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2nd International Conference on Mechanics, Electronics, Automation and Automatic control, MEAAC 2024

作者： Wei, Pengxuan Wang, Liping Li, Weitao School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu611731 China State Key Laboratory of Tribology Department of Mechanical Engineering Tsinghua University Beijing100084 China Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipment and Control Beijing100084 China

ISBN: (纸本)9781643685403

Machine tools play a vital role in the manufacturing industry and their wide application leads to high energy consumption. Considering energy saving and emission reduction, it becomes particularly important to reduce the energy consumption of machine tools while improving processing efficiency. Selecting appropriate milling parameters while optimizing the processing power and efficiency of the machine tools is a challenge. In this paper, an adaptive multi-objective differential evolutionary PSO based on analytic hierarchy process (AMDEPSO) is proposed to optimize the two objectives. Firstly, an accurate multi-objective optimization model integrating the processing power and time of machine tools is established. In order to solve this optimization model, this study sets adaptive weights based on PSO and incorporates the differential evolution (DE) method to update particles in the local search. Subsequently, the Pareto solution set is filtered to obtain the optimal solution through analytic hierarchy process (AHP). Finally, the algorithm is verified by processing experiments, and compared with the two existing methods, the proposed method effectively reduces the processing power and improves the processing efficiency. Combining the relationship between the two optimization objectives, it can be obtained that the algorithm reduces the machining energy consumption by 45.58% and 47.15% respectively. Â© 2024 The Authors.

关键词： differential evolution PSO Energy consumption milling parameters processing efficiency model processing power model

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Microwave heating as a universal method to transform confined molecules into armchair graphene nanoribbons

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Nano Research 2023年第7期16卷 10644-10651页

作者： Haoyuan Zhang Yingzhi Chen Kunpeng Tang Ziheng Lin Xuan Li Hongwei Zhang Yifan Zhang Chi Ho Wong Chi Wah Leung Chee Leung Mak Yuan Hu Weili Cui Kecheng Cao Lei Shi State Key Laboratory of Optoelectronic Materials and Technologies Nanotechnology Research CenterGuangdong Province Key Lab of Display Material and TechnologySchool of Materials Science and EngineeringSun Yat-sen UniversityGuangzhou 510275China Huzhou Key Laboratory of Environmental Functional Materials and Pollution Control School of EngineeringHuzhou UniversityHuzhou 313000China Department of Industrial and Systems Engineering Research Institute for Advanced ManufacturingThe Hong Kong Polytechnic UniversityHong Kong 999077China Department of Applied Physics The Hong Kong Polytechnic UniversityHong Kong 999077China Shanghai Key Laboratory of High-resolution Electron Microscopy ShanghaiTech UniversityShanghai 201210China

Armchair graphene nanoribbons(AGNRs)with sub-nanometer width are potential materials for the fabrication of novel nanodevices thanks to their moderate direct band *** are usually synthesized by polymerizing precursor molecules on substrate ***,it is time-consuming and not suitable for large-scale *** can also be grown by transforming precursor molecules inside single-walled carbon nanotubes(SWCNTs)via furnace annealing,but the obtained AGNRs are normally *** this work,microwave heating is applied for transforming precursor molecules into *** fast heating process allows synthesizing the AGNRs in *** different molecules were successfully transformed into AGNRs,suggesting that it is a universal *** importantly,as demonstrated by Raman spectroscopy,aberrationcorrected high-resolution transmission electron microscopy and theoretical calculations,less twisted AGNRs are synthesized by the microwave heating than the furnace *** results reveal a route for rapid production of AGNRs in large scale,which would benefit future applications in novel AGNRs-based semiconductor devices.

关键词： armchair graphene nanoribbons(AGNRs) microwave heating single-walled carbon nanotubes(SWCNTs) Raman spectroscopy

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Maneuvering Multiple Hypersonic Flight Vehicles via a Hierarchical control Framework

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Sun, Chong-Yi Fang, Xu Ma, Yan-Hua Chen, Hui Sun, Xi-Ming Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian116024 China Chalmers University of Technology Department of Electrical Engineering Gothenburg Sweden

This paper studies how to maneuver multiple hypersonic flight vehicles (HFVs) with desired collective forms. To this end, a hierarchical control framework utilizing the leaderfollower strategy is proposed, where the knowledge of time-varying target formation is not required for the followers. First, different from the real-weighted position constraints, the proposed matrixweighted position constraint requires fewer neighbors and less communication. Second, compared to most existing formation maneuver control methods, our method can change not only the rotation, scaling, and translation of multi-HFV formations but also a greater variety of formation shapes. Third, unlike the conventional strategies in which the altitudes and forward positions of the HFVs are controlled separately, the proposed method can control both altitudes and forward positions of the HFVs simultaneously. A remarkable advantage is its ability to achieve precise position control for each HFV. Finally, two numerical simulations are performed to demonstrate the effectiveness of the proposed control strategy © 1965-2011 IEEE.

关键词： Hypersonic vehicles

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Numerical simulation of the electromagnetic torques of PMSM with two-way magneto-mechanical coupling and nonuniform spline clearance in electric submersible pumping wells

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Petroleum science 2024年第6期21卷 4417-4426页

作者： Xin-Fu Liu Chun-Hua Liu Ying Zheng Ji-Fei Yu Wei Zhou Meng-Xiao Wang Peng Liu Yi-Fei Zhou Key Lab of Industrial Fluid Energy Conservation and Pollution Control(Ministry of Education) Qingdao University of TechnologyQingdao266520ShandongChina College of Mechanical and Electronic Engineering China University of Petroleum(East China)Qingdao266580ShandongChina Department of Chemical and Biochemical Engineering Western UniversityOntarioN6A 3K7Canada CNOOC Research Institute Ltd. CNOOCBeijing100028China

Clearance-fit(side-fit)spline joints are a key component in a permanent magnet synchronous motor(PMSM)in electric submersible pumping *** nonuniform spline clearance affects the output performance of a PMSM.A concept for energy conservation is optimized in this study to improve the modeling accuracy of electromagnetic ***,most existing computation models are one-way model with a magneto-mechanical *** this study,a more accurate two-way coupling method is presented for simulating the electromagnetic and mechanical characteristics of ***,importance should be attached to this two-way magneto-mechanical coupling methodology in an actual *** coupled power,electrical and magnetic energy,and electromagnetic torque equations are solved iteratively until convergence for PMSMs with a segmented rotor and a non-segmented *** optimal electromagnetic torque is obtained for different rotor configurations with the change of temperatures and rotational *** results show that the output performance and electromagnetic torque of the PMSM are seriously affected by the effects of two-way magneto-mechanical coupling and nonuniform spline *** proposed two-way coupling model gives more reasonable predictions than other one-way models do,because the power transfer between the electrical and magnetic energy can be modeled more *** self-centralizing performance of clearance-fit splines and the sensitivity to the radial clearance magnitude lead to the reduction of the electromagnetic torque for the ***,the electromagnetic torques decrease with the enhanced rotor temperatures and rotational *** best rotor temperature and rotational speed are chosen through a comparison of the experimental results,and then the optimal electromagnetic torque is provided to ensure the output performance of the PMSM in electric submersible pumping wells.

关键词： Permanent magnet synchronous motor Two-way coupling Magneto-mechanical coupling Nonuniform splineclearance Electromagnetic torque

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Topology Optimization for a Spoke-Type Permanent Magnet Synchronous Motor Based on a Siamese Convolutional Network 27

Topology Optimization for a Spoke-Type Permanent Magnet Sync...

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27th International Conference on Electrical Machines and Systems, ICEMS 2024

作者： Ma, Yidan Song, Zaixin Liang, Yongtao Cao, Jianfu The Hong Kong Polytechnic University State Key Lab of Ultra-precision Machining Technology Department of Industrial and Systems Engineering Hong Kong School of Automation Science and Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9784886864406

Combining stochastic algorithm-based topology optimization methods with deep neural networks holds great promise for enhancing the performance of electric machines. In this paper, we address the optimization of rotor structure with flux barriers in a spoke-type permanent magnet synchronous motor (PMSM) and introduce a siamese convolutional network based topology optimization method (SCNTO). After training the Siamese convolutional network using a cross-sectional image dataset, predetermined conditions are designed to filter a subset for further assessment using topology optimization. Experiments demonstrate that the proposed method achieves a smooth rotor shape within specified ranges of average torque and torque ripple, while minimizing iron loss with reduced computational costs. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Convolution

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Gear Fault Diagnosis in Geared Motors Based on Frequency Adaptation Graph Prototype Network with Limited Data 27

Gear Fault Diagnosis in Geared Motors Based on Frequency Ada...

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27th International Conference on Electrical Machines and Systems, ICEMS 2024

ISBN: (纸本)9784886864406

Detecting and classifying gear faults with limited labeled data is essential for effective fault diagnosis in electromechanical systems. This paper presents a novel Frequency Adaptation Graph Prototype Network (FAGPN) for classifying various gear faults in geared motors. FAGPN employs customized low-pass and high-pass filters, integrated with an attention mechanism, to enhance multi-scale feature fusion from vibration signals processed through various frequency-time methods. Additionally, FAGPN projects embeddings onto hyperspherical space with a consistency constraint to improve accuracy. Experimental results on real-world datasets involving multiple gear sets in different states demonstrate the superior performance of FAGPN. Remarkably, with a training ratio of 1%, FAGPN achieves over 99% accuracy. © 2024 The Institute of Electrical Engineers of Japan.

关键词： High pass filters

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VTAO-BiManip: Masked Visual-Tactile-Action Pre-training with Object Understanding for Bimanual Dexterous Manipulation

arXiv

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arXiv 2025年

作者： Sun, Zhengnan Shi, Zhaotai Chen, Jiayin Liu, Qingtao Cui, Yu Ye, Qi Chen, Jiming College of Control Science and Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Industrial Control Technology Zhejiang University China Key Key Lab of CS&AUS of Zhejiang Province China

Bimanual dexterous manipulation remains significant challenges in robotics due to the high DoFs of each hand and their coordination. Existing single-hand manipulation techniques often leverage human demonstrations to guide RL methods but fail to generalize to complex bimanual tasks involving multiple sub-skills. In this paper, we introduce VTAOBiManip, a novel framework that combines visual-tactile-action pretraining with object understanding to facilitate curriculum RL to enable human-like bimanual manipulation. We improve prior learning by incorporating hand motion data, providing more effective guidance for dual-hand coordination than binary tactile feedback. Our pretraining model predicts future actions as well as object pose and size using masked multimodal inputs, facilitating cross-modal regularization. To address the multiskill learning challenge, we introduce a two-stage curriculum RL approach to stabilize training. We evaluate our method on a bottle-cap unscrewing task, demonstrating its effectiveness in both simulated and real-world environments. Our approach achieves a success rate that surpasses existing visual-tactile pretraining methods by over 20%. Copyright © 2025, The Authors. All rights reserved.

关键词： Bottles

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TPGP: Temporal-Parametric Optimization with Deep Grasp Prior for Dexterous Motion Planning

TPGP: Temporal-Parametric Optimization with Deep Grasp Prior...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haoming Li Qi Ye Yuchi Huo Qingtao Liu Shijian Jiang Tao Zhou Xiang Li Yang Zhou Jiming Chen College of Control Science and Engineering Zhejiang University Hangzhou China The College of Control Science and Engineering the State Key Laboratory of Industrial Control Technology Zhejiang University The Key Key Lab of CS&AUS of Zhejiang Province State Key Lab of CAD&CG Zhejiang University Zhejiang Lab OPPO US Research Center

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Grasping motion planning aims to find a feasible grasping trajectory in the configuration space given an input target grasp. While optimizing grasp motion with two or three-fingered grippers has been well studied, the study on natural grasp motion planning with a dexterous hand remains a very challenging problem due to the high dimensional working space. In this work, we propose a novel temporal-parametric grasp prior (TPGP) optimization method to simplify the difficulty of grasping trajectory optimization for the dexterous hand while maintaining smooth and natural properties of the grasping motion. Specifically, we formulate the discrete trajectory parameters into a temporal-based parameterization, where the prior constraint provided by a hand poser network, is introduced to ensure that hand pose is natural and reasonable throughout the trajectory. Finally, we present a joint target optimization strategy to enhance the target pose for more feasible trajectories. Extensive validations on two public datasets show that our method outperforms state-of-the-art methods regarding grasp motion on various metrics.

关键词： Measurement Employment Optimization methods Grasping Planning Robotics and automation Grippers

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Detection Algorithm of Gastric Mucosal Atrophic Lesions under Gastroscopy Based on Deep Learning

Detection Algorithm of Gastric Mucosal Atrophic Lesions unde...

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第35届中国过程控制会议

作者： Yining Zhao Xiaolei Guo Xinao Jin Yuqi Cao Guangxin Zhang Yuehua Han State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Department of Gastroenterology the Second Affiliated Hospital Zhejiang University School of Medicine

Autoimmune gastritis(AIG) is a type of atrophic gastritis that is closely related to diseases including pernicious anemia, gastric adenocarcinoma and gastric neuroendocrine tumors. Gastroscopy is one of the most important tools for the diagnosis of AIG, and the most important lesion of AIG under gastroscopy is the high atrophy of the gastric mucosa, mainly in the body and fundus of stomach. However, the large number of gastroscopy images that need to be interpreted brings a large workload to doctors, which is not conducive to the efficient and accurate diagnosis of AIG. Therefore, we propose the multiscale Yolov5l(MS-Yolov5l) for gastric mucosal atrophic lesions to realize automated assisted diagnosis of AIG. For the problems of uneven brightness and noise in gastroscopy images, CLAHE and Gaussian filter are used to process the images. Aiming at the multi-scale characteristics of gastric mucosal atrophy lesions, DAC block is used to improve the extraction ability of the model for multi-scale information. For the detection of gastric mucosal atrophy lesions, we obtained an AP value of 0.744 and a recall value of 0.950. The study shows that the detection algorithm based on deep learning is capable of extracting gastric mucosal atrophic lesions in gastroscopy images, which is of great practical value for the further development of automated diagnosis and auxiliary diagnosis for AIG.

关键词： Medical Images Processing Autoimmune Gastritis Lesion Detection Deep Learning

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An Improved Data-Driven Adaptive Dynamic Programming Approach for Cooperative Games 42

An Improved Data-Driven Adaptive Dynamic Programming Approac...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yi-Min Sun, Tao Ma, Song He, Lei-Ming Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tsinghua University Department of Automation Beijing100084 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China Chinese Aeronautical Establishment Beijing100029 China

ISBN: (纸本)9789887581543

In this paper, we consider a continuous system cooperative dynamic game problem with two players. Through the introduction of dynamic programming concept, a Hamilton-jacobi-Belman equation for two players is designed. By introducing detection noises and using the basis function approximation method, a data-driven adaptive dynamic programming method is proposed and an iterative equation is obtained. Then, by introducing two detection noises and using the basis function approximation method, an iterative equation is obtained. It is note-worthy that we can obtain the Nash equilibrium solution of the cooperative game. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed adaptive dynamic programming approach. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Dynamic programming

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