis of a Hexagon Rolling Mechanism with Single Degree of Freedom

Journal of Mechanisms and Robotics 2025年第8期17卷 081001页

作者： Zhang, Qianqian Li, Yezhuo Yan, Shaoze Yao, Yan-An Department of Mechanical Engineering Tsinghua University Beijing100084 China School of Mechanical Electronic and Control Engineering Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control Technology Beijing Jiaotong University Beijing100044 China

This article presents a comprehensive performance analysis of the step-climbing and passive rolling modes of a hexagon rolling mechanism with single-degree-of-freedom, based on its structural characteristics and the constraints of centroid stability. First, a step-climbing model, incorporating motion parameters and support distance parameters, is established by leveraging the symmetrical posture movement characteristics of the hexagon rolling mechanism. Building on this foundation, the impact of each parameter on the mechanism's step-climbing ability is thoroughly analyzed, and the maximum height achievable during step climbing is also examined. Subsequently, the existence and sufficient conditions for the hexagon rolling mechanism to achieve passive rolling are analyzed using the centroid fluctuation curve and its slope curves. The analysis results indicate that, due to its unique coupling structure design, the hexagon rolling mechanism possesses a passive rolling capability that is not available in conventional planar linkage mechanisms. Finally, the correctness of the theoretical model is validated through both simulation and prototype experiments. Copyright © 2025 by ASME.

关键词： Degrees of freedom (mechanics)

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Design and Performance Analysis of HMDV Dynamic Inertial Suspension Based on Active Disturbance Rejection control

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Computer Modeling in engineering & Sciences 2024年第8期140卷 1485-1506页

作者： Xiaofeng Yang Wei Wang Yujie Shen Changning Liu Tianyi Zhang School of Automotive and Traffic Engineering Jiangsu UniversityZhenjiang212013China Automotive Engineering Research Institute Jiangsu UniversityZhenjiang212013China Chongqing Key Laboratory of Urban Rail Transit System Integration and Control Chongqing400074China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan universityChangsha410082China

This paper addresses the impact of vertical vibration negative effects,unbalanced radial forces generated by the static eccentricity of the hub motor,and road excitation on the suspension performance of Hub Motor Driven vehicle(HMDV).A dynamic inertial suspension based on Active Disturbance Rejection control(ADRC)is proposed,combining the vertical dynamic characteristics of dynamic inertial suspension with the features of ADRC,which distinguishes between internal and external disturbances and arranges the transition ***,a simulation model of the static eccentricity of the hub motor is established to simulate the unbalanced radial electromagnetic force generated under static eccentricity.A quarter-vehicle model of an HMDV with a controllable dynamic inertial suspension is then ***,the passive suspension model is studied under different grades of road excitation,and the impact mechanism of suspension performance at speeds of 0–20 m/s is ***,the three main components within the ADRC controller are designed for the second-order controlled system,and optimization algorithms are used to optimize its internal ***,the performance of the traditional passive suspension,the PID-based controllable dynamic inertial suspension,and the ADRC-based controllable dynamic inertial suspension are analyzed under different road *** results show that,under sinusoidal road input,the ADRC-based controllable dynamic inertial suspension exhibits a 52.3%reduction in the low-frequency resonance peak in the vehicle body acceleration gain diagram compared to the traditional passive suspension,with significant performance optimization in the high-frequency *** random road input,the ADRC-based controllable dynamic inertial suspension achieves a 29.53%reduction in the root mean square value of vehicle body acceleration and a 14.87%reduction in dynamic tire *** indicates that the designed controllable dynamic inertia

关键词： HMDV static eccentricity ADRC dynamic inertial suspension road excitation

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Sigma-Mixed Unscented Kalman Filter-Based Fault Detection for Traction systems in High-Speed Trains

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Chinese Journal of Electronics 2023年第5期32卷 982-991页

作者： CHENG Chao WANG Weijun MENG Xiangxi SHAO Haidong CHEN Hongtian Department of Computer Science and Technology Changchun University of Technology Department of Mathematics and Statistics Changchun University of Technology Institute of System Research China Industrial Control Systems Cyber Emergency Response Team Department of Mechanical and Vehicle Engineering Hunan University Department of Chemical and Materials Engineering University of Alberta

Fault detection(FD) for traction systems is one of the active topics in the railway and academia because it is the initial step for the running reliability and safety of high-speed trains. Heterogeneity of data and complexity of systems have brought new challenges to the traditional FD methods. For addressing these challenges, this paper designs an FD algorithm based on the improved unscented Kalman filter(UKF) with consideration of performance degradation. It is derived by incorporating a degradation process into the state-space *** network topology of traction systems is taken into consideration for improving the performance of state estimation. We first obtain the mixture distribution by the mixture of sigma points in UKF. Then, the Lévy process with jump points is introduced to construct the degradation model. Finally, the moving average interstate standard deviation(MAISD) is designed for detecting *** the proposed methods via a traction systems in a certain type of trains obtains satisfactory results.

关键词： Degradation Network topology Fault detection Rail transportation State-space methods Safety Kalman filters

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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Robotic mobile and mirror milling of large-scale complex structures

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National Science Review 2023年第5期10卷 10-13页

作者： Zenghui Xie Fugui Xie Limin Zhu Xin-Jun Liu State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical Engineering(DME) Tsinghua University Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control Tsinghua University State Key Laboratory of Mechanical System and Vibration School of Mechanical EngineeringShanghai Jiao Tong University

Large-scale complex structures,such as spacecraft cabins,aircraft composite skins and launch vehicle fuel tanks,are the core components of the equipment in aerospace,energy,shipbuilding and other *** milling quality and efficiency are factors directly affecting the performance and productivity of spacecraft,aircraft and other key *** kind of structure generally features large dimension,high accuracy,

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Research on fatigue evaluation method of high-speed train axle based on axle box acceleration

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High-Speed Railway 2023年第4期1卷 233-240页

作者： Wenjing Wang Yiming Zeng Ruiguo Yan Yiyue Chen Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control TechnologyMinistry of EducationBeijing Jiaotong UniversityBeijing 100044China Department of Engineering Mechanics Tsinghua UniversityBeijing 100084China

As a key safety component of the high-speed train, fatigue fracture of the axle would lead to major accidents such as derailment or overturning. The complexity of the axle dynamic stress test seriously enhances the difficulty of axle fatigue damage analysis. In this paper, the dynamic stress test of the high-speed train axle was carried out,the axle box acceleration was monitored on-track during the test, and the relationship between the axle stress spectrum and acceleration was analyzed on-track. The results show that the relationships between the axle equivalent stresses and the Root Mean Square(RMS) values of the axle box vertical acceleration and lateral acceleration exhibit a strong joint probability density distribution. The concept of the virtual surface density of wheel-rail contact is also proposed to realize the purpose of using axle box acceleration to deduce axle equivalent force. The results quantify the relationship between axle box acceleration and axle equivalent force, provide a new method for predicting the axle damage using the acceleration RMS values, and open up a new approach for structural health monitoring of high-speed train axles.

关键词： High-speed train axles Axle-box acceleration Dynamic stress of wheelset axle Fatigue damage Wheel-rail contact virtual surface density

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Broadband Optical Nonlinearities and Ultrafast Carrier Dynamics of GO-CuS Hybrid Film

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Journal of Lightwave Technology 2025年第11期43卷 5381-5389页

作者： Zhang, Xuefeng Bai, Xuli Liu, Xiaofei Wang, Dan Han, Hong Xiao, Zhengguo Zhang, Jianguo Nie, Zhongquan Taiyuan University of Technology College of Materials Science and Engineering Institute of New Carbon Materials Taiyuan030024 China Taiyuan University of Technology Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan030024 China Taiyuan Institute of Technology Department of Science Taiyuan030008 China Tongren University Department of Physics and Electronic Engineering Tongren China National University of Defense Technology College of Advanced Interdisciplinary Studies Changsha410073 China

We report the broadband optical nonlinearities and ultrafast carrier dynamics of GO doped with CuS nanoparticles (GO-CuS) following the femtosecond pulse lasers. Both the pure GO and GO-CuS hybrid films are first synthesized by the vacuum filter deposition method and their optical nonlinearities are then examined in the wide wavelength range (400 nm-1064 nm) based on the femtosecond Z-scan technique. The results reveal that, compared to the pristine GO, the introduction of CuS not only makes the GO-CuS hybrid film switched from saturated absorption to reverse saturated absorption possible, but also achieves strong broadband optical nonlinear absorption responses and optical limiting effects. It is demonstrated that the strongest nonlinear absorption coefficient (∼3.6×10-7 m/W) appears at 400 nm excitation, which is dozens of times larger than that under the illumination of 1064 nm. By leveraging the femtosecond pump-probe technique, we further study the ultrafast carrier dynamics of the GO-CuS hybrid film carrying the fast and slow relaxation processes. Moreover, the physical mechanisms behind these excellent nonlinear optical responses are elucidated. The findings presented here indicate that the GO-CuS hybrid film can be regarded as a potential promising candidate in various ultrafast photonics devices. © 1983-2012 IEEE.

关键词： Femtosecond lasers

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A generative deep learning framework for inverse design of compositionally complex bulk metallic glasses

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npj Computational Materials 2023年第1期9卷 2196-2203页

作者： Ziqing Zhou Yinghui Shang Xiaodi Liu Yong Yang Department of Mechanical Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongChina City University of Hong Kong(Dongguan) 523000 DongguanChina College of Mechatronics and Control Engineering Shenzhen University518060 ShenzhenChina Department of Materials Science and Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongChina Department of Advanced Design and System Engineering College of EngineeringCity University of Hong KongKowloon TongKowloonHong KongChina

The design of bulk metallic glasses(BMGs)via machine learning(ML)has been a topic of active research ***,the prior ML models were mostly built upon supervised learning algorithms with human inputs to navigate the high dimensional compositional space,which becomes inefficient with the increasing compositional complexity in ***,we develop a generative deep-learning framework to directly generate compositionally complex BMGs,such as high entropy *** framework is built on the unsupervised Generative Adversarial Network(GAN)algorithm for data generation and the supervised Boosted Trees algorithm for data *** studied systematically the confounding effect of various data descriptors and the literature data on the effectiveness of our framework both numerically and *** importantly,we demonstrate that our generative deep learning framework is capable of producing composition-property mappings,therefore paving the way for the inverse design of BMGs.

关键词： inverse metallic entropy

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RGB-Based Category-Level Object Pose Estimation via Depth Recovery and Adaptive Refinement

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IEEE Robotics and Automation Letters 2025年第6期10卷 5377-5384页

作者： Yang, Hui Sun, Wei Liu, Jian Zheng, Jin Zeng, Zhiwen Mian, Ajmal Hunan University National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering Changsha410082 China Hunan University State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha410082 China Central South University School of Architecture and Art Changsha410082 China University of Western Australia Department of Computer Science and Software Engineering CrawleyWA6009 Australia

Category-level pose estimation methods have received widespread attention as they can be generalized to intra-class unseen objects. Although RGB-D-based category-level methods have made significant progress, reliance on depth image limits practical application. RGB-based methods offer a more practical and cost-effective solution. However, current RGB-based methods struggle with object geometry perception, leading to inaccurate pose estimation. We propose depth recovery and adaptive refinement for category-level object pose estimation from a single RGB image. We leverage DINOv2 to reconstruct the coarse scene-level depth from the input RGB image and propose an adaptive refinement network based on an encoder-decoder architecture to dynamically improve the predicted coarse depth and reduce its gap from the ground truth. We introduce a 2D–3D consistency loss to ensure correspondence between the point cloud obtained from depth projection and the objects in the 2D image. This consistency supervision enables the model to maintain alignment between the depth image and the point cloud. Finally, we extract features from the refined point cloud and feed them into two confidence-aware rotation regression branches and a translation and size prediction residual branch for end-to-end training. Decoupling the rotation matrix provides a more direct representation, which facilitates parameter optimization and gradient propagation. Extensive experiments on the REAL275 and CAMERA25 datasets demonstrate the superior performance of our method. Real-world estimation and robotic grasping experiments demonstrate our model robustness to occlusion, clutter environments, and low-textured objects. Our code and robotic grasping video are available at DA-Pose. © 2016 IEEE.

关键词： Depth perception

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A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials

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International Journal of Extreme Manufacturing 2023年第3期5卷 620-644页

作者： Chunlei He Jiwang Yan Shuqi Wang Shuo Zhang Guang Chen Chengzu Ren Tianjin Key Laboratory of Equipment Design and Manufacturing Technology Department of Mechanical EngineeringTianjin UniversityTianjin 30054People’s Republic of China Department of Mechanical Engineering Keio UniversityYokohama 223-8522Japan Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384People’s Republic of China School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004People’s Republic of China

Polycrystalline materials are extensively employed in *** surface roughness significantly affects the working *** defects,particularly grain boundaries,have a great impact on the achieved surface roughness of polycrystalline ***,it is difficult to establish a purely theoretical model for surface roughness with consideration of the grain boundary effect using conventional analytical *** this work,a theoretical and deep learning hybrid model for predicting the surface roughness of diamond-turned polycrystalline materials is *** kinematic–dynamic roughness component in relation to the tool profile duplication effect,work material plastic side flow,relative vibration between the diamond tool and workpiece,etc,is theoretically *** material-defect roughness component is modeled with a cascade forward neural *** the neural network,the ratio of maximum undeformed chip thickness to cutting edge radius RT S,work material properties(misorientation angle θ_(g) and grain size d_(g)),and spindle rotation speed n s are configured as input *** material-defect roughness component is set as the output *** validate the developed model,polycrystalline copper with a gradient distribution of grains prepared by friction stir processing is machined with various processing parameters and different diamond *** with the previously developed model,obvious improvement in the prediction accuracy is observed with this hybrid prediction *** on this model,the influences of different factors on the surface roughness of polycrystalline materials are *** influencing mechanism of the misorientation angle and grain size is quantitatively *** fracture modes,including transcrystalline and intercrystalline fractures at different RTS values,are ***,optimal processing parameters are obtained with a simulated annealing *** experiments are performed with

关键词： diamond turning material-defect roughness component polycrystalline copper neural network simulated annealing algorithm

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