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Study of the 6.x nm short wavelength radiation spectra of laser-produced erbium plasmas for BEUV lithography

Plasma Science and Technology 2023年第6期25卷 41-51页

作者：吴涛王倩陈柳安陆培祥 Hubei Key Laboratory of Optical Information and Pattern Recognition School of Optical Information and Energy EngineeringWuhan Institute of TechnologyWuhan 430205People's Republic of China Guangdong Intelligent Robotics Institute Dongguan 523808People's Republic of China

Beyond extreme ultraviolet(BEUV)radiation with a wavelength of 6.x nm for lithography is responsible for reducing the source wavelength to enable continued miniaturization of semiconductor *** this work,the Required BEUV light at 6.x nm wavelength was generated in dense and hot Nd:YAG laser-produced Er *** spectral contributions from the 4p–4d and 4d–4f transitions of singly,doubly and triply excited states of Er XXIV–Er XXXII in the BEUV band were calculated using Cowan and the Flexible Atomic *** was also found that the radiative transitions between multiply excited states dominate the narrow wavelength window around 6.x *** the assumption of collisional radiative equilibrium of the laser-produced Er plasmas,the relative ion abundance in the experiment was *** the Boltzmann quantum state energy level distribution and Gram–Charlier fitting function of unresolved transition arrays(UTAs),the synthetic spectrum around 6.x nm was finally obtained and compared with the experimental *** spatio-temporal distributions of electron density and electron temperature were calculated based on radiation hydrodynamic simulation in order to identify the contributions of various ionic states to the UTAs arising from the Er plasmas near 6.x nm.

关键词： laser-produced plasmas unresolved transition array collisional radiative equilibrium

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A new active rehabilitation training mode for upper limbs based on Tai Chi Pushing Hands

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Biomimetic Intelligence & robotics 2024年第3期4卷 82-92页

作者： Xiangpan Li Liaoyuan Li Jianhai Han Bingjing Guo Ganqin Du School of Mechatronics Engineering Henan University of Science and TechnologyLuoyang 471003China Henan Provincial Key Laboratory of Robotics and Intelligent Systems Luoyang 471003China School of Automotive Engineering Hubei University of Automotive TechnologyShiyan 442002China Hubei Key Laboratory of Automotive Power Train and Electronic Control Shiyan 442002China The First Affiliated Hospital of Henan University of Science and Technology Luoyang 471003China

Robot-assisted rehabilitation is a crucial approach to restoring motor function in the ***,the current training trajectory lacks sufficient theoretical or practical support,and the monotony of single-mode training is a *** Chi Pushing Hands,a beneficial and effective daily exercise,has been shown to improve balance function,psychological state,and motor function of the upper extremities in patients recovering from *** address these issues,we propose a new active rehabilitation training that incorporates Tai Chi Pushing Hands movements and yin-yang balance *** training trajectory and direction are encoded by the velocity field and consist of two processes:yang(push)and yin(return).During yang,the limb actively pushes the robot to move,while during yin,the limb actively follows the robot’s *** provide necessary assistance,an admittance controller with self-adaptive parameters is *** addition,we introduce two indexes,the‘Intention Angle’(ϖ)and the time ratio(Γ),to evaluate motion perception *** experiment was conducted on a 4-degree-of-freedom upper limb rehabilitation robot platform,and the subjects were separated into a familiar group and an unfamiliar *** experiment results show that the training could be completed well no matter whether the subject is familiar with Tai Chi Pushing Hands or *** parameters and the movement of the robot can be adjusted based on the interactive force to adapt to the ability of the subject.

关键词： Tai Chi Push Hands Velocity field Self-adaptive admittance Upper limb rehabilitation Active training

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Hardware-Free Event Cameras Temporal Synchronization Based on Event Density Alignment 1

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16th International Conference on intelligent robotics and Applications, ICIRA 2023

作者： Li, Wenxuan Dong, Yan Qiu, Shaoqiang Han, Bin State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology Hubei Wuhan430074 China Guangdong Intelligent Robotics Institute Dongguan523106 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Event cameras are a novel type of sensor designed for capturing the dynamic changes of a scene. Due to factors such as trigger and transmission delays, a time offset exists in the data collected by multiple event cameras, leading to inaccurate information fusion. Thus, the collected data needs to be synchronized to overcome any potential time offset issue. Hardware synchronization methods require additional circuits, while certain models of event cameras (e.g., CeleX5) do not support hardware synchronization. Therefore, this paper proposes a hardware-free event camera synchronization method. This method determines differences between start times by minimizing the dissimilarity of the event density distributions of different event cameras and synchronizes the data by adjusting timestamps. The experiments demonstrate that the method's synchronization error is less than 10 ms under various senses with multiple models of event cameras. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Cameras

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An Indoor Positioning Algorithm Against NLOS Error Based on UWB 41

An Indoor Positioning Algorithm Against NLOS Error Based on ...

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第41届中国控制会议

作者： Mingxiang Liao Yongbo Li Guangyao Wang Zhenyu Lei Zihao Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Ultra-wideband（UWB） positioning technology has absolute advantages due to its centimeter-level accurate positioning ***,the positioning accuracy is greatly reduced because of the inability to completely solve the error caused by non-line-of-sight（NLOS） and multi-path *** present,the Chan-Taylor（C-T） combination algorithm proposed by scholars can achieve a good positioning effect in the line-of-sight（LOS） environment,but in the NLOS environment,positioning deviation of this algorithm is large .Aiming at the problem of low localization accuracy in NLOS environment,this paper presents a Chan-Taylor-Kalman（CTK） joint positioning algorithm based on UWB and adapted to NLOS *** basic idea of CTK joint positioning algorithm is to introduce weight coefficients on the basis of C-T combination algorithm to reduce the situation of non-convergence of positioning results;then combined with the improved Kalman filter to eliminate outliers and eliminate the influence of the non-line-of-sight *** show that under the same NLOS environment,the probability of the positioning error of the C-T combination positioning algorithm greater than 20 cm is about 60%,while the probability of the positioning error of the CTK joint positioning algorithm greater than 10 cm is only about 10%.

关键词： UWB NLOS indoor positioning Chan-Taylor combination algorithm Kalman filter

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Kinematics analysis of lower limb rehabilitation robot based on D-H method 41

Kinematics analysis of lower limb rehabilitation robot based...

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第41届中国控制会议

作者： Kui Jie Wangyong He Renjie Gui School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

At present,rehabilitation robots usually work together with patients and train them to achieve therapeutic effects by assisting them to complete movement within a certain *** this paper,it analyzes the average length and proportion of Chinese human lower limbs,as well as the range of extreme motion and comfortable motion of each joint of human lower *** on the error transfer matrix of rigid body connecting rod,the three-DOF lower limb rehabilitation robot human lower limb static pose error model and human/machine integration model are *** D-H method was used to solve the kinematic function between the angle of each joint and the position of the end of human lower *** analysis of the kinematics of human lower limbs is to calculate its inverse kinematics *** the motion control of rehabilitation robots,the inverse kinematics is more important than the forward kinematics,which is the basis for rehabilitation robot to realize trajectory planning under the training mode of passive trajectory traction,as well as the basis for compliant ***,a simulation model is established with Matlab software,and the simulation results show the feasibility and safety of the rehabilitation training process.

关键词： Lower limb rehabilitation robot Range of motion Human kinematics

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Research on Tool Wear State Monitoring Method Based on Feature Processing 11th

Research on Tool Wear State Monitoring Method Based on Featu...

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11th International Workshop of Advanced Manufacturing and Automation, IWAMA 2021

作者： Chao, Liu Chen, Wang Xiufeng, Zhang Xuxiang, Lu Yu, Tang Hubei University of Automotive Technology Shiyan442002 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200072 China

ISBN: (纸本)9789811905711

In order to accurately monitor the tool wear degree in milling process, the tool wear state is monitored based on feature processing. Firstly, the force, vibration and acoustic emission signals were collected in the processing process, and the multi-dimensional information of the serial signals was obtained by analyzing the time domain, frequency domain and wavelet packet. Then, the Spearman coefficient was used to obtain the feature weight coefficient and extract the features strongly correlated with the average rear tool surface wear to carry out feature dimension reduction. Finally, KNN and ANN are respectively used to identify the tool wear state. By comparing the loss function, accuracy and confusion matrix, it is found that ANN model can accurately identify the tool wear state, and the recognition accuracy and generalization degree have been improved to some extent. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wear of materials

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A Weighting Factors Autotuning Strategy for Model Predictive Torque Control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-Objective Black Hole Algorithm 42

A Weighting Factors Autotuning Strategy for Model Predictive...

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42nd Chinese Control Conference, CCC 2023

作者： Zhou, Zixiang Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

The rational design of weighting factors in the cost function for finite control set model predictive torque control (FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor (PMSM) based on the adaptive multi-objective black hole algorithm (AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multi-objective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Cost functions

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Temperature Rising Model of Tubular Permanent Magnet Linear Synchronous Motor Based on Transfer Learning-Deep Neural Network 42

Temperature Rising Model of Tubular Permanent Magnet Linear ...

引用

42nd Chinese Control Conference, CCC 2023

作者： Wang, YiFei Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

High temperature rise of permanent magnet linear synchronous motor can lead to irreversible demagnetization of the motor permanent magnet, which can negatively affect the motor performance. To address this problem, a thermal modeling analysis method based on Transfer learning-Deep neural network (TL-DNN) was proposed in this paper. Its specific implementation steps include (1) corresponding to different heat source inputs, the equivalent thermal circuit method and the finite element analysis was adopted based on the structure and main parameters of PMLSM including overall average temperature rise, coil temperature rise and permanent magnet temperature rise from the data sets of the motor;(2) TL-DNN was used to fit the functional relationship between the input source features and the output targets based on the characteristics of the sample data sets. In order to verify the accuracy of the prediction model with small sample data sets, this paper divided the proportion of the data set and compared the results with other classic nonparametric models (random forest, support vector machine, and deep neural network). The results show that the TL-DNN model outperforms other machine learning models and has better robustness and generalization ability when the training datasets are insufficient, and achieves an organic combination of physical field path model and data-driven model, which provides a feasible solution for PMLSM modeling in the case of small samples. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Finite element method

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A Review of Small-Sample Target Detection Research 14th

A Review of Small-Sample Target Detection Research

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14th International Workshop of Advanced Manufacturing and Automation, IWAMA 2024

作者： Zhou, Lin Wang, Chen Yang, Shuai Huang, Peng College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442002 China China Academy of Engineering Science and Technology Shiyan Industrial Technology Research Institute Shiyan442000 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200072 China

ISBN: (纸本)9789819626243

Deep learning-based methods for detecting targets in images have advanced significantly in recent years and shown to have tremendous application potential across various domains. But in real-world applications, these methods are frequently constrained by the lack of labelled samples, particularly in situations with small sample sizes. As a result, it has become a crucial area of research to determine how to carry out target detection efficiently. This paper conducts a thorough analysis of image target detection technology under small sample conditions. It does this by methodically elaborating on the definition of the problem of small-sample image target detection and by thoroughly discussing a number of small-sample learning approaches, the most prominent of which are data enhancement-based, migration learning-based, and meta-learning-based. By discussing various algorithms and the fundamental idea behind the process, the benefits and drawbacks of the current approaches to small-sample detection are made evident. Sample identification issues. Lastly, the technological challenges of the current small sample target identification and the direction of future improvement are explored. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Review of Research on Battery Defect Detection and Recovery 14th

Review of Research on Battery Defect Detection and Recovery

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14th International Workshop of Advanced Manufacturing and Automation, IWAMA 2024

作者： Huang, Peng Wang, Chen Yang, Shuai Zhou, Lin College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442002 China China Academy of Engineering Science and Technology Shiyan Industrial Technology Research Institute Shiyan442000 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200072 China

ISBN: (纸本)9789819626243

Deep learning technology has injected new vitality into the defect detection and disassembly recycling of batteries. This paper describes the defect detection and disassembly recycling of batteries. Firstly, this paper outlines a protocol for detecting imperfections that relies on traditional machine vision procedures, encompassing both image domain analysis and transform domain analysis. Secondly, this paper describes the applications of deep learning in defect detection, including supervised training, unsupervised data mining, limitedly supervised learning, etc. Then, deep neural network applications in the disassembly and recycling of waste batteries is described. Finally, defect inspection relying on traditional machine vision methodologies, the approach for anomaly detection utilizing hierarchical learning, and the implementation of deep neural networks technology in the disassembly and recycling of waste batteries are all summarized herein. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Machine vision

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