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arXiv 2020年

作者： Zhang, Yijin Li, Honggang Jin, Maoming Lin, Zongbing Key Lab of Intelligent Analysis and Decision on Complex Systems Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Pass College of Chongqing Technology and Business University Chongqing401520 China Institute of Nonlinear Analysis Research Changjiang Normal University Chongqing400803 China School of Mathematics and Computer Science Panzhihua University Panzhihua617000 China

In this paper, a new concept, the fuzzy rate of an operator in linear spaces is proposed for the very first time. Some properties and basic principles of it are studied. Fuzzy rate of an operator B which is specific i... 详细信息

关键词： Membership functions

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Degradation mechanism of perovskite under high charge carrier density condition

arXiv

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arXiv 2021年

作者： Li, Guohui Pi, Huihui Wei, Yanfu Zhou, Bolin Gao, Ya Wen, Rong Hao, Yuying Zhang, Han Ong, Beng S. Cui, Yanxia College of Physics and Optoelectronics Key Laboratory of Interface Science and Engineering in Advanced Materials Key Lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology Taiyuan030024 China Shenzhen University Shenzhen518060 China Department of Chemistry Research Centre of Excellence for Organic Electronics Institute of Advanced Materials Hong Kong Baptist University Kowloon Tong Hong Kong

Extensive studies have focused on degradation of perovskite at low charge carrier density (16cm-3), but few have surveyed the degradation mechanism at high charge carrier density (∼1018cm-3). Here, we investigate the degradation mechanisms of perovskite under high charge carrier conditions. Unlike the observations in previous works, we find that MAPbI3degradation starts at surface defects and progressing from the surface defects towards neighboring regions under high charge carrier density condition. By using PbI2passivation, the defect-initiated degradation is significantly suppressed and the nanoplatelet degrades in a layer-by-layer way, enabling the MAPbI3laser sustain for 4500 s (2.7×107pulses), which is almost 3 times longer than that of the nanoplatelet laser without passivation. Meanwhile, the PbI2passivated MAPbI3nanoplatelet laser with the nanoplatelet cavity displaying a maximum quality factor up to ∼7800, the highest reported for all MAPbI3nanoplatelet cavities. Furthermore, a high stability MAPbI3nanoplatelet laser that can last for 8500 s (5.1×107pulses) is demonstrated based on a dual passivation strategy, by retarding the defect-initiated degradation and surface-initiated degradation, simultaneously. This work provides in-depth insights for understanding the degradation of perovskite at high charge carrier density. Copyright © 2021, The Authors. All rights reserved.

关键词： Passivation

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Two points are enough

arXiv

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arXiv 2024年

作者： Liu, Hao Zhao, Yanbin Zheng, Huarong Fan, Xiulin Deng, Zhihua Chen, Mengchi Wang, Xingkai Liu, Zhiyang Lu, Jianguo Chen, Jian State Key Laboratory of Fluid Power Components and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Ocean College Zhejiang University Hangzhou China State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Hangzhou China Nanyang Technological University Singapore School of Control Science and Engineering Zhejiang University Hangzhou China School of Materials Science and Engineering Tianjin University Tianjin China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

Prognosis and diagnosis play an important role in accelerating the development of lithium-ion batteries, as well as reliable and long-life operation. In this work, we answer an important question: What is the minimum amount of data required to extract features for accurate battery prognosis and diagnosis? Based on the first principle, we successfully extracted the best two-point feature (BTPF) for accurate battery prognosis and diagnosis using the fewest data points (only two) and the simplest feature selection method (Pearson correlation coefficient). The BTPF extraction method is tested on 820 cells from 6 open-source datasets (covering five different chemistry types, seven manufacturers, and three data types). It achieves comparable accuracy to state-of-the-art features in both prognosis and diagnosis tasks. This work challenges the cognition of existing studies on the difficulty of battery prognosis and diagnosis tasks, subverts the fixed pattern of establishing prognosis and diagnosis methods for complex dynamic systems through deliberate feature engineering, highlights the promise of data-driven methods for field battery prognosis and diagnosis applications, and provides a new benchmark for future studies. Copyright © 2024, The Authors. All rights reserved.

关键词： Lithium-ion batteries

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Achieving Peta-Ohm Resistance for Semi-Insulating 4H-SiC Devices by Atomic Layer Deposition

arXiv

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arXiv 2024年

作者： Xi, Yuying Li, Helios Y. Li, Guohui Su, Qingmei Mao, Kaili Xu, Bingshe Hao, Yuying Fang, Nicholas X. Cui, Yanxia College of Electronic Information and Optical Engineering Key Lab of Interface Science and Engineering in Advanced Materials Key Lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology Taiyuan030024 China Department of Mechanical Engineering University of Hong Kong Hong Kong999077 Hong Kong School of Materials Science and Engineering Materials Institute of Atomic and Molecular Science Shaanxi University of Science and Technology Xi’an710021 China Shanxi Semisic Crystal Co. Ltd. Taiyuan030000 China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030032 China

Growing demands for precise current measurements, such as atto-ampere-level measurement of cross-cellular biological current transduction, have spotlighted a pressing need for low-noise resistors with ultra-high resistance immune to voltage fluctuations. Traditional semi-insulating materials, however, struggle to provide consistent resistance across varying voltages. To bridge this gap, we introduce a design that integrates semi-insulating 4H-SiC with atomic-level metal oxide interlayers and electrodes. The strategic adjustment of surface states via atomic-scale metal oxide layers optimizes the work functions on 4H-SiC surfaces, validated through density functional theory simulations. This design transcends conventional limitations, establishing an ideal Ohmic behavior and maintains Peta-Ohm-level resistance, unaffected by voltage variations. These on-chip devices with fine-tuned resistance are compatible with integrated circuit manufacturing processes, making them ideally suited for applications in precision electronics. © 2024, CC BY-NC-ND.

关键词： Silicon carbide

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Study on Autonomous Surgical control system of The Vascular Interventional Surgical Robot Based on Catheter Tip Location Tracking

Study on Autonomous Surgical Control System of The Vascular ...

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IEEE International Conference on Mechatronics and Automation

作者： Zhimin Feng Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications In Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5Zhongguancun South Street Beijing China

The control system of vascular interventional surgical robot is a complex nonlinear system. When the catheter is inserted into human blood vessels, due to the irregular and curved shape of human blood vessels, the catheter will undergo small deformation, which will affect the displacement of the catheter. In order to reduce the displacement tracking error, a BP neural network PID controller was designed to compensate the displacement error of the autonomous vascular interventional surgical robot. Firstly, the dynamic analysis is carried out according to the axial displacement motion of the vascular interventional surgical robot, and the catheter displacement tracking controller was designed. According to the displacement error, BP neural network PID control is used to output three parameters of PID. Finally, in the experiment and PID control simulation comparison, the results show that the BP neural network PID control has a small displacement tracking error and superior tracking performance, which can meet the requirements.

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Design of control system for Lower Limb Rehabilitation Robot on the Healthy Side sEMG Signal

Design of Control System for Lower Limb Rehabilitation Robot...

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IEEE International Conference on Mechatronics and Automation

作者： Shiqin Yu Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

With the number of stroke patients increasing year by year, rehabilitation exoskeleton robot has been paid more and more attention. For the rehabilitation exoskeleton robot, human-computer interaction ability is an important index, which affects the effect of rehabilitation therapy to a great extent. Surface Electromyography (sEMG) signals are the combined effect of sEMG signals and electrical activities on nerve stem on the skin surface, which can reflect neuromuscular activities in advance and can be used to predict movement intention by sEMG signals. Therefore, this article proposes to use sEMG signals to monitor the motion information of the healthy leg in real-time, extract the characteristics of the electromyography signals, use the sEMG of the healthy leg as the control signal, reflect the motion patterns reflected by the sEMG collected from the healthy side, and then use the motion intention recognition method of Long Short Term Memory(LSTM) neural network to identify the motion intention of the prosthetic limb by identifying the motion patterns of the swing phase of the healthy side. The results indicate that the predicted maximum Root Mean Squared Error(RMSE) is 5.3729, which proves the feasibility of using LSTM model for motion intention recognition and contributes to the real-time and accuracy of lower limb exoskeleton rehabilitation.

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Study on 6D Pose Estimation system of Occlusion Targets for the Spherical Amphibious Robot based on Neural Network

Study on 6D Pose Estimation System of Occlusion Targets for ...

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IEEE International Conference on Mechatronics and Automation

作者： Chaofeng Du Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications in Complicated systems and Intelligent Robot Laboratory Tianjin University of Technology BinshuiXidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

The amphibious robot needs to accurately estimate the 6D pose of the target in tasks such as target tracking, docking with the recovery module, and target grasping. The current research on target 6D pose estimation is mainly applied to unoccluded targets, but when the target is occluded, the target’s pose cannot be accurately identified. Compared with other algorithms, the PVNet algorithm shows better robustness when target is occluded, but the accuracy is still low. To improve the accuracy of the PVNet algorithm, this paper adds the confidence score prediction of the prediction vector at the last layer of the PVNet network, and designs a vector confidence score loss function to train the network. Before generating the hypothetical keypoints, the pixels whose confidence score is lower than the set threshold are screened out, so that the generated hypothetical 2D keypoints are closer to the true 2D keypoints. Finally, the method in this paper is compared with the Tekin, PoseCNN, Oberweger and Pvnet algorithm, and demonstrate the superiority of the proposed method.

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A DDPG-Based Method of Autonomous Catheter Navigation in Virtual Environment

A DDPG-Based Method of Autonomous Catheter Navigation in Vir...

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IEEE International Conference on Mechatronics and Automation

作者： Wei Tian Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications In Complicated systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5Zhongguancun South Street Beijing China

Vascular interventional surgery is the main method for treating cardiovascular diseases. But navigating endovascular catheters through the vascular tree is a highly challenging task even for highly trained specialists. Automation of this task can reduce the burden on surgeons and is expected to improve the surgical outcomes. Although there have been relevant studies utilizing reinforcement learning algorithms to realize autonomous navigation of catheter in the virtual environment Cathsim. However, the kinematics model of the catheter in Cathsim does not conform to the operating mode of the catheter in real vascular interventional surgery. Besides, there are problems such as low success rates of catheter autonomous navigation tasks. To address these issues, this paper modifies the kinematics model of the catheter in Cathsim and designs a catheter autonomous navigation model based on reinforcement learning DDPG (Deep Deterministic Policy Gradient) algorithm. The experimental results show that the agents trained through DDPG in this paper performs better than the agents trained through PPO (Proximal Policy optimization) in other studies in terms of navigation task success rate, completion time, and contact force between the catheter and vascular wall during the navigation process.

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Study on control Strategy of the Vascular Interventional Surgical Robot Based on LADRC

Study on Control Strategy of the Vascular Interventional Sur...

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IEEE International Conference on Mechatronics and Automation

作者： Wenqiang Zhang Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Applications In Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5Zhongguancun South Street Beijing China

As a medical device used in surgery, the vascular interventional surgical robot itself needs to have good control accuracy to ensure the safety of the surgery process. Given this security problem, this paper selects the Line Active Disturbance Rejection control (LADRC) as the control strategy of the vascular interventional robot, aiming at improving the master-slave tracking accuracy of the vascular interventional robot. This article compares the LADRC and PID(Proportional-Integral-Derivative) control strategies through simulation and experiments. The experimental results show that LADRC has good control performance for master-slave tracking and can be applied to the vascular interventional surgical robots.

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Deep Learning-Based Dimension Measurement system for Industrial Part Inspection

Deep Learning-Based Dimension Measurement System for Industr...

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Chinese Automation Congress (CAC)

作者： Xiao-Di Li Xing-Rong Fan Xian-Ming Zhang Han-Zhi Zhang Chun-Jie Huang Cheng Xu Chongqing Engineering Laboratory for Detection Control and Integrated System School of Artificial Intelligence Chongqing Technology and Business University Chongqing China Engineering Research Centre for Waste Oil Recovery Technology and Equipment Ministry of Education Chongqing Key Laboratory Chongqing Technology and Business University Chongqing China School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China Chongqing Intelligent Supply Chain Engineering & Technology Research Center Chongqing Jiaotong University Chongqing China Chongqing Aerospace Bashan Motorcycle Manufacturing Co. Ltd. Chongqing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

This paper develops a deep learning-based system for the dimension measurement of industrial parts. The system employs a general self-supervised image segmentation network to perform dichotomous image segmentation (DIS) on the parts, effectively extracting binary images of the target components from complex backgrounds without requiring preprocessing steps such as filtering or denoising. Following segmentation, contour detection, and dimension measurement are executed. The system utilizes a CMOS area scan camera and was tested on a computer equipped with a GTX1050 graphics card. The tests, conducted on two typical thrust ball bearing components (i.e., the ball retainer and the shaft ring) - yielded ten measurements per part. Comparison with a vernier caliper as the reference standard reveals that under normal operating conditions, the maximum standard deviation is 0.007 mm and the maximum absolute error is 0.017 mm.

关键词： Shafts Image segmentation Accuracy Measurement uncertainty Noise reduction Manuals Size measurement Stability analysis Robustness Standards

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