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International Conference on Advanced Robotics and mechatronics (ICARM)

作者： Jiyong Tan Hui Qin Xinxing Chen Jiawang Li Yuanwei Li Bing Li Yuquan Leng Chenglong Fu School of Mechatronics Engineering Harbin Institute of Technology Harbin China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China Guangdong Medical Rehabilitation Intelligent System Engineering Technology Research Center Shenzhen China

Automatic segmentation of the region of interest to be scanned (ROIS) is one of the key tasks to achieve autonomous scanning of ultrasound robots. By analyzing breast ROIS in an unstructured environment, a point cloud segmentation framework for the breast ultrasound ROIS that incorporates 2D image instance segmentation and keypoint detection is proposed. Firstly, 2D image instance segmentation based on the improved SOLOv2 is performed to extract the human torso point cloud in the unstructured environment. Then, based on YOLO-Pose, the keypoints of human body are automatically detected, and the upper and lower lines of breast ROIS are obtained according to the constraint matching relationship between breast ROIS and keypoints, and finally the point cloud of breast ROIS is obtained effectively and accurately. Experiments show that the proposed framework can achieve automatic segmentation of breast ROIS within 2 s.

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Examination of Thickness Measurement Method for Hot Spring Scale inside Steel Pipes using Electromagnetic Force Vibration

Examination of Thickness Measurement Method for Hot Spring S...

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IEEE Conference on Electromagnetic Field Computation

作者： Ryota Takasugi Shinya Shiota Hiroyuki Ikusada Shotaro Niwa Yanhui Gao Yuji Gotoh Dept. Mechatronics Engineering Graduate School of Engineering Oita University Oita Japan Dept. Mechanical Energy Engineering Graduate School of Engineering Oita University Oita Japan Dept. Intelligent Mechanical System Faculty of Science and Technology Oita University Oita Japan

ISBN: (数字)9798350348958

ISBN: (纸本)9798350348965

At geothermal power plants has a problem that the large-diameter steel pipe is blocked by solid material of hot spring water's components, called for “hot spring scale”. Therefore, it is necessary to develop a method for measuring the thickness of hot spring scale from the outside of large-diameter steel pipe. In this paper, we investigated a non-contact inspection method that uses electromagnetic force vibration to measure the thickness of hot spring scale from the outside of a steel pipe. In addition, the proposed inspection method was evaluated by comparing electromagnetic force and displacement analysis using the 3-D finite element method (FEM), and verification experiments.

关键词： Vibrations Force measurement Estimation Electromagnetic forces Inspection Vibration measurement Finite element analysis

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Static Force-Based Modeling and Parameter Estimation for a Deformable Link Composed of Passive Spherical Joints With Preload Forces

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IEEE/CAA Journal of Automatica Sinica 2021年第11期8卷 1817-1826页

作者： Gaofeng Li Dezhen Song Lei Sun Shan Xu Hongpeng Wang Jingtai Liu Nankai University Tianjin 300350China Humanoids and Human Centered Mechatronics Research Line Italian Institute of Technology16163 GenovaItaly Department of Computer Science and Engineering Texas A&M UniversityCollege StationTexas 77843 USA Institute of Robotics and Automatic Information System Nankai UniversityTianjin 300350China Tianjin Key Laboratory of Intelligent Robotics Nankai UniversityTianjin 300350China

To balance the contradiction between higher flexibility and heavier load bearing capacity,we present a novel deformable manipulator which is composed of active rigid joints and deformable *** deformable link is composed of passive spherical joints with preload forces between socket-ball *** estimate the load bearing capacity of a deformable link,we present a static force-based model of spherical joint with preload force and analyze the static force propagation in the deformable *** yields an important result that the load bearing capacity of a spherical joint only depends on its radius,preload force,and static friction *** further develop a parameter estimation method to estimate the product of preload force and static friction *** experimental results validate our model.80.4%of percentage errors on the maximum payload mass prediction are below 15%.

关键词： Deformable link parameters identification spherical joint with preload force static force-based model

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RHNet: A Real-Time High-Resolution Network for Surface Defect Detection

RHNet: A Real-Time High-Resolution Network for Surface Defec...

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第43届中国控制会议

作者： Yijie Wang Zhigang Ren Jianpu Cai Zongze Wu Shengli Xie School of Automation Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangdong University of Technology Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangdong University of Technology College of Mechatronics and Control Engineering Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)Shenzhen University Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing (GDUT) Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the industrial domain, surface defect detection after multiple processing steps is crucial for improving the outgoing quality of products. However, due to the characteristics of surface defects, such as low contrast, irregular shapes, small and elongated features, and significant noise. To address these issues, this paper proposes a novel real-time high-resolution network(RHNet). Unlike previous models, RHNet emphasizes the importance of modeling spatial information to capture small ***, the output feature maps of each module are maintained at 1/4 resolution of the original image. We introduce a short-term dual-branch module(SDBM) to handle real-time processing of high-resolution feature maps. Additionally, FPAPPM is proposed for swift extraction of deep information and multi-scale context. Through extensive experiments, we demonstrate that our proposed model exhibits robust defect modeling capabilities and detection performance while still meeting real-time requirements.

关键词： Surface defect inspection Anomaly detection Semantic segmentation Deep learning Pattern recognition

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Guest Editorial: Special Issue on Technology Trends in Control, Robotics and systems - For the 30th Anniversary of the Institute of Control, Robotics and systems -

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Journal of Institute of Control, Robotics and systems 2024年第4期30卷 295-295页

作者： Ko, Nak Yong Kang, Taesam Song, Jin Woo Lim, Myo Taeg Jo, Kang-Hyun Department of Electronic Engineering Interdisciplinary Program in IT-Bio Convergence System Chosun University Korea Republic of Department of Mechanical and Aerospace Engineering Konkuk University Korea Republic of Department of Intelligent Mechatronics Engineering Sejong University Korea Republic of School of Electrical Engineering Korea University Korea Republic of Department of Electrical Electronic and Computer Engineering University of Ulsan Korea Republic of

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Generalized Predictive Analysis of Reactions in Paper Devices Via Graph Neural Networks

SSRN

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SSRN 2024年

作者： Sun, Hao Pan, Yihan Dong, Hui Liu, Canfeng Yang, Jintian Tao, Yihui Jia, Yuan School of Mechanical Engineering and Automation Fuzhou University Fuzhou China School of Mechatronics Engineering Harbin Institute of Technology Harbin China Fuzhou University China Department of Automation Control and System Engineering University of Sheffield Sheffield United Kingdom Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China

Microfluidic technology facilitates high-throughput generation of time series data for biological and medical studies. Deep learning enables accurate, predictive analysis and proactive decision-making based on autonomous recognition of intricate pattern hidden in series. In this work, we first devised a paper-based microfluidic system for portable nucleic acid amplification test with economic energy consumption. Then, we employed Graph Neural Network (GNN), distinguished by its non-Euclidean data structure tailored for deep learning, with spatio-temporal attention mechanism to perform near-sensor predictive analysis of the on-chip reaction. Our findings demonstrated that the novel GNN model can provide accurate predictions of positive outcomes at the early stages of the reaction using less than one-third of the total reaction time. Then, the deep learning model trained by on-chip data was subsequently applied to more than 900 clinical plots. Generalization of the GNN model was successfully validated across different detection methods, diverse types of datasets and time series with variable length. Accuracy, sensitivity and specificity of the predictive approach were 96.5%, 94.3% and 99.0% by utilizing the early half of reaction information. Finally, we compared the GNN model with various deep learning models. Despite differences in the prediction of negative samples among various models were minute, GNN obviously offered overall superior performance. This work ignites a cutting-edge application of deep learning in point-of-care and near-sensor tests. By harnessing the power of body area networks and edge/fog computing, our approach unlocks promising possibilities in diverse fields like healthcare and instrument science. © 2024, The Authors. All rights reserved.

关键词： Energy utilization

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Temperature and strain sensitivities of surface and hybrid acoustic wave Brillouin scattering in optical microfibers

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Chinese Physics B 2022年第9期31卷 333-339页

作者： Yi Liu Yuanqi Gu Yu Ning Pengfei Chen Yao Yao Yajun You Wenjun He Xiujian Chou Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control SystemMinistry of Education and Shanxi ProvinceTaiyuan 030024China Taiyuan University of Technology Institute of Optoelectronic EngineeringCollege of Physics and OptoelectronicsTaiyuan 030024China Strong Digital Technology Co. Ltd.(Thinvent)Nanchang 410000China North University of China Key Laboratory of Instrumentation Science and Dynamic Measurement Ministry of EducationTaiyuan 030051China North University of China College of Mechatronics EngineeringTaiyuan 030051China North University of China Science and Technology on Electronic Test and Measurement LaboratorySchool of Instrument and ElectronicsTaiyuan 030051China

Temperature and strain sensitivities of surface acoustic wave(SAW)and hybrid acoustic wave(HAW)Brillouin scat-tering(BS)in 1μm-1.3μm diameter optical microfibers are *** contrast to stimulated Brillouin scattering(SBS)from bulk acoustic wave in standard optical fiber,SAW and HAW BS,due to SAWs and HAWs induced by the coupling of longitudinal and shear waves and propagating along the surface and core of microfiber respectively,facilitate innovative detection in optical microfibers *** highest temperature and strain sensitivities of the hybrid acoustic modes(HAMs)are 1.082 MHz/℃and 0.0289 MHz/με,respectively,which is suitable for microfiber sensing applica-tion of high temperature and strain ***,the temperature and strain sensitivities of the SAMs are less affected by fiber diameter changes,ranging from 0.05 MHz/℃/μm to 0.25 MHz/℃/μm and 1×10^(-4) MHz/με/μm to 5×10^(-4) MHz/με/μm,*** can be found that that SAW BS for temperature and strain sensing would put less stress on manufacturing constraints for optical ***,the simultaneous sensing of temperature and strain can be realized by SAW and HAW BS,with temperature and strain errors as low as 0.30℃-0.34℃and 14.47με-16.25με.

关键词： Brllouin scatering surface acoustic waves hybrid acoustic waves optical microfiber sensing

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Error-state Kalman Filtering with Linearized State Constraints

TechRxiv

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TechRxiv 2023年

作者： Do, Hoang Viet Jung, Jae Hyung Park, Chan Gook Song, Jin Woo The Intelligent Navigation and Control Systems Laboratory Department of Convergence Engineering for Intelligent Drone School of Intelligent Mechatronics Engineering Sejong University Seoul05006 Korea Republic of The Department of Aerospace Engineering Automation and Systems Research Institute Seoul National University Seoul08826 Korea Republic of The Navigation and Electronic System Laboratory Department of Aerospace Engineering Institute of Advanced Aerospace Technology Seoul National University Seoul08826 Korea Republic of

In recent years, the error-state Kalman filter (ErKF) has been extensively employed across various applications, including but not limited to robotics, aerospace, and localization. However, incorporating constraints into the ErKF framework when state constraint is necessary has remained a challenging task due to its intrinsic properties. This paper explores all possible ways to achieve this goal in the context of the estimate projection method. In particular, the constraint can be enforced before or after the ErKF’s correction step. We approach the problem from a mathematical perspective by deriving analytical solutions and discussing their statistical properties. We prove that the two mentioned methods are statistically identical for a linear system with linear constraints. Conversely, the filter’s behavior remains uncertain in the presence of linearized constraints. However, we provide a special case of the nonlinear constraint, wherein the results of the linear case remain valid. To support our theorem and verify the filter’s performance when the assumptions are invalidated, we present two Monte Carlo simulations under the increasing initialization error and the constraint’s incompleteness. The simulation results clearly confirm our insights and lead to the conclusion that constraining the error-state after the correction may offer superior outcomes compared to its competitor. © 2023, CC BY.

关键词： Linearization

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A Steering Strategy for Self-Driving Automobile systems Based on Lane-Line Detection 6

A Steering Strategy for Self-Driving Automobile Systems Base...

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6th International Conference on Green Technology and Sustainable Development, GTSD 2022

作者： Phan, Thanh-Danh Nguyen, Tan-Thien-Nien Duong, Minh-Thien Nguyen, Chi-Tam Le, Hoang-Anh Le, My-Ha HCMC University of Technology and Education Intelligent System Laboratory Ho Chi Minh City Viet Nam Soongsil University Department of Information and Telecommunication Engineering Seoul Korea Republic of Lac Hong University Faculty of Mechatronics and Electronics Dong Nai province Bien Hoa city Viet Nam Faculty of Electrical and Electronics Engineering HCMC University of Technology and Education Ho Chi Minh City Viet Nam

ISBN: (数字)9781665466288

ISBN: (纸本)9781665466288

Steering strategy is an essential task for self-driving automobile systems. However, studies on this problem have not yet achieved satisfactory results and typically cause navigation tasks to be difficult. Therefore, this paper proposes a novel steering strategy based on the lane-line detection model. First and foremost, the row-based selecting strategy and CNN-based extraction were adopted to anticipate lane-line markers from the images captured from a front-view monocular camera. Next, the lane-line detection model output is utilized to estimate the next destination for the self-driving automobile, and then we converted the model to TensorRT pattern with Float16 format. Depending on the result of the lane-line detection model, we designed a strategy to control the steering wheel through a DC Servo motor. Last but not least, the whole algorithm is deployed on the golf cart to perform navigation tasks. The experimental result proves that our model achieves approximately 50 frames per second (50 fps) on our laptop with GTX 1650 graphic card during the testing stage and can work with satisfactory performance on the HCMUTE campus. © 2022 IEEE.

关键词： Motion planning

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Interface Engineering of P-Type Nio/Β-Ga2o3 Heterojunction Diodes for High Power Applications

SSRN

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SSRN 2023年

作者： Min, Ji Young Labed, Madani Prasad, Chowdam Venkata Hong, Jung Yeop Jung, Young-Kyun Rim, You Seung Department of Semiconductor Systems Engineering Sejong University Seoul05006 Korea Republic of Department of Intelligent Mechatronics Engineering and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of Electronic Device Research Team Research and Development Division Hyundai Motor Group Gyeonggi-do 16082 Korea Republic of Institute of Semiconductor and System IC Sejong University Seoul05006 Korea Republic of

This work fabricated NiO/β-Ga2O3 heterojunctions (HJs) deposited using confined magnetic field-based sputtering (CMFS) at different oxygen flow percentages and compared these with a Schottky barrier diode (SBD). Firstly, the optical and electrical properties of NiO thin film are discussed. We noticed that with increasing oxygen flow percentages, the NiO bandgap (Eg) increased, and resistivity decreased. Furthermore, an X-ray photoelectron spectroscopy (XPS) technique was used to analyze the chemical state of NiO films at different oxygen flow percentages and to extract a NiO/β-Ga2O3 band offset. In addition, we observed that the p-NiO interlayer improved NiO/β-Ga2O3 heterojunction performance compared with a SBD. The leakage of current was reduced, and breakdown increased from -552 V to -644 V after the insertion of a 4.7% NiO interlayer. This improvement was explained by the decrease in interfacial state density. However, on-resistance increased from 44.84 mΩ.cm² to 431.54 mΩ.cm². This increase in on-resistance can be explained by the high NiO resistivity layer. Accordingly, the effect of oxygen flow percentage was optimized to improve NiO layer resistivity. Subsequently, a very low on-resistance (Ron) with a value 10.85 mΩ.cm² was obtained by increasing the O2/Ar percentage to 10%. Moreover, we noticed that with increasing oxygen flow percentage, the on-voltage (Von) had two variations, an increase and then a decrease. The increase in Von is explained by the conduction band increasing with increasing oxygen flow percentage, but the decrease is explained by the effect of trap-assisted tunneling transport mechanism activation. These variations were confirmed with a TCAD simulator. © 2023, The Authors. All rights reserved.

关键词： Nickel oxide

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