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SSRN 2023年

作者： Zhang, Zhuopei Feng, Yange Feng, Min Du, Changhe Zhang, Liqiang Li, Wanting Yu, Tongtong Wang, Daoai State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical Physics Chinese Academy of Sciences Lanzhou730000 China Center of Materials Sciences and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Qingdao Center of Resource Chemistry and New Materials Qingdao266104 China Shandong Laboratory of Advanced Materials and Green Manufacturing Yantai Yantai264000 China

As a new and promising energy utilization device, triboelectric nanogenerators (TENGs) still have output performance limitations due to electrode design in some practical application aspects. In this research paper, the influence of component composition, thickness, and surface morphology of the metal conducting layer on the performance of triboelectric nanogenerators were systematically investigate. It has been established that these three factors exert a substantial impact on the output performance of TENGs. Among the four common metals of Au, Pt, Ag and Cu, the triboelectric nanogenerator obtains the highest output when Ag is used as the conducting layer, which are nearly twice as the output of Au. It is found that the maximum output is obtained when the thickness of silver is about 278 nm. In addition, when endowing the conducting layer with nanostructures, the inductive electrification area increases, the output of TENG can also be effectively enhanced. Especially when compared with the triboelectric nanogenerator with copper foil as the conducting layer and polyvinylidene difluoride and nylon 11 as the friction layers in the common work, the short-circuit current of the triboelectric nanogenerator increased by 2.3 times and the maximum short-circuit current reached 149 μA when the conducting layer was replaced with Ag. The maximum output power can reach 9.52 mW when the load resistance is 2 MΩ and the enhanced triboelectric nanogenerator can light up 1536 commercial LEDs while driven by a linear motor. This study provides a new simple and reliable method for enhancing the output of TENG. © 2023, The Authors. All rights reserved.

关键词： Nanogenerators

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Structural Design of Mos2-Cu Films to Improve Thermal and Tribological Properties of Silicon Nitride Materials

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SSRN 2024年

作者： Zhang, Xiaochen Liang, Jiaqi Bai, Xu Wang, Xiaolong Wu, Yuhou Zhang, Ke Zheng, Tongxiang Zhao, Zichen School of mechanical engineering Shenyang Jianzhu University No. 25 Hunnan Middle Road Hunnan District Shenyang110168 China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Shenyang110819 China Key Laboratory of Fundamental Science for National Defense of Aeronautical Digital Manufacturing Process of Shenyang Aerospace University Shenyang110135 China School of Mechanical Engineering Shenyang University of Technology No.111 Shenliao West Road Economic & Technological Development Zone Shenyang110870 China National-Local Joint Engineering Laboratory of NC Machining Equipment and Technology of High-Grade Stone Shenyang110168 China

In order to solve the problems of heat dissipation and insufficient wear resistance of silicon nitride materials during dry friction, a novel Ti/TiN/MoS2-Cu lubricated film was deposited on a silicon nitride substrate by magnetron sputtering. The results show that the Ti/TiN structure design promoted MoS2(002) crystal plane growth. Moderate Cu(20W) doping promoted film densification and reduced structural defects, resulting in films with high thermal conductivity and low wear rate. Excessive Cu(40W) doping enabled the films to have high hardness, but due to structural defects and elemental aggregation, the thermal conductivity and abrasion resistance of the films were reduced. The Ti/TiN structure and MoS2-Cu film design provide guidance to improve the thermal and tribological performance of silicon nitride materials. © 2024, The Authors. All rights reserved.

关键词： Friction

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Research on Deformation Law and Forming Accuracy of Dieless Single Point Incremental Forming Based on Machine Vision

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SSRN 2022年

作者： Li, Yan Pang, Qiu Hu, Zhi-Li Hubei Key Laboratory of Advanced Technology of Automobile Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology 430070 China Hubei Research Center for New Energy & Intelligent Connected Vehicle Wuhan University of Technology Wuhan430070 China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China

Dieless single point incremental forming is very suitable for individual and small batch processing, due to its advantages of high flexibility and low cost. However, it has always been difficult to control the surface quality and geometric accuracy of the part. In this paper, a dieless single point incremental forming device based on machine vision is designed to study the deformation law of parts and the evolution law of forming accuracy under different process parameters. The results show that the defects of wrinkle, fracture, discontinuous outer contour and poor geometric accuracy are easy to appear in the dieless single point incremental forming. A high accuracy multi-pass single point incremental forming model based on machine vision is established. In this model, the contour data of the part is obtained online, and the relationship between the toolpath and the actual contour is fitted by neural network in the multi-pass forming, then the forming toolpath is automatically optimized. By combining with the ring washer to constrain the deformation of the material, problems of discontinuous outer contour and poor geometric accuracy of the part are solved. Finally, the deviation is controlled within 0.5mm, and high efficiency and high accuracy incremental forming is achieved. © 2022, The Authors. All rights reserved.

关键词： Surface properties

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Time-Domain Transfer Path Analysis Based on Gaussian Process Latent Force Model and Least Squares

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SSRN 2024年

作者： Zhu, Yu He, Zhicheng Zhou, Enlin L. Li, Eric Chen, Y.J. Gao, H. State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha410082 China School of Computing Engineering & Digital Technologies Teesside University Middlesbrough United Kingdom Chinese Scholartree Ridge Laboratory China North Vehicle Research Institute Beijing100072 China Liuzhou Wuling New Energy Vehicle Co. Ltd. Guangxi Automobile Group Co. Ltd. Liuzhou545005 China

The appearance of Time-domain transfer path analysis (TPA) has provided an effective means for addressing the issues of noise, vibration, and harshness (NVH) in mechanical systems under transient conditions. However, two primary challenges exist with this approach. Firstly, computing the generalized inverse of the frequency response functions (FRFs) matrix from excitations to indicators is prone to numerical instabilities, leading to ill-conditioned problems. Secondly, the accuracy of time-domain information extracted from existing frequency-domain data is relatively low. These issues diminish the precision of classical time-domain TPA methods in time-domain loads identification and impulse response functions (IRFs) recognition, thereby affecting their accuracy. In this work, we propose a novel time-domain TPA method that integrates the gaussian process latent force model (GPLFM) with the least squares (LS). Initially, this method explores the GPLFM in fluid-structure interaction (FSI) system. Secondly, a genetic algorithm (GA) is utilized to determine optimal parameters of the indicators. Subsequently, the vibration IRFs are identified using the LS. Finally, the contribution of each path to the targets' vibration is calculated using linear convolution, while a Kalman filter without measurement updates predicts the noise contribution. Case studies have demonstrated that the proposed method achieved higher accuracy in time-domain loads identification under multiple loading conditions compared to traditional methods using deconvolution filters. Additionally, the accuracy of calculating the contributions surpasses that of traditional methods employing linear convolution. © 2024, The Authors. All rights reserved.

关键词： Genetic algorithms

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Investigation on Material Removal of the Sub-Aperture Tool Used for Polishing Riblet Surfaces

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SSRN 2022年

作者： Wang, Guilian Lv, Bingrui Liu, Bin Fang, Fengzhou Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China School of Mechanical and Materials Engineering University College Dublin Belfield D04 V1W8 Ireland Key Laboratory of Advanced Ceramics and Machining Technology Ministry of Education Tianjin University Tianjin300072 China Tianjin Laboratory of Control Theory and Applications in Complicated System School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin 300384 China Tianjin University Tianjin 300072 China

Riblet surfaces find wide applications owing to their excellent performance such as drag reduction. In this study, sub-aperture tool is investigated to polish the riblet surfaces, two main different curvatures at any point of this kind of tool surface are proposed. A series of simulation studies are conducted to investigate the effect of key parameters on the material removal, such as tool radius, inclination angle, polishing pressure, and tool speed. The results show that a higher difference between the tool radius values in two directions increases the difference between the major and minor axes of the contact area. Based on experimental tests and simulation analysis, it is conluded that the profile and depth of material removal distribution both increase with an increase in polishing pressure, the material removal profile remains constant but the removal detpth increases with an increase in polishing speed, and the parameter K is a time-dependent. © 2022, The Authors. All rights reserved.

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Disturbance Rejection for Pedaling Rehabilitation Robot Based on Integration of Equivalent-Input-Disturbance and Repetitive control Methods

Disturbance Rejection for Pedaling Rehabilitation Robot Base...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Yujian Zhou Jinhua She Feng Wang Makoto Iwasaki School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Department of Electrical and Mechanical Engineering Nagoya Institute of Technology Nagoya Japan

This study integrated an improved equivalent-input-disturbance (EID) and a repetitive control methods to ensure reference tracking and enhance disturbance-rejection performance for a pedaling rehabilitation robot. A repetitive controller ensures steady-state tracking of a periodic reference input. An EID estimator with a state observer estimates and compensates for the effect of disturbances generated by patients with lower-limb impairment. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show the effectiveness of this method.

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BodyFormer: Semantics-guided 3D Body Gesture Synthesis with Transformer

arXiv

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arXiv 2023年

作者： Pang, Kunkun Qin, Dafei Fan, Yingruo Habekost, Julian Shiratori, Takaaki Yamagishi, Junichi Komura, Taku Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing Guangdong Academy of Sciences China The University of Hong Kong Hong Kong The University of Edinburgh United Kingdom Meta Reality Labs Research United States National Institute of Informatics Japan Research Institute of Electrical Communication Tohoku University Japan

Automatic gesture synthesis from speech is a topic that has attracted researchers for applications in remote communication, video games and Meta-verse. Learning the mapping between speech and 3D full-body gestures is difficult due to the stochastic nature of the problem and the lack of a rich cross-modal dataset that is needed for training. In this paper, we propose a novel transformer-based framework for automatic 3D body gesture synthesis from speech. To learn the stochastic nature of the body gesture during speech, we propose a variational transformer to effectively model a probabilistic distribution over gestures, which can produce diverse gestures during inference. Furthermore, we introduce a mode positional embedding layer to capture the different motion speeds in different speaking modes. To cope with the scarcity of data, we design an intra-modal pre-training scheme that can learn the complex mapping between the speech and the 3D gesture from a limited amount of data. Our system is trained with either the Trinity speech-gesture dataset or the Talking With Hands 16.2M dataset. The results show that our system can produce more realistic, appropriate, and diverse body gestures compared to existing state-of-the-art approaches. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep learning

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Review of key technology and Latest Research Progress of Deflector Jet Servo Valve

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Recent Patents on Engineering 2025年

作者： Li, Jianying Guo, Qi Wang, Yaqian Zhang, Xiaoqiu Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin150080 China School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China

The deflector jet servo valve has the advantages of strong anti-pollution ability, high reliability and better dynamic performance, so it is widely used in aviation, military and other fields. The research on deflector jet servo valve theory and production is not yet mature. It is expected that through the collation and analysis of the existing data, the method of improving the performance of this kind of valve will be obtained, which will provide the basis for future research and development. By summarizing the research status of the static and dynamic characteristics, pre-stage optimization, mathematical modeling and other parts of the deflector jet servo valve, the technical points and development rules are obtained. By sorting out the relevant patent information in recent years, the vacancy in the patent analysis of the deflector jet servo valve is filled. Based on the summary of the research status of the deflector jet servo valve, combined with the summary of the research status of the deflector jet servo valve, it is pointed out that there are few studies on the performance of deflector jet servo valve under cavitation, noise and extreme temperature. These parameters are of great significance to improve the performance of servo valve, which will be an important research direction in the future. The research status and development trend of the deflector jet servo valve are summarized and analyzed, and various methods that can improve the performance of the servo valve are described, which is of great significance for the subsequent performance improvement and in-depth study of such valves. © 2024 Bentham Science Publishers.

关键词： Analytical models

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Explainable Deep Learning for Semg-Based Similar Gesture Recognition: A Shapley-Value-Based Solution

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SSRN 2023年

作者： Wang, Feng Ao, Xiaohu Wu, Min Kawata, Seiichi She, Jinhua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo192-0982 Japan

Surface electromyography (sEMG) based gesture recognition shows promise in enhancing human-robot interaction. However, accurately recognizing similar gestures is a challenging task, and the underlying mechanisms of gesture recognition are not well understood. To address these issues, we developed a new solution called the Shapley-value-based similar gesture recognition (SV-SGR) method. Our solution combines deep learning and game theory to achieve high recognition accuracy and interpretability. First, we devised a data preprocessing method that converts sEMG signals into sEMG color images, which can be more effectively utilized by deep learning techniques. Next, we established a deep-neural-network-based model for gesture recognition using the processed sEMG color images. Then, we designed a global explanation approach based on Shapley values to quantify the contribution of each channel to recognizing similar gestures. Finally, we carried out an explanation analysis, which provides feedback on the recognition model to enhance the precision of gesture recognition. Extensive comparisons and interpretable analyses have been conducted on real-world datasets, and the results demonstrate that the SV-SGR method outperforms other baselines under various experimental conditions. The interpretable analysis method based on Shapley values effectively enhances the performance of recognizing similar gestures and provides valuable insights into the decision-making process of recognition models. © 2023, The Authors. All rights reserved.

关键词： Gesture recognition

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Application of Johnson-Cook Model in Failure Simulation for Steel-Aluminium Hybrid Spr Joint Under Dynamic Loading

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SSRN 2022年

作者： Duan, Libin Xue, Kaiwen Du, Zhanpeng Ma, Hongfeng Li, Wen Su, Yulong Institute of Lightweight and Safety of New Energy Vehicle School of Automotive and Traffic Engineering Jiangsu University Zhenjiang212013 China Jiangsu XCMG State Key Laboratory Technology Co. Ltd. Xuzhou221001 China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China

Steel-aluminium hybrid material is the main development direction of body material combination. This paper aims to investigate the failure behaviour of high-strength steel B280VK and aluminum alloy 6063-T6. First, the parameters of Johnson-Cook (J-C) material model (i.e. J-C constitutive and failure model) are experimentally obtained by conducted uniaxial and notch tensile tests at five constant loading speeds of 3mm/min, 1.25 m/s, 2.5 m/s and 7.5 m/s. Then, numerical simulation of different tensile tests on B280VK and 6063-T6 specimens has been done in commercial software LS-DYNA using J-C material model. The results reveal that the established J-C material model can accurately simulate the mechanical performance and failure behaviour of high-strength steel B280VK and aluminum alloy 6063-T6. Finally, the J-C material model is used to simulate the failure behaviour of self-piercing riveting (SPR) joint with steel-aluminium hybrid material under dynamic loading. By comparing the numerical results with those of the experiment results, it can be found that the established J-C material model can describe the deformation and failure behaviour of steel-aluminium hybrid SPR joint well. © 2022, The Authors. All rights reserved.

关键词： Tensile testing

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