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SSRN 2024年

作者： Darayen, Jidsucha Ploypech, Suwat Metzner, Martin Santos, Claudia Beatriz dos Jearanaisilawong, Petch Boonyongmaneerat, Yuttanant Nanoscience and Technology Graduate School Chulalongkorn University Bangkok Thailand Fraunhofer Institute for Manufacturing Engineering and Automation Stuttgart Germany Department of Mechanical and Aerospace Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Surface Coating Technology for Metals and Materials Research Unit Metallurgy and Materials Science Research Institute Chulalongkorn University Bangkok Thailand Faculty of Engineering Thammasat University Klong Nueng Klong Luang Pathumthani Thailand

This research explores the relationship between electrodeposition parameters, particularly tungsten content and current density, and the resulting properties of NiW coatings. Increased tungsten content systematically raises microcrack density, which enhances surface wettability by acting as lubricant reservoirs. The unique microstructure of NiW coatings, characterized by high crack density, also delivers exceptional wear resistance in both dry and wet conditions. As a potential alternative to conventional Cr coatings, NiW coatings offer superior performance and durability. This study highlights the importance of optimizing tungsten content and crack density to maximize the benefits of NiW coatings for advanced, wear-resistant applications. © 2024, The Authors. All rights reserved.

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A Novel Variable Stiffness Actuator Based on a Rocker-Linked Epicyclic Gear Train

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SSRN 2022年

作者： Li, Zhisen Xu, Peng Huang, Hailin Ning, Yinghao Li, Bing State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Zhengzhou Electromechanical Engineering Research Institute Zhengzhou450015 China

This paper presents a novel variable stiffness actuator based on a rocker-linked epicyclic gear train (REGT-VSA). The stiffness adjustment principle of the actuator is to change the lever ratio of force by converting the differential motion of the planetary gear train into the linear motion of the elastic element. The unique design of the rocker-linked epicyclic gear train ensures the compactness of structure and the accuracy of transmission. The simultaneous relocations of the pivot and torsion spring permit a wide-range stiffness adjustment. By introducing a linear guide and a cam follower, the internal friction is reduced, and the energy efficiency is improved. A prototype and its trajectory tracking controller are developed to evaluate the performance of REGT-VSA. An exponential function is used to train the neuron proportion coefficient of the conventional single-neuron adaptive PID (proportional-integral-derivative) controller to compensate for the hysteresis of elastic elements, thus creating the dynamic single-neuron adaptive PID controller. The stiffness identification and trajectory tracking experiments under different conditions prove the feasibility of the actuator and the proposed algorithm. © 2022, The Authors. All rights reserved.

关键词： Proportional control systems

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The DRTS-Net Framework: Enhanced Probabilistic Health Perception for Wind Turbine Bearings Under Complex Operating Conditions With Improved Interpretability

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Yang, Tongguang Li, Guanchen Huo, Jinzhao Li, Xiaoyong Zhou, Xianwen Han, Qingkai Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China Johns Hopkins University Department of Mechanical Engineering BaltimoreMD21218 United States Foshan University School of Mechatronic Engineering and Automation Foshan528225 China SCNU Environmental Research Institute Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety MOE Key Laboratory of Theoretical Chemistry of Environment South China Normal University School of Environment Guangzhou510006 China SCNU Qingyuan Institute of Science and Technology Innovation Company Ltd. Qingyuan511517 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Shenyang110819 China

Health perception in mechanical systems is a crucial aspect of prognostics and health management (PHM). Deep learning models have been successfully applied to health perception in wind turbine bearings. However, due to the time-varying, redundant, and noisy characteristics of time-series data representing bearing wear, existing models face significant challenges, particularly in terms of generalization and interpretability. Moreover, although most current models have provided health perceptions, they overlook the strong stochastic nature of bearing degradation data, and thus fail to deliver reliable predictions of uncertainty information. To address these technical challenges, this study introduces a novel Deep residual temporal-spatial framework (DRTS-Net) for probabilistic health perception of wind turbine bearing wear states. This article creatively designs spatiotemporal information fusion module for extracting features from bearing degradation data. Inspired by improvements in residual network structures, the DRTS-Net integrates an attention mechanism and a soft thresholding mechanism from the deep residual shrinkage network to optimize the feature extraction process. This integration aims to mitigate the interference from minor redundant features in the degradation data. The framework incorporates Gaussian process regression in the output layer to yield the probability distribution of single-health perception values for bearing features. A comparative study was conducted using the same bearing health state dataset against current mainstream deep learning methods for bearing health assessment. Results demonstrate that the proposed DRTS-Net achieves superior performance in high-precision health perception, high-reliability probabilistic health perception. © 1963-2012 IEEE.

关键词： Stochastic systems

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Durable Ag-Coated Micro-Crack Velcro Electrode for Hi-Fi Bioelectric Signals in Hairy Areas

Durable Ag-Coated Micro-Crack Velcro Electrode for Hi-Fi Bio...

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IEEE International Conference on Micro Electro mechanical systems

作者： Jun Guo Kang Fu Zimo Zhang Ruiyu Bai Xuanqi Wang Kai Xue Huazhen Chen Le Li Huijing Hu Minghao Wang Honglong Chang Bowen Ji Unmanned System Research Institute Northwestern Polytechnical University China National Key Laboratory of Unmanned Aerial Vehicle Technology Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology Northwestern Polytechnical University China Ministry of Education Key Laboratory of Micro/Nano Systems for Aerospace School of Mechanical Engineering Northwestern Polytechnical University China Institute of Medical Research Northwestern Polytechnical University China MOE Engineering Research Center of Smart Microsensors and Microsystems College of Electronics and Information Hangzhou Dianzi University China

ISBN: (数字)9798331508890

ISBN: (纸本)9798331508906

This paper reports a conductive Velcro electrode with micro-cracks for the first time. The laser-induced micro-cracks increase the surface area of Velcro hooks and facilitate the adhesion of more silver particles. A cluster of Nylon-Ag hook are durable with repeated mechanical compression and multiple washing. After 100 times of compression, the plastic deformation is less than 23 μm (<10%). The impedance (@10 Hz) of the Velcro electrode is still 2.6% lower than the AgCl electrode after washing for 3 times. The resilient conductive hooks can effectively penetrate through thick hair for hi-fi bioelectric signal acquisition, compared with commercial AgCl electrodes.

关键词： Electrodes Hair Micromechanical devices Surface impedance Silver Deformation Adhesives Surface emitting lasers Plastics Impedance

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On disturbance rejection control for nonlinear three-revolute prismatic spherical ball and plate systems

Advanced Control for Applications: Engineering and Industria...

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Advanced Control for Applications: engineering and Industrial systems 2021年第2期3卷

作者： Cai, Tao Dong, Zhenye Liu, Xinning School of Automation Beijing Institute of Technology Beijing China Beijing Aerospace UAV System Engineering Research Institute Beijing China Systems Engineering Research Institute of China State Shipbuilding Corporation Beijing China

The three-revolute prismatic spherical ball and plate system (BP) is a typical complex nonlinear uncertain system involving axial coupling, friction, and other nonlinear factors. It is difficult to identify the model for each factor and isolate its effect from other factors. In addition to such challenge, the measurement noise, which is beyond the capability of many traditional closed-loop control methods, exists in the system. For this reason, an active disturbance-rejection control scheme combining linear tracking differentiator is presented to tackle the problems in the BP system. The simulation and real system test are conducted in response to point-to-point trajectories, circular and rectangular loci. The results demonstrate that fast response with small steady error can be achieved by the proposed control method. GTOC:The paper provide an active disturbance-rejection control scheme combining linear tracking differentiator for the BP system control, The simulation and real system test demonstrate that fast response with small steady error can be achieved by the proposed control method. © 2020 John Wiley & Sons, Ltd.

关键词： Disturbance rejection

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Deep convolutional neural network-based image processing for vision-based safe landing region recognition framework

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Journal of institute of Control, Robotics and systems 2021年第8期27卷 544-555页

作者： Cho, Sungwook Jung, Yeondeuk Major of Aeronautical and Mechanical Engineering Cheongju University Korea Republic of Unmanned Aircraft System Research Division Korea Aerospace Research Institute Korea Republic of

The UAM (Urban Air Mobility) industry is currently in the limelight. To adopt sustainable urban transport systems and contribute to the advancement of aerospace technology, the MOLIT (Ministry of Land, Infrastructure and Transport) of South Korea has developed the K-UAM (Korea Urban Air Mobility) roadmap by collaborating with industries and academia to lead research and development related to the emerged industry. To guarantee the high reliability of industrial-level autonomous flights in urban areas, high priority should be provided to observe flight safety and survivability measures. This paper proposes adopting DNN (Deep Neural Network) based image processing for a vision-based safe landing region recognition framework to satisfy research and development needs. This framework is one of the core elements of the flight contingency plan for UAM and drone transportation in urban environments. Our proposed algorithm can recognize the coarse candidate region to land safely by using a DNN and then determine the refined safety zone by using the contour detection algorithm. To verify the performance of the proposed contribution, a simulation was done and the results were analyzed. The findings proved to be valid with regard to both the quantitative and qualitative terms. Therefore, our proposed framework will not only overcome the image processing complexity of the real world but also improve the enhancement of the flight emergency relief performance. © ICROS 2021.

关键词： Air mobility

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Deep Learning EEG Technology Development and Brain Computer Interface Chips Progress

Deep Learning EEG Technology Development and Brain Computer ...

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Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Wenjie Li Lei Chen Bing Lv Xiaobo Li Weijun Wang Kun Xu Xilun Ding School of Mechanical Engineering and Automation Beihang University Beijing BJ P.R.China Beijing Microelectronics Technology Institute Beijing BJ P.R.China China Academy of Aerospace Electronics Technology Beijing BJ P.R.China Robotics Engineering Center The 21ST Research Institute of China Electronic Technology Group Corporation Shanghai China

ISBN: (数字)9798350374513

ISBN: (纸本)9798350374520

Brain Computer Interfaces establishes an interaction mode between the human brain and external devices, and has broad application prospects. With the development of neuroscience and artificial intelligence technology, brain computer interfaces have rapidly evolved from a single perception stage to a multimodal cognition and complex interaction control stage. This article elaborates on the functional zoning of the brain and cerebellum and the latest research on brain signal classification. Afterwards, the latest research progress of deep learning based EEG signal processing technology was analyzed in depth from three key directions: brain network analysis, research on neurological diseases, cognitive analysis, and emotion recognition. This paper provides a detailed description of the typical structure and main functional unit design ideas of Brain Computer Interface chips, and analyzes the core and difficult technologies from the aspects of acquisition, 3D heterogeneous integration, low-power design, software and brain science research. Finally, based on typical Brain Computer Interface design and application cases, the future development trends of Brain Computer Interface chips and deep learning EEG technology are proposed.

关键词： Deep learning Neurological diseases Three-dimensional displays Neuroscience Pattern classification Signal processing Brain-computer interfaces

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Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges

arXiv

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arXiv 2022年

作者： Liu, Qi Li, Xueyuan Li, Zirui Wu, Jingda Du, Guodong Gao, Xin Yang, Fan Yuan, Shihua School of Mechanical Engineering Beijing Institute of Technology Beijing China Chair of Traffic Process Automation "Friedrich List" Faculty of Transport and Traffic Sciences TU Dresden Germany School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore639798 Singapore Institute of Dynamic System and Control ETH Zurich Zurich Switzerland

Proper functioning of connected and automated vehicles (CAVs) is crucial for the safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous driving requires a long period of mixed autonomy traffic, including both CAVs and human-driven vehicles. Thus, collaboration decision-making for CAVs is essential to generate appropriate driving behaviors to enhance the safety and efficiency of mixed autonomy traffic. In recent years, deep reinforcement learning (DRL) has been widely used in solving decision-making problems. However, the existing DRL-based methods have been mainly focused on solving the decision-making of a single CAV. Using the existing DRL-based methods in mixed autonomy traffic cannot accurately represent the mutual effects of vehicles and model dynamic traffic environments. To address these shortcomings, this article proposes a graph reinforcement learning (GRL) approach for multi-agent decision-making of CAVs in mixed autonomy traffic. First, a generic and modular GRL framework is designed. Then, a systematic review of DRL and GRL methods is presented, focusing on the problems addressed in recent research. Moreover, a comparative study on different GRL methods is further proposed based on the designed framework to verify the effectiveness of GRL methods. Results show that the GRL methods can well optimize the performance of multi-agent decision-making for CAVs in mixed autonomy traffic compared to the DRL methods. Finally, challenges and future research directions are summarized. This study can provide a valuable research reference for solving the multi-agent decision-making problems of CAVs in mixed autonomy traffic and can promote the implementation of GRL-based methods into intelligent transportation systems. The source code of our work can be found at https://***/Jacklinkk/Graph_CAVs. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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Satellite-pose estimation using IMU sensor data and Kalman filter with RF-433 Mhz powered communication and helical antenna design for ground station

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Measurement: Sensors 2024年 35卷

作者： Paneru, Biplov Adhikari, Ankit Paneru, Bishwash Shah, Krishna Bikram Chhetri Sapkota, Sanjog Poudyal, Ramhari Poudyal, Khem Narayan Department of Electronics and Communication Engineering Nepal Engineering College Affiliated to Pokhara University Bhaktapur Nepal Department of Mechanical and Aerospace Engineering Institute of Engineering Pulchowk Campus Affiliated to Tribhuvan University Lalitpur Nepal Department of Applied Sciences and Chemical Engineering Institute of Engineering Pulchowk Campus Affiliated to Tribhuvan University Lalitpur Nepal Department of Computer Science Engineering Nepal Engineering College Affiliated to Pokhara University Nepal Nepal Research and Collaboration Center Nepal Department of Information System Engineering HIST Engineering College Affiliated to Purbanchal University Nepal

Space research relies heavily on satellites, and technological developments are critical to the success of these missions. In order to estimate satellite pose, a simulation of an IMU sensor using Matplotlib is presented in this study. A roll, pitch, and yaw value analysis is performed on data obtained from the BNO-055 IMU sensor. A prototype ground station's helical antenna is used to investigate these parameters. For effective communication between the satellite body and ground station setup, a low-cost transceiver module RF-433Mhz module is connected to the ground station. IMUsensors are essential for inertial measurements in spacecraft, which support ground station monitoring. This study makes use of a four-turn helical antenna that is built for deployment and designed using the 4nec2 simulation program for RF-based satellite-ground station communication. The antenna's VSWR is 1.432, and its directivity is 18.581. Matplotlib is utilized to model variations in roll, pitch, and yaw values. Roll, pitch, and yaw ranges that are observed are −0.375 to 0.25, −0.375 to 0.5625, and −0.3125 to 0.1875, in that order. These ranges are useful in effectively visualizing the body pose of the CubeSat when connecting via PySerial to a Matplotlib-developed program. © 2024 The Authors

关键词： Kalman filters

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An in Vitro Experimental Investigation of Oscillatory Flow in the Cerebral Aqueduct

SSRN

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SSRN 2023年

作者： Sincomb, Stephanie Moral-Pulido, Francisco Campos, Obed Martínez-Bazán, C. Haughton, Victor Sánchez, Antonio Luis Department of Aerospace and Mechanical Engineering University of California San Diego La Jolla CA92093-0411 United States Department of Mechanical and Mining Engineering University of Jaen Jaen23071 Spain Andalusian Institute for Earth System Research University of Jaen Jaen23071 Spain Department of Mechanics of Structures and Hydraulic Engineering University of Granada Granada18001 Spain Andalusian Institute for Earth System Research University of Granada Granada18006 Spain School of Medicine and Public Health University of Wisconsin-Madison MadisonWI53706 United States

This in vitro study aims at clarifying the relation between the oscillatory flow of cerebrospinal fluid (CSF) in the cerebral aqueduct and the interventricular pressure difference over the range of flow conditions commonly encountered in healthy subjects. Dimensional analysis is used in designing a scaled model of the aqueduct flow, with physical similarity maintained by adjusting the flow frequency and the properties of the working fluid. The experiments include an aqueduct model with an anatomically correct shape determined from high-resolution magnetic resonance imaging (MRI). A programmable pump is employed to generate the flow-rate signal, including a sinusoidal waveform and a complex waveform previously measured {\it in vivo} using phase-contrast (PC) MRI. The time-varying pressure difference across the aqueduct is measured in parametric ranges covering relevant frequencies and stroke volumes. The experimental measurements are presented in dimensionless form to provide the relation between the waveforms of the flow rate and transaqueductal pressure difference. Parametric dependences are delineated for the time-averaged pressure fluctuations and for the phase lag between the pressure gradient and the flow rate, both having clinical relevance. The results are validated through comparisons with predictions obtained with a previously derived computational model. The parametric quantification in this study enables the derivation of a simple formula for the relation between the transaqueductal pressure and the stroke volume. This relationship can be useful in the quantification of transmantle pressure differences based on non-invasive PC MRI measurements of aqueduct flow for investigation of CSF-related disorders. © 2023, The Authors. All rights reserved.

关键词： Cerebrospinal fluid

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