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Chinese Journal of Mechanical Engineering 2024年第2期37卷 100-114页

作者： Yan Shi Jiange Kou Zhenlei Chen yixuan Wang Qing Guo School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaChengdu 611731China

Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction ***,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to ***,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model ***,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical *** a backstepping controller based on the identified model is adopted to improve the human-robot wearable comfortable performance under cooperative ***,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons *** knee joint motion achieves a steady-state response after 0.5 ***,the position error of hip joint response is less than 0.03 rad after 0.9 *** addition,the steady-state human-robot interaction torque of the two joints is constrained within 15 N·*** research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model ***,an enhanced mutation strategy is adopted to avoid whale evolution’s unsatisfactory local optimal value.

关键词： Parameter identification Enhanced whale optimization algorithm(EWOA) Backstepping Human-robot interaction Lower limb exoskeleton

MAUN:Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1139-1150页

作者： Qian Hu Jiayi Ma Yuan Gao Junjun Jiang yixuan Yuan Electronic Information School Wuhan UniversityWuhan 430072China School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Department of Electronic Engineering Chinese University of Hong KongHong Kong 999077China

Spectral compressive imaging has emerged as a powerful technique to collect the 3D spectral information as 2D *** algorithm for restoring the original 3D hyperspectral images(HSIs)from compressive measurements is pivotal in the imaging *** approaches painstakingly designed networks to directly map compressive measurements to HSIs,resulting in the lack of interpretability without exploiting the imaging *** some recent works have introduced the deep unfolding framework for explainable reconstruction,the performance of these methods is still limited by the weak information transmission between iterative *** this paper,we propose a Memory-Augmented deep Unfolding Network,termed MAUN,for explainable and accurate HSI ***,MAUN implements a novel CNN scheme to facilitate a better extrapolation step of the fast iterative shrinkage-thresholding algorithm,introducing an extra momentum incorporation step for each iteration to alleviate the information ***,to exploit the high correlation of intermediate images from neighboring iterations,we customize a cross-stage transformer(CSFormer)as the deep denoiser to simultaneously capture self-similarity from both in-stage and cross-stage features,which is the first attempt to model the long-distance dependencies between iteration *** experiments demonstrate that the proposed MAUN is superior to other state-of-the-art methods both visually and *** code is publicly available at https://***/HuQ1an/MAUN.

关键词： Deep folding iteration

Bioinspired Multifunctional Self-Sensing Actuated Gradient Hydrogel for Soft-Hard Robot Remote Interaction

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Nano-Micro Letters 2024年第4期16卷 139-152页

作者： he Liu Haoxiang Chu Hailiang Yuan Deliang Li Weisi Deng Zhiwei Fu Ruonan Liu Yiying Liu yixuan Han Yanpeng Wang Yue Zhao Xiaoyu Cui Ye Tian College of Medicine and Biological Information Engineering Northeastern UniversityShenyang 110169People’s Republic of China Foshan Graduate School of Innovation Northeastern UniversityFoshan 528300People’s Republic of China

The development of bioinspired gradient hydrogels with self-sensing actuated capabilities for remote interaction with soft-hard robots remains a challenging endeavor. here, we propose a novel multifunctional self-sensing actuated gradient hydrogel that combines ultrafast actuation and high sensitivity for remote interaction with robotic hand. The gradient network structure, achieved through a wettability difference method involving the rapid precipitation of MoO_(2) nanosheets, introduces hydrophilic disparities between two sides within hydrogel. This distinctive approach bestows the hydrogel with ultrafast thermo-responsive actuation(21° s^(-1)) and enhanced photothermal efficiency(increase by 3.7 ℃ s^(-1) under 808 nm near-infrared). Moreover, the local cross-linking of sodium alginate with Ca^(2+) endows the hydrogel with programmable deformability and information display capabilities. Additionally, the hydrogel exhibits high sensitivity(gauge factor 3.94 within a wide strain range of 600%), fast response times(140 ms) and good cycling stability. Leveraging these exceptional properties, we incorporate the hydrogel into various soft actuators, including soft gripper, artificial iris, and bioinspired jellyfish, as well as wearable electronics capable of precise human motion and physiological signal detection. Furthermore, through the synergistic combination of remarkable actuation and sensitivity, we realize a self-sensing touch bioinspired tongue. Notably, by employing quantitative analysis of actuation-sensing, we realize remote interaction between soft-hard robot via the Internet of Things. The multifunctional self-sensing actuated gradient hydrogel presented in this study provides a new insight for advanced somatosensory materials, self-feedback intelligent soft robots and human–machine interactions.

关键词： Self-sensing Gradient structure Bioinspired actuator Hydrogel sensor Remote interaction

Exponentially Convergent Multiscale Finite Element Method

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Communications on Applied Mathematics and Computation 2024年第2期6卷 862-878页

作者： Yifan Chen Thomas Y.Hou yixuan Wang Applied and Computational Mathematics CaltechPasadena 91106USA

We provide a concise review of the exponentially convergent multiscale finite element method(ExpMsFEM)for efficient model reduction of PDEs in heterogeneous media without scale separation and in high-frequency wave *** ExpMsFEM is built on the non-overlapped domain decomposition in the classical MsFEM while enriching the approximation space systematically to achieve a nearly exponential convergence rate regarding the number of basis *** most generalizations of the MsFEM in the literature,the ExpMsFEM does not rely on any partition of unity *** general,it is necessary to use function representations dependent on the right-hand side to break the algebraic Kolmogorov n-width barrier to achieve exponential ***,there are online and offline parts in the function representation provided by the *** online part depends on the right-hand side locally and can be computed in parallel *** offline part contains basis functions that are used in the Galerkin method to assemble the stiffness matrix;they are all independent of the right-hand side,so the stiffness matrix can be used repeatedly in multi-query scenarios.

关键词： Multiscale method Exponential convergence helmholtz's equation Domain decomposition Nonlinear model reduction

An automatic Q-factor matching method for eliminating 77%of the ZRO of a MEMS vibratory gyroscope in rate mode

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Microsystems & Nanoengineering 2024年第3期10卷 35-48页

作者： Jingbo Ren Tong Zhou Yi Zhou yixuan Li Yan Su School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210000China

Mismatching quality factors(Q-factors)is one of the main factors causing zero-rate output(ZRO)in degenerate(DE)Micro-Electro-Mechanical Systems(MEMS)vibratory *** eliminate the ZRO of the DE MEMS gyroscope,this study introduces a method for real-time identification and automatic matching of Q-factors in rate *** leveraging the vibration characteristics of the DE MEMS vibratory gyroscope in rate mode,dedicated online test methods are designed to determine the Q-factors for both the drive and sense modes,enabling online identification of the Q-factor ***,an automatic Q-factor matching system is designed utilizing the mechanical-thermal dissipation mechanism of the resistive *** effectiveness of this proposed method is validated through simulations and experiments conducted on a MEMS disk resonator gyroscope(DRG).The results show a measurement error within 4%for Q-factor identification,and automatic Q-factor matching effectively reduces the ZRO by 77%.Employing this automatic Q-factor matching method successfully reduces the ZRO that is caused by the mismatching of Q-factors in the MEMS DRG from 0.11°/s to 0.025°/s and improves the bias instability(BI)from 0.40°/s to 0.19°/s.

关键词： matching mode method

2001-2015年西南纵向岭谷区植被EVI变化趋势与驱动力分析

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2001-2015年西南纵向岭谷区植被EVI变化趋势与驱动力分析

作者：何奕萱成都理工大学

学位级别：硕士

植被在调节生态碳循环及气候系统的平衡性中发挥了重要作用,通过监测植被分布状况、变化趋势及其驱动机制能揭示植被与大气、土壤等生态因子之间的关系。西南纵向岭谷区内高山峡谷相间分布的地貌格局及垂直带谱结构对研究区域尺度下山... 详细信息

植被在调节生态碳循环及气候系统的平衡性中发挥了重要作用,通过监测植被分布状况、变化趋势及其驱动机制能揭示植被与大气、土壤等生态因子之间的关系。西南纵向岭谷区内高山峡谷相间分布的地貌格局及垂直带谱结构对研究区域尺度下山地生态系统的演变规律与过程具有科学意义。本文基于MODIS EVI数据产品,结合植被类型数据、气候数据以及DEM数据等,利用趋势分析、灰色关联分析以及相关性分析法,探讨西南纵向岭谷区2001-2015年植被EVI时空变化趋势及其对气候变化的响应。主要结论如下:(1)西南纵向岭谷区植被EVI年均值为0.36,空间特征大致表现为由北向南逐渐增加的趋势,局部分异明显。植被EVI高值区主要集中在德宏、思茅以及临沧西南部等地区,低值区主要分布在怒江北部、昌都西部以及甘孜州西南部等地区。不同季节植被EVI与年植被EVI空间分布特征整体相似,但局部地区有所差异。此外,西南纵向岭谷区年及各季节植被EVI均表现出随海拔升高而降低的趋势。(2)西南纵向岭谷区植被EVI年均值年际变化波动较小,范围0.30-0.34之间。西南纵向岭谷区年均植被EVI退化区域主要零散分布在怒江州、大理南部等地区;改善的地区主要分布于临沧西部、文山县东部等区域。此外,各季节与全年植被EVI年际变化趋势大体一致,均呈不明显减少趋势。各季节中植被EVI呈退化趋势、基本不变、改善趋势所占面积比最大的分别在夏季、秋季、春季。不同高程区间植被EVI变化趋势具有显著差异。(3)西南纵向岭谷区植被EVI对气候因子的响应存在明显的时滞效应。春季和生长季植被EVI与同时期月平均气温响应迅速,对降水的响应则滞后一个月;夏季植被EVI与同时期月累计降水量之间关系最为密切,而对气温则表现为滞后两个月;秋季植被EVI对气温和降水均滞后两个月。(4)年均、生长季、夏季植被EVI与气温大致呈负相关关系,主要以块状分布在怒江、丽江东部以及德宏北部等地区;与降水则表现为正相关关系,区域主要集中分布在大理西北部、临沧东部以及楚雄南部等地区。春季植被EVI与气温和降水均表现为负相关。秋季植被EVI与气温和降水的相关性较弱。(5)西南纵向岭谷区大部分地区植被EVI指数表现为非气候因子驱动。植被EVI受气候驱动的区域面积占比为11.05%;其中气温驱动型、降水驱动型分别占5.26%和3.21%;气温、降水强驱动零星地分布全区,仅占1.84%。整体而言,气候因子对不同季节植被EVI生长影响强弱依次为夏季、生长季、春季、秋季。

关键词：增强型植被指数时滞效应气候变化响应分析西南纵向岭谷区

Towards complex scenes: A deep learning-based camouflaged people detection method for snapshot multispectral images

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Defence Technology（防务技术） 2024年第4期34卷 269-281页

作者： Shu Wang Dawei Zeng yixuan Xu Gonghan Yang Feng Huang Liqiong Chen School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China

Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.

关键词： Camouflaged people detection Snapshot multispectral imaging Optimal band selection MS-YOLO Complex remote sensing scenes

Analysis of temperature characteristics of high-speed train wheelset system under complex operating conditions

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International Journal of Mechanical System Dynamics 2024年第3期4卷 331-345页

作者： Baosen Wang Yongqiang Liu Yingying Liao yixuan Wang School of Mechanical Engineering Shijiazhuang Tiedao UniversityShijiazhuangChina hebei Key Laboratory of Mechanical Power and Transmission Control Shijiazhuang Tiedao UniversityShijiazhuangChina School of Civil Engineering Shijiazhuang Tiedao UniversityShijiazhuangChina Taiyuan Vehicle Depot Daqin Railway Co.Ltd.TaiyuanChina

With the rapid advancements in high-speed train technology,the importance of ensuring the safety of train operations has become ***,being a critical component of train bogies,have garnered significant attention for their role in maintaining safety *** the temperature of bearings to evaluate their motion state is a common practice in high-speed trains,emphasizing the need for further research into temperature *** this study,a dynamic model is developed for the bearing rotor system of high-speed *** considering the contact points between raceways and rolling elements,the power loss in the bearing is obtained and a transient temperature-field model of the system is *** relationship between node temperature and factors such as ambient temperature,train running speed,and load is illustrated,with a detailed presentation of the influence of bearing fault type and size on node *** analysis results reveal that the node temperature increases with higher values corresponding to those quantifiable factors and is most affected by rolling element ***,it is observed that the temperature rises rapidly in the initial stage and gradually flattens out over *** comparative analysis of temperature under different fault conditions shows that the node temperature is most affected by the rolling element *** and actual line temperature data are used to verify the validity of the *** comparison results show that the simulation aligns well with experimental and line *** transient temperature-field model of the bearing rotor system in high-speed trains can effectively simulate and predict the temperature change process of each node of the *** simulation results hold certain theoretical guiding significance for further research and practical applications in ensuring train operation safety.

关键词： high-speed train dynamic model transient temperature field bearing fault line data

More Than Lightening:A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 622-637页

作者： Han Xu Jiayi Ma yixuan Yuan Hao Zhang Xin Tian Xiaojie Guo the Electronic Information School Wuhan UniversityWuhan 430072China IEEE the Department of Electronic Engineering Chinese University of Hong KongHong Kong 999077China the College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of *** enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is *** contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better *** self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and *** response,this paper proposes a self-supervised enhancement method,termed as *** can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised *** attenuation is estimated based on physical principles and local neighborhood *** removal and correction of noise and color shift removal are solely realized with noisy images and images with color ***,the comprehensive and fully self-supervised approach can achieve better adaptability and *** is applicable to various low light conditions,and can reproduce the original color of scenes in natural *** experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art *** code is available at https://***/hanna-xu/SLIE.

关键词： Color correction low-light image enhancement self-supervised learning.

A Predictive Energy Management Strategies for Mining Dump Trucks

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Energy Engineering 2024年第3期121卷 769-788页

作者： yixuan Yu Yulin Wang Qingcheng Li Bowen Jiao College of Mechanical and Electrical Engineering Qingdao UniversityQingdao266071China

The plug-in hybrid vehicles(PheV)technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump ***,plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies(EMS).Therefore,a series hybrid system is constructed based on a 100-ton mining dump truck in this *** inspired by the dynamic programming(DP)algorithm,a predictive equivalent consumption minimization strategy(P-ECMS)based on the DP optimization result is *** on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm,the P-ECMS strategy performs real-time stage parameter optimization to obtain the optimal equivalent factor(EF).Finally,applying the equivalent consumption minimization strategy(ECMS)realizes real-time *** simulation results show that the equivalent fuel consumption of the P-ECMS strategy under the experimentally collected mining cycle conditions is 150.8 L/100 km,which is 10.9%less than that of the common CDCS strategy(169.3 L/100 km),and achieves 99.47%of the fuel saving effect of the DP strategy(150 L/100 km).

关键词： Mining dump truck energy management strategy plug-in hybrid electric vehicle equivalent consumption minimization strategy dynamic programming