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Constructing nitrided aluminum metal skeleton to improve the reversibility and cyclicity of Si film electrode

Progress in Natural Science:Materials International 2023年第6期33卷 789-796页

作者： Jiali Tong Tingfeng Guan Qilin Tong Yan Cheng Zhaozhe Yu Guangxi Key Laboratory of Manufacturing Systems and Advanced Manufacturing Technology Guilin University of Electronic Technology

Silicon is a promising anode material for lithium-ion batteries（LIBs） due to its high theoretical capacity, low discharge potential, environmental friendliness and cost-effectiveness. However, its low conductivity, high volume variation and poor cycling performance hamper its practical application. Herein, we prepare Si-Al（Al N）composite film anodes containing a nitrided aluminum metal conductive skeleton. The Al（Al N） creates a multiphase interface, buffers the volume expansion of the electrode, and also plays a role in conducting electricity and supporting the electrode structure. As a result, the Si-Al（Al N） electrode exhibits excellent performance with a high initial coulombic efficiency of 86 %, an outstanding cycling stability of roughly 1955 m Ah g-1after 200 cycles at420 m A g-1and retains 916 m Ah g-1after 300 cycles even at 4200 m A g-1（the capacity retention rate of 83 %）.This work provides an effective method for adjusting anode performance with greater freedom.

关键词： Silicon film anode Nitrided aluminum metal conducting skeleton Cycling stability Lithium-ion battery

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Automatic control of Magnetic Helical Microrobots Docking with Target Objects in Liquid Environments

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Journal of Bionic Engineering 2025年第2期22卷 574-584页

作者： Fu Zhao Haoran Rong Lefeng Wang State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin150080China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin150080China

Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for helical microrobots to perform various tasks. In this study, an automatic control method is proposed to realize the axial docking of helical microrobots with arbitrarily placed cylindrical objects in liquid environments. The docking process is divided into ascent, approach, alignment, and insertion stages. First, a 3D docking path is planned according to the positions and orientations of the microrobot and the target object. Second, a steering-based 3D path-following controller guides the helical microrobot to rise away from the container bottom and approach the target along the path. Third, based on path design with gravity compensation and steering output limits, alignment of position and orientation can be accomplished simultaneously. Finally, the helical microrobot completes the docking under the rotating magnetic field along the target orientation. Experiments verified the automatic docking of the helical microrobot with static targets, including connecting with micro-shafts and inserting into micro-tubes. The object grasping of a reconfigurable helical microrobot aided by 3D automatic docking was also demonstrated. This method enables precise docking of helical microrobots with objects, which might be used for capture and sampling, in vivo navigation control, and functional assembly of microrobots.

关键词： Magnetic actuation Helical microrobots Visual servo Motion control Docking

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A mechanism-data hybrid-driven modeling method for predicting machine tool-cutting energy consumption

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Advances in manufacturing 2025年第1期13卷 167-195页

作者： Yue Meng Sheng-Ming Dong Xin-Sheng Sun Shi-Liang Wei Xian-Li Liu Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin150080People’s Republic of China

High-quality development in the manufacturing industry is often accompanied by high energy *** accurate prediction of the energy consumption of computer numerical control(CNC)machine tools,which plays a vital role in manufacturing,is of great importance in energy ***,the existing research ignores the impact of multi-factor energy losses on the performance of machine tool energy consumption prediction *** existing models must be selected and verified several times to determine the appropriate ***,in this study,a machine tool energy consumption prediction method based on a mechanism and data-driven model that considers multi-factor energy losses and hyperparameter dynamic self-optimization is proposed to improve the accuracy and reduce the difficulty of hyperparameter *** proposed multi-factor energy-loss prediction model is based on the theoretical prediction model of machine-tool cutting energy *** creating the model,a hyperparameter search space embedding a tree-structured Parzen estimator(TPE)was designed based on Hyperopt to dynamically self-optimize the hyperparameters in the deep neural network(DNN)***,two sets of experiments were designed for verification and comparison with the theoretical and data *** results showed that the energy consumption prediction performances of the proposed hybrid model in the two sets of experiments were 99% and 97%.

关键词： Mechanism-data hybrid-driven Cutting energy consumption Hyperopt Hyperparameters tuning

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Structural Design and Dynamic Characteristic Analysis of Short-column Micro Piezoelectric Power Actuator

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Recent Patents on Mechanical Engineering 2024年第2期17卷 143-156页

作者： Li, Huaiyong Gao, Shijie Chen, Zhong Yin, Yonghua Jiangsu Key Laboratory of Advanced Manufacturing Technology Huaiyin Institute of Technology Jiangsu Huai’an China

Background: With the rapid development of science and technology, industrial prod-ucts continue to develop towards the direction of lightweight and miniaturization, and the demand for power sources to drive micromachinery is increasing, so the patents related to microactuators are also increasingly valued. The microactuator based on a piezoelectric drive converts the deformation energy of the piezoelectric body into the kinetic energy of the transmission mechanism to drive the output shaft rotation. The stator and the rotor of the existing actuator are the surface contact with a certain preload force. After working for a long time, the contact surface will be lost due to friction, which will reduce the response speed and rotation accuracy and even cause the rotor to slip, affecting the actuator operating life. Objective: In order to solve the above technical problems, the author innovates the driving mode between stator and rotor and proposes a novel short-column micro piezoelectric actuator based on multi-tooth alternating meshing transmission. Methods: Firstly, the structure and operating principle of short-column micro piezoelectric power actuator, which can realize linear motion into rotary motion, and has three main advantages: com-pactness in size, multi-tooth meshing drive and large driving torque, are proposed and elucidated. Secondly, the structure size of each component of the actuator is determined to complete the 3D structure design. Thirdly, the modal analysis and the harmonic response analysis of the actuator are studied. The frequency range of the sawtooth wave voltage excitation signal applied to the actuator is determined. Finally, the prototype is made, and the performance test is carried out. Results: In this paper, a micro piezoelectric power actuator different from the existing patent is proposed, which is assembled by a drive module, a transmission module, an elastic element, an output shaft, a base module and a shell. The results show that whe

关键词： Stators

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Advancing electrochemical drilling process via coupling of flow field and electric field in pulsating state generated by a novel tube tool

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Chinese Journal of Aeronautics 2024年第4期37卷 542-555页

作者： Liang CHENG Xiaolei CHEN Zhisen YE Yongjun ZHANG State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of TechnologyGuangzhou 510006China Guangdong Key Laboratory of Advanced Manufacturing Technology of Marine Energy Equipment Guangdong University of TechnologyGuangzhou 510006China Guangzhou Key Laboratory of Nontraditional Machining and Equipment Guangdong University of TechnologyGuangzhou 510006China

This paper introduces an improvement to electrochemical drilling process by coupling flow field and electric field in pulsating state. A novel tube with half-wedged shape at the end(HW-tube) is prepared, with both sidewall and wedged part of the HW-tube insulated. Only the flat part is utilized to provide electric field for electrochemical drilling. By rotating the HW-tube, both flow field and electric field in pulsating state are generated, alternating in different positions within the inter-electrode gap(IEG). The pulsating flow field enhances the mass transfer process, while pulsating electric field disperses material dissolution process and distribution of electrolytic byproducts. Both pulsating fields are coupled at the same frequency, further enhancing the electrochemical drilling process. Simulation results indicate that both flow field and electric field in pulsating state are generated. Compared to the traditional tube, the HW-tube significantly reduces the number of residual particles in IEG, and this number is further reduced by increasing the rotation speed. Experimental results reveal that the surface quality and dimensional uniformity of small hole are improved with HW-tube. With feed rate of 2.22 mm/min, a small hole with diameter of 1.52± 0.017 mm is drilled, resulting in a surface roughness of 0.331 μm.

关键词： Small holes Electrochemical drilling Tools Pulsating flow field Pulsating electric field

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Design and Optimization Analysis of an Adaptive Knee Exoskeleton

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Chinese Journal of Mechanical Engineering 2024年第5期37卷 387-408页

作者： Xinhua Yang Sheng Guo Peiyi Wang Yifan Wu Lianzheng Niu Duxin Liu School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control TechnologyMinistry of EducationBeijing Jiaotong UniversityBeijing 100044China

To solve the problem of undesired relative motion of human-machine interaction positions caused by misalignment of the human-machine joints rotation axis of the knee exoskeleton,this study designed an adaptive knee exoskeleton based on a gear-link mechanism(GLM)by considering the human body as a component of the exoskeleton ***,the concept of the wearable area(WA)was proposed,which transformed the operation of aligning the exoskeleton rotation axis with the human knee joint rotation axis into a"face alignment point"in the sagittal plane,reducing the difficulty of aligning the human-machine joint rotation *** the kinematic analysis of GLM,the phenomenon of instantaneous movement of the central axis of the human knee joint was *** on the kinematic model,the WA,velocity transfer ratio,and initial position static stiffness of GLM were *** NSGA-II optimization algorithm was used to optimize the size parameters of GLM,which increased the WA by 18.4%,the average velocity transfer ratio by 4.98%,and the average initial position static stiffness by 6.01%.Finally,the ability of the exoskeleton to absorb movement displacement(MD)was verified through simulation,and the good human-machine kinematic compatibility of the exoskeleton was verified through wearable tests conducted on the initial mechanism principle prototype.

关键词： Adaptive knee exoskeleton Gear-link mechanism Wearable area Optimization Simulation

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Multiscale Facial Expression Recognition Based on Dynamic Global and Static Local Attention

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IEEE Transactions on Affective Computing 2024年第2期16卷 683-696页

作者： Xu, Jie Li, Yang Yang, Guanci He, Ling Luo, Kexin Guizhou University Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education Guiyang China

To better characterize the differences in category features in Facial Expression Recognition (FER) tasks, and improve inter-class separability and intra-class compactness, we propose a Multiscale Facial Expression Recognition model based on dynamic global and static local attention (MFER) from the perspectives of intra-class and inter-class features. Firstly, we propose Dynamic global and Static local attention (DS Attention) mechanism that fuse contextual information, learn potential regions of global and local features between different expression categories, and represent feature discrepancies between categories to distinguish between different expression categories. Then, we design a Deep Smooth Feature loss function (DSF) to balance the probability difference of encoded intra-class features and promote intra-class features towards corresponding centers. Finally, we construct a Multiscale classifier method (Msc) to learn high-frequency and low-frequency information in the dimensional space, represent deep features of multiscale dimensional space, and alleviate sparse distribution problems in high-dimensional space. Experimental results on public datasets RAF-DB, AffectNet-7, AffectNet-8, and FERPlus show that the proposed model achieves state-of-the-art performance with recognition accuracies of 92.08%, 67.06%, 63.15%, and 91.09%, respectively. Code available at https://***/XuJ1E/MFER/. © 2024 IEEE.

关键词： Face recognition

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IZOA: Multi-strategy improved zebra optimization algorithm and its engineering applications

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Journal of Intelligent and Fuzzy Systems 2024年第5-6期47卷 517-542页

作者： Wang, Xianlong Chen, Jiadui He, Ling Liu, Dan Yang, Kai Fu, Youfa Key Laboratory of Advanced Manufacturing Technology Ministry of Education Guizhou University Guiyang China

The Zebra Optimization Algorithm (ZOA) mimics the social behavior of zebras and is susceptible to the interference of local optimal solutions, leading to poor optimization and premature convergence. In this paper, we propose an improved zebra optimization algorithm (IZOA) that integrates several advanced strategies to overcome these problems. First, IZOA introduces a Lévy flight strategy in the foraging phase of the zebra population to expand the search range and improve the quality of individuals. At the same time, the 'PZ' mechanism updates the other individuals based on the value of the leading zebra in each generation, which accelerates the optimization process and improves the searching ability. In addition, IZOA integrates a nonlinear convergence factor based on the COS function, which improves the convergence speed and balances the exploration and development phases. A Cauchy variation strategy is used to enhance the global search capability and help the population escape from local extremes. In CEC2017 and CEC2022 benchmarking and rolling bearing design applications, IZOA is compared with 12 mainstream and improved ZOA algorithms (CZOA and IIZOA), and shows better performance. Finally, IZOA is combined with LSTM network for wind power prediction to show its application advantages in real engineering design problems. © 2024 - IOS Press. All rights reserved.

关键词： Windmill

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

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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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Review of rolling bearings performance degradation trend prediction

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Noise and Vibration Worldwide 2024年第11期55卷 585-604页

作者： Wang, Yaping Lu, Kaiting Dong, Renquan Fan, Yuqi Jiang, Xudong Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin China

Rolling bearings are widely used in rotating machinery in modern industry, and ensuring their stability during operation is one of the prerequisites for the overall safety of the equipment. Predicting performance degradation can play a key role in preventing accidents and extending equipment life. With the development of big data and deep learning, more trend prediction methods are emerging in the field of performance degradation prediction of rolling bearings. Therefore, this paper reviews the evaluation indicators and performance degradation prediction models for rolling bearing performance degradation prediction. The advantages and disadvantages of physical degradation indicators, and virtual degradation indicators are analyzed. It is presented to utilize the powerful feature self-extraction ability and nonlinear function characterization ability of deep learning methods to construct bearing evaluation indicators. It also analyzes the research progress of traditional performance degradation prediction models and deep learning prediction models. In this review, future developments in rolling bearing performance degradation prediction are summarized in this paper as deep learning-based, digital twin correlation, high dimensionality, and adaptive, which guide researchers and practitioners to effectively identify suitable performance degradation prediction models. © The Author(s) 2024.

关键词： Prediction models

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