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Real-time traffic enhancement scheduling for train communication networks based on TSN

Journal of Traffic and Transportation Engineering(English Edition) 2025年第1期12卷 34-51页

作者： Deqiang He Zeqian Chen Daliang Sun Zhenzhen Jin Yanjun Chen Rui Ma Chen Liang Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education Guangxi Key Laboratory of Manufacturing System&Advanced Manufacturing TechnologySchool of Mechanical EngineeringGuangxi UniversityNanning530004China

With the increasing data volume of train on-board system,real-time performance has become the most critical factor to ensure the safety of train *** that standard Ethernet cannot meet the real-time requirement of existing train communication network(TCN),the time-sensitive network(TSN)technology for TCN is *** solve the time-delay problem,an adaptive switch queue selection mechanism for traffic scheduling is ***,the topology model of TCN based on TSN and the traffic model are ***,the K shortest path routing algorithm based on load balancing provides the optimal routing for the scheduling ***,the adaptive switch queue selection mechanism is introduced to solve the aggregation flow conflict problem effectively,queue resources are properly allocated,and the gate control list(GCL)of each frame in the queue is *** results show that compared with the traditional constraint model,the schedulability of the model with an adaptive switch queue selection mechanism increases by 33.0%,and the maximum end-to-end delay and network jitter decrease by 19.1%and 18.6%on average *** can provide theoretical support and application reference for the real-time performance optimization of TCN based on TSN.

关键词： Train communication network Time-sensitive network Adaptive switch queue selection mechanism Gate control list Real-time

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Experimental Study on Geometry Characteristics of Turbulent Premixed Flames for Natural Gas/Air Mixtures

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Journal of Thermal Science 2025年第1期34卷 268-282页

作者： ZHENG Weilin WANG Qijiao XIAO Huahua CHEN Xiaoxiao XIE Fan ZENG Wen Liaoning Key Lab of Advanced Test Technology for Aerospace Propulsion System Shenyang Aerospace UniversityShenyang 110136China State Key Laboratory of Fire Science University of science and Technology of ChinaHefei 230027China AVIC Shenyang Aircraft Design and Research Institute Shenyang 110035China

In this study,focusing on the geometry characteristics of spherical expanding flame,the turbulent premixed flames of natural gas/air mixtures were investigated in a fan-stirred turbulent *** effects of initial temperature(T=300-400 K),initial pressure(P=0.1-0.3 MPa),turbulence intensity(u'=1.0-2.7 m/s),oxygen volumetric percentage(φ(O_(2))=15%-21%)and carbon dioxide volumetric percentage(φ(CO_(2))=0-20%)were delved *** flame profile under the Cartesian coordinate system was derived from the schlieren images taken by the high-speed ***,from both macroscopic and microscopic perspectives,the influence of experimental conditions on the flame geometry characteristics was explored through flame front extraction,wavelet decomposition and network *** results demonstrate that for significant flame wrinkling,changes in species concentrations and turbulence intensity have more pronounced effects on the flame wrinkling *** wrinkling of the flame front maintains a certain degree of similarity,as evidenced by the locally concentrated distribution of the angles of the maximum fluctuation *** disturbance energy under large-scale(D6-D8)disturbances exhibits relatively high values with a similar trend,exerting a significant impact on the geometry characteristics of the flame *** peaks of correlation degree are scattered either with the decomposition scale or the development of flame radius,indicating no linear correlation between different detail ***,the probability distribution of node degrees in key wrinkled regions exhibits different trends with that of large-scale wrinkling and disturbance energy,especially with changes in initial *** occurs because the number of key wrinkles varies based on the perturbation's strength or the region's ***,an increase in the fluctuation frequency of the flame's local radius may not necessarily lead to an increase in the number of key folded regions.

关键词： geometry characteristics large-scale wrinkling wavelet decomposition network topology fan-stirred turbulent combustor

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Effect of Free-End Torsion on the Corrosion and Mechanical Properties for Mg-3Zn-0.2Ca Alloy

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Acta Metallurgica Sinica(English Letters) 2025年第1期38卷 59-70页

作者： Li-Lan Gao Jiang Ma Yan-Song Tan Xiao-Hao Sun Qi-Jun Gao De-Bao Liu Chun-Qiu Zhang 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 TechnologyTianjin300384China School of Materials Science and Engineering Tianjin University of TechnologyTianjin300384China

Magnesium alloys with excellent degradability and biocompatibility are promising materials for biomedical implants,saving patients the burden of second ***,their mechanical properties and corrosion resistance are significantly below the requirements for implant *** study aims to improve the mechanical and corrosion resistance properties of Mg-3Zn-0.2Ca alloy by pre-torsion treatment,and find out the optimal shear *** rod-shaped Mg-3Zn-0.2Ca alloy specimens were pre-torsion treated at different torsion *** effect of free-end torsion on Mg-3Zn-0.2Ca alloy was characterized through microstructure analysis,mechanical testing,and corrosion ***-torsion treatment can refine grain and induce twins and dislocations in Mg-3Zn-0.2Ca *** surface hardness increases with the increase in torsion *** yield strength and ultimate strength initially increase and then decrease with increasing torsion angle,while ductility decreases with increasing torsion *** with a shear strain of 30%exhibit the highest tensile strength,reaching 284.78±10.62 MPa,with an elongation of 19.37±1.66%.Furthermore,they show a significant improvement in fatigue lives both before and after *** the stress amplitude is 120 MPa,the fatigue lives for specimens without pre-torsion treatment are 54,275 cycles and 4324 cycles before and after pre-corrosion,while they increased significantly to 92,015 cycles and 5050 cycles with the 30%shear strain,***,the 30%shear strain specimens show a significant reduction in corrosion *** conclusion,pre-torsion treatment can effectively modify the microstructure of Mg-3Zn-0.2Ca alloy,enhancing both mechanical properties and corrosion *** optimal shear strain for this improvement is 30%.This study provides a practical method to enhance the mechanical properties and corrosion resistance of Mg-3Zn-0.2Ca alloy,making it more suitable for biomedical implan

关键词： Magnesium alloy Pre-torsion Microstructure Mechanical property Corrosion resistance

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Erosion Analysis of Static Components in Slurry Pumps Based on Reverse Modeling

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Fluid Dynamics & Materials Processing 2025年第3期21卷 589-603页

作者： Zhengjing Shen Fanqiang Kong Yu Liu Jilai Zeng Wengang Yang Jiangbo Wu School of College of Energy and Power Engineering Lanzhou University of TechnologyLanzhou730050China Key Laboratory of Advanced Pumps Valves and Fluid Control SystemMinistry of EducationLanzhou730050China

Erosion in slurry pumps presents a persistent challenge in industrial *** study examines the erosion of the static components of a 150ZJ-C42 centrifugal slurry pump,currently in operation at a beneficiation plant,under varying particle *** high-precision three-dimensional reverse engineering,the pump’s flow passage geometry was reconstructed to facilitate detailed erosion *** on the front and rear baffles of the pump chamber,as well as the volute,erosion patterns were analyzed for different particle volume concentrations and *** results reveal that the highest erosion damage consistently occurs near the volute tongue,with wear being most severe in regions adjacent to the partition plate near the rear *** damage intensity in this area correlates positively with particle ***,the average erosion rate in the volute surpasses that of the front and rear chamber liners,reaching a value as high as 6.03×10^(-7)kg·m^(-2)·s^(-1)at a particle concentration of 9%and diameter of 0.1 mm,adversely impacting pump *** the pump chamber baffles,increased erosion is observed at a particle diameter of 0.05 mm under constant volume concentration conditions,while higher particle concentrations exacerbate localized erosion.

关键词： Slurry pump reverse modeling numerical simulation erosion solid-liquid two-phase flow

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Deep Learning and Projection Neural Network With Finite-Time Convergence for Energy Management of Multi-Energy system

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IEEE Transactions on Smart Grid 2025年第3期16卷 2156-2168页

作者： Liu, Xueying He, Xing Li, Chaojie Huang, Tingwen Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China North China Electric Power University State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources Beijing102206 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this paper, an approach based on projection neural network (PNN), sliding mode control technique, and deep learning is proposed to solve the energy management problem of multi-energy systems (MES) containing dynamic parameters. First, the sliding mode technique is introduced in the PNN to design a finite-time PNN (FTPNN). The stability and finite-time convergence of the proposed FTPNN are proved by the Lyapunov method and the setting time bound is given. Then, the deep FTPNN (DFTPNN) is designed by combining deep learning with the proposed FTPNN. The dynamic parameters in the MES that change over time are used as input variables for the DFTPNN, allowing the trained DFTPNN to respond immediately to changes in the dynamic parameters and to predict the solutions of the FTPNN with different parameters directly. Simulation experiments show that FTPNN has faster convergence compared to PNN. DFTPNN significantly reduces the computation time compared to FTPNN. DFTPNN provides predicted solutions to FTPNN. Since DFTPNN can respond immediately to changes in dynamic parameters and directly provide energy management strategies under different parameters, it can adapt to changing environments and promote the economic and stable operation of MES. © 2010-2012 IEEE.

关键词： Cogeneration Heuristic algorithms Convergence Deep learning Prediction algorithms Optimization Heating systems Energy management Approximation algorithms Power system stability

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Evetac Meets Sparse Probabilistic Spiking Neural Network: Enhancing Snap-Fit Recognition Efficiency and Performance

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IEEE Robotics and Automation Letters 2025年第6期10卷 5353-5360页

作者： Fang, Senlin Ding, Haoran Liu, Yangjun Liu, Jiashu Zhang, Yupo Li, Yilin Kong, Hoiio Yi, Zhengkun Faculty of Data Science City University of Macau 999078 China Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China City University of Hong Kong Hong Kong University of Macau 999078 China Shenzhen Institute of Advanced Technology Shenzhen518055 China City University of Macau 999078 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China City University of Macau Faculty of Data Science 999078 China Chinese Academy of Sciences Key Laboratory of Biomedical Imaging Science and System Shenzhen518055 China

Snap-fit peg-in-hole assembly is common in industrial robotics, particularly for 3 C electronics, where fast and accurate tactile recognition is crucial for protecting fragile components. Event-based optical sensors, such as Evetac, are well-suited for this task due to their high sparsity and sensitivity in detecting small, rapid force changes. However, existing research often converts event data into dense images and processing them with dense methods, leading to higher computational complexity. In this letter, we propose a Sparse Probabilistic Spiking Neural Network (SPSNN) that utilizes sparse convolutions to extract features from the event data, avoiding computations on non-zero cells. We introduce the Forward and Backward Propagation Through Probability (FBPTP) method, which enables simultaneous gradient computation across all time steps, eliminating the need for the step-by-step traversal required by traditional Forward and Backward Propagation Through Time (FBPTT). Additionally, the Temporal Weight Prediction (TWP) method dynamically allocates weights for different time outputs, enhancing recognition performance with minimal impact on model efficiency. We integrate the Evetac sensor compactly into our robotic system and collected two datasets, named Tactile Event Ethernet (TacEve-Eth) and Tactile Event Type-C (TacEve-TC), corresponding to cantilever and annular snap-fit structures. Experiments show that the SPSNN achieves the superior trade-off between recognition performance and efficiency compared to other widely used methods, achieving the highest average recognition performance while reducing inference time by over 90% compared to FBPTT-based dense SNN baselines. © 2016 IEEE.

关键词： Robotic assembly

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Design of off-axis reflective holographic optical elements in a holographic near-eye display system

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Optics Letters 2025年第9期50卷 3022-3025页

作者： Zhang, Shijie Tian, Yifan Liu, Juan Beijing Engineering Research Center for Mixed Reality and Advanced Display MoE Key Lab of Photoelectronic Imaging Technology and System School of Optics and Photonics Beijing Institute of Technology Beijing100081 China

Holographic optical elements (HOEs) span a wide application, such as virtual reality and augmented reality displays. However, due to the complex aperiodic structures in lens-type HOEs, the phase design faces difficulties in aberration optimization. Here, we present a method for the design of the off-axis reflective lens-type HOE. Considering the varying degrees of aberrations introduced by the varying object distances across different regions of the object plane, a straightforward yet effective local aberration compensation method is carried out through superimposing different mutually perpendicular cylindrical lens phases at different positions of the HOE. The optimized phase distribution of the HOE can be directly obtained for fabrication like holographic printing. The numerical results show that the field curvature (FC) and the interval of the imaging distance between the meridional plane and the sagittal plane are significantly reduced to 1% of their initial values, and the astigmatism is alleviated. The optical experiments are conducted using two spatial light modulators (SLMs), and the experimental results are in good agreement with the optimized ones. It is expected that the proposed method could be further applied for the development of holographic near-eye display (NED) devices. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Augmented reality

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Irrelevant Locomotion Intention Detection for Myoelectric Assistive Lower Limb Robot Control

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical Robotics and Bionics 2025年第2期7卷 655-665页

作者： Song, Xiaoyu Liu, Jiaqing Pan, Heng Rao, Haotian Wang, Can Wu, Xinyu Southern University of Science and Technology Shenzhen518055 China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China

In this study, we propose a robust myoelectric intention recognition framework to recognize human locomotion mode and detect irrelevant locomotion intention. The framework is integrated into the control system of the lower limb exoskeleton robot for experimental validation. Most conventional electromyography(EMG) intention detection methods aim to accurately detect the target motion intentions but ignore the possible effects of irrelevant intentions. In traditional action intention recognition strategies, most researchers did not consider entering irrelevant action intentions into the model during training. Therefore, when using a classification model, if irrelevant action intentions are input, the model will still recognize it as a type of target action intention. That can lead to incorrect recognition results, which will cause the robot to perform wrong movements and pose a safety risk to the wearer. To detect and reject irrelevant motion intentions, we first used the dual-purpose autoencoder-guided temporal convolution network (DA-TCN) to obtain discriminative features of the surface EMG signal. Autoencoders (AE)/Variable Autoencoders (VAE) are then trained for each of the seven deep features of the target motion intention. In addition, irrelevant motion intentions are detected according to the value of their reconstruction error. The recall rate of this method for the detection of irrelevant motion intentions exceeds 99% and the accuracy rate exceeds 99%.At the same time, we replaced the TCN with the LSTM model and compared the performance of the two after adding irrelevant motion discrimination. We collected data on seven goals and three unrelated motor intentions from seven experimenters for testing and completed an online experimental validation. The motion recognition accuracy of all the experimenters can be maintained above 86%. © 2018 IEEE.

关键词： Limbs Legged locomotion Exoskeletons Robots Image color analysis Convolution Stairs Training Feature extraction Autoencoders

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FWAF-VID: A Flapping-Wing Aggressive Flight Benchmark Dataset for Visual-Inertial Localization

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IEEE Robotics and Automation Letters 2025年第6期10卷 6328-6335页

作者： Jiang, Jizhou Pan, Erzhen Xu, Wenfu Sun, Wei Ye, Jingyang School of Robotics and Advanced Manufacture Harbin Institute of Technology Shenzhen China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Guangdong Biomimetic Intelligent Unmanned System Engineering Technology Research Center Shenzhen518052 China

Accurate state estimation of micro aerial vehicles (MAVs) in high-speed and dynamic environments poses a significant challenge for visual-inertial odometry (VIO) algorithms. Flapping-wing aerial vehicles (FWAVs), as an emerging flight platform, have attracted significant attention for stealth capabilities and efficient flight characteristics. Despite the availability of numerous MAV visual-inertial datasets for six-degree-of-freedom (6-DoF) state estimation, these datasets are not applicable for FWAVs with pronounced vibrations and agile maneuverability. To address this gap, we propose a large-scale flapping-wing aggressive flight visual-inertial dataset FWAF-VID. It contains diverse integrations of synchronized onboard cameras and IMU sensors. A total of 28 sequences include static flapping, calibration, and real-world flights collected in outdoor and indoor environments. The 17 flight sequences feature variations in illuminations, speeds, trajectories, camera perspectives, and flight modalities. We provide precisely aligned ground truth RTK and UWB measurements for algorithm evaluation. Furthermore, a comprehensive benchmark comparison is conducted, qualitatively and quantitatively evaluating the positioning accuracy of state-of-theart VIO algorithms. The experimental results indicate that despite the degradation in localization accuracy in high-dynamic environments, FWAF-VID can effectively support the further development of VIO algorithms for FWAVs. To the best of our knowledge, this is the first onboard benchmark dataset tailored for aggressive flight in flapping-wing airborne platforms. © 2016 IEEE.

关键词： Micro air vehicle (MAV)

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Dynamic Characteristics of the Subsea Direct Drive Hydraulic Servo Rotary Valve

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China Ocean Engineering 2025年第2期39卷 329-339页

作者： SHI You-cheng SHAN Jun-feng ZHANG Hu-cheng LIU Yin-shui College of Energy and Fluid Power Engineering Lanzhou University of Technology Key Laboratory of Advanced Pumps Valves and Fluid Control System of the Ministry of Education Lanzhou University of Technology

Hydraulic technology has the outstanding advantages of easy pressure compensation and high power density. It is an indispensable part of subsea equipment, such as deep-sea operations and submersible propulsion. There are few studies on electrohydraulic servo valves(EHSVs) in the deep sea. In this work, a novel electro-hydraulic servo rotary valve is designed, and its mathematical model is established. The analysis considers the variations in physical parameters such as temperature, ambient pressure, and oil viscosity resulting from changes in sea depth. This study focuses on the deformation of the rotary valve and the consequent alterations in leakage and friction torque. The findings indicate that at a depth of 12000 m, the fit clearance between the valve spool and the valve sleeve is 0.00413 mm, representing a 17% reduction compared with the clearance in a land environment. Then, the response of the rotary valve to depth is analyzed. The results indicate that the bandwidth of the rotary valve decreases with increasing depth. This study provides a reference for the use of the EHSV in the deep sea.

关键词： dynamic characteristics electro-hydraulic servo rotary valve fit clearance response subsea hydraulic technology valve deformation

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