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2022 International Symposium on Networks, Computers and Communications, ISNCC 2022

作者： Zhang, Bo Yan, Bingjun Liu, Mingzhe Hu, Bo Xu, Aidong Wang, Kai Key Laboratory of Networked Control Systems Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China

ISBN: (数字)9781665485449

ISBN: (纸本)9781665485449

In order to improve the real-time and reliability of network communication in intelligent ship system, this paper analyzes the requirements of ship-borne network, and develops a real-time Ethernet protocol stack based on Zynq7000 series SoC chip. The development of the protocol stack includes the software layer and the firmware layer. As the main part of the protocol stack, the software layer adds real-time communication entities upon the data link layer of the Ethernet reference model, and the timing of communication is controlled by the synchronous precise measurement clock to realize the real-time scheduling and transmission of data. On the other hand, the PTP message timestamp function of clock synchronization and the redundant function of zero recovery time based on PRP algorithm is realized on the firmware layer. Finally, the real-time, reliability and synchronization accuracy of the protocol stack are tested and verified on the developed real-time Ethernet cards. © 2022 IEEE.

关键词： System-on-chip

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Weld Defects Detection by Neural Networks Based on Attention Mechanism 7

Weld Defects Detection by Neural Networks Based on Attention...

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7th IEEE Information Technology and Mechatronics Engineering Conference, ITOEC 2023

作者： Yang, Guang Liu, Zhifeng Wang, Jianjun Cui, Shuping State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9798350334197

Welding technology plays an indispensable role in ship construction, and its maturity has a direct impact on the quality of shipbuilding. The weld seam, being the weakest part of a welded structure, significantly affects the structural strength, service life, and safety reliability of ships. However, the current identification of weld defects in the ship industry relies on manual methods, which are subjective and prone to error. To address this issue, this paper presents a novel approach by collecting weld images from actual ship scenes, preprocessing them to eliminate noise and highlight defect features, and proposing a Transformer-based improved target detection model (T-OBJDETC) to enhance the recognition accuracy of the model. © 2023 IEEE.

关键词： Ships

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Research on the Application of Mask2Former for Segmenting Small Mushroom Caps of Seafood Mushrooms

Research on the Application of Mask2Former for Segmenting Sm...

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Electronic Information Engineering and Computer Technology (EIECT), International Conference on

作者： Mengchao Ren Wanhe Du Shuzhen Yang Tao Yu Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China School of Intelligent Manufacturing and Control Engineering Shanghai China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798331528850

ISBN: (纸本)9798331528867

In the task of monitoring mushroom growth characteristics, the mushroom cap is one of the most important features. To address the challenges faced by traditional instance segmentation algorithms in segmenting the caps of seafood mushrooms during the early stages of growth, such as unclear edges and low success rates. This paper proposes the application of the Mask2Former algorithm for instance segmentation of the caps of seafood mushrooms in their early differentiation stage. First, camera equipment was set up to capture images of the mushroom house for dataset creation. Then, the collected images were augmented through techniques such as flipping and adding noise. Finally, the processed images were input into the model, allowing Mask2Former to be compared with three other instance segmentation algorithms. Experimental results demonstrated that Mask2Former performed better in segmenting small mushroom caps during the early growth stage of seafood mushrooms, achieving an average precision (AP) of 96.731%, which effectively meets practical production needs.

关键词： Instance segmentation Electric potential Image edge detection Noise Production Transformers Cameras Agriculture Monitoring

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Kuhn-Munkres Algorithm Based Hybrid Beamforming for Wideband Millimeter Wave MIMO Systems With Dynamic Subarrays 15

Kuhn-Munkres Algorithm Based Hybrid Beamforming for Wideband...

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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Wang, Gengshan Yang, Zhijia Gong, Tierui Zheng, Meng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Singapore University of Technology and Design Singapore

ISBN: (纸本)9798350324662

Dynamic subarrays (DSs) is an energy-efficient and cost-effective hybrid beamforming structure for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communications. In this paper, we investigate the nonconvex hybrid beam-forming problem of maximizing the average spectral efficiency of the point-to-point wideband mmWave MIMO system with DSs, where the beam squints are also considered. To address the nonconvexity of this hybrid beamforming problem, we first exploit the singular value decomposition of each subcarrier channel and water-filling strategy to get the optimal fully-digital beamforming. We then propose to leverage the Kuhn-Munkres algorithm to get the hybrid beamforming from the obtained fully-digital solutions, aiming to guarantee that every radio-frequency chain is connected to at least one antenna. Besides, we analyze the computational complexity of the proposed design. Numerical results demonstrate the superiority of this work over the state of the art. © 2023 IEEE.

关键词： dynamic subarrays hybrid beamforming Kuhn-Munkres algorithm MIMO spectral efficiency Wideband millimeter wave

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Small Photoresist Defect Samples Augmentation Based on Generative Adversarial Network 6

Small Photoresist Defect Samples Augmentation Based on Gener...

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6th IEEE Information Technology, Networking, Electronic and Automation control Conference, ITNEC 2023

作者： Yang, Guang Li, Zhihang Yang, Zhijia Cui, Shuping State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9781665460033

Photoresist coating technology is an important part of the surface treatment of semiconductor wafers. The presence of bubbles in photoresist can seriously affect the quality of wafers, however, the lack of sufficient bubble samples makes intelligent automatic detection techniques impossible. To solve such a problem, we propose B-GAN based on adversarial generative network, and design a mapping network for potential encoding mapping and a synthetic network for high-quality bubble image generation, so that defective bubble samples can be automatically generated. Experiments prove that our method achieves excellent results. © 2023 IEEE.

关键词： III-V semiconductors

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Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells 32

Application of Deep Learning Method to Estimate Bottomhole P...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Cheng, Haibo Li, Shichao Zeng, Peng Vyatkin, Valeriy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350399714

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry. © 2023 IEEE.

关键词： Long short-term memory

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Performance Comparison of Teleoperation Interfaces for Ultra-Lightweight Anthropomorphic Arms

Performance Comparison of Teleoperation Interfaces for Ultra...

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IEEE/RSJ International Conference on intelligent Robots and Systems (IROS)

作者： Filip Zorić Alejandro Suarez Goran Vasiljević Matko Orsag Zdenko Kovačić Anibal Ollero Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia GRVC Robotics Lab University of Seville Sevilla Spain

This paper presents a comparative performance evaluation of three different teleoperation interfaces for very low weight (<3 kg) anthropomorphic dual arms intended to conduct complex manipulation tasks involving a certain level of dexterity, accuracy and agility, either in ground service or in aerial manipulation applications. A visual human pose estimation system is developed to obtain the Cartesian and joint values of the user, which are mapped to the corresponding pose of the dual arm manipulator exploiting the equivalent human-robot kinematics. A leader-follower scheme is also presented, using a reduced scale dual arm that can replicate directly the joint positions of the leader arms to the follower arms. A 6-DOF (degrees of freedom) joystick is proposed to generate linear motions more accurately. A total of 60 ground tests were conducted involving 10 participants to determine the accuracy and time performance in two benchmarks (box edges and S contour tracking). Finally, the visual and leader-follower interfaces were evaluated with the dual arm aerial manipulator on flight tests, reporting several findings derived from the system evaluation.

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Enhanced cathodic activity by tantalum inclusion at B-site of La_(0.6)Sr_(0.4)Co_(0.4)Fe_(0.6)O_(3)based on structural property tailored via camphor-assisted solid-state reaction

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Journal of Advanced Ceramics 2022年第8期11卷 1330-1342页

作者： Dingyu XIONG Sefiu Abolaji RASAKI Yangpu LI Liangdong FAN Changyong LIU Zhangwei CHEN Additive Manufacturing Institute Shenzhen UniversityShenzhen 518060China Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robotics Shenzhen UniversityShenzhen 518060China Department of Chemical and Petroleum Engineering University of CalgaryCalgary T2N1N4Canada College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China

Lanthanum strontium cobalt ferrite(LSCF)is an appreciable cathode material for solid oxide fuel cells(SOFCs),and it has been widely investigated,owing to its excellent thermal and chemical ***,its poor oxygen reduction reaction(ORR)activity,particularly at a temperature of≤800℃,causes setbacks in achieving a peak power density of>1.0 W·cm^(-2),limiting its application in the commercialization of *** improve the ORR of LSCF,doping strategies have been found ***,the porous tantalum-doped LSCF materials(La_(0.6)Sr_(0.4)Co_(0.4)Fe_(0.5)7Ta_(0.03)O_(3)(LSCFT-0),La_(0.6)Sr_(0.4)Co_(0.4)Fe_(0.5)4Ta0.06O_(3),and La_(0.6)Sr_(0.4)Co_(0.4)Fe_(0.5)Ta0.1O_(3))are prepared via camphor-assisted solid-state reaction(CSSR).The LSCFT-0 material exhibits promising ORR with area-specific resistance(ASR)of 1.260,_(0.5)80,0.260,0.100,and 0.06Ω·cm^(2)at 600,650,700,750,and 800℃,*** performance is about 2 times higher than that of undoped La_(0.6)Sr_(0.4)Co_(0.4)Fe_(0.6)O_(3)with the ASR of 2.515,1.191,_(0.5)96,0.320,and 0.181Ω·cm^(2)from the lowest to the highest *** material characterization,it was found that the incorporated Ta occupied the B-site of the material,leading to the enhancement of the ORR *** the use of LSCFT-0 as the cathode material for anode-supported single-cell,the power density of>1.0 W·cm^(-2)was obtained at a temperature<800℃.The results indicate that the CSSR-derived LSCFT is a promising cathode material for SOFCs.

关键词： tantalum-doped lanthanum strontium cobalt ferrite(LSCF) solid oxide fuel cell(SOFC) oxygen reduction reaction(ORR) solid-state synthesis reaction clean energy conversion

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Temperature Rising Model of Tubular Permanent Magnet Linear Synchronous Motor Based on Transfer Learning-Deep Neural Network

Temperature Rising Model of Tubular Permanent Magnet Linear ...

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第42届中国控制会议

作者： YiFei Wang Tao Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

High temperature rise of permanent magnet linear synchronous motor can lead to irreversible demagnetization of the motor permanent magnet, which can negatively affect the motor performance. To address this problem, a thermal modeling analysis method based on Transfer learning-Deep neural network(TL-DNN) was proposed in this paper. Its specific implementation steps include(1) corresponding to different heat source inputs, the equivalent thermal circuit method and the finite element analysis was adopted based on the structure and main parameters of PMLSM including overall average temperature rise, coil temperature rise and permanent magnet temperature rise from the data sets of the motor;(2) TL-DNN was used to fit the functional relationship between the input source features and the output targets based on the characteristics of the sample data sets. In order to verify the accuracy of the prediction model with small sample data sets, this paper divided the proportion of the data set and compared the results with other classic nonparametric models(random forest, support vector machine, and deep neural network). The results show that the TL-DNN model outperforms other machine learning models and has better robustness and generalization ability when the training datasets are insufficient, and achieves an organic combination of physical field path model and data-driven model, which provides a feasible solution for PMLSM modeling in the case of small samples.

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Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

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4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

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