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23rd Pacific Basin Nuclear Conference, PBNC 2022

作者： Song, Fei Liu, Hang Luan, Zhenhua Qiao, Jianfeng Liu, Peng China Nuclear Power Engineering Co. Ltd Guangdong Shenzhen China State Key Lab of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou Zhejiang China

ISBN: (纸本)9789811987793

In the start-up and shutdown stage of the nuclear power plant, the Steam generator has not been put into operation, and the core residual heat and temperature control are realized by the residual heat removal system. Traditional GEN-II nuclear power plants use RRA system to control the primary temperature. Operators manually control the regulating valve on the pipeline where Heat exchanger is located, adjust the primary coolant flow through Heat exchanger, so as to control the primary temperature and its gradient. In the start-up and shutdown stage of a GEN-III nuclear power plant, when the steam generator has not been put into operation, the waste heat removal function is completed by RIS low-pressure safety injection system. And the primary loop can automatically heat up and cool down in a temperature gradient and target temperature which set by the operators, hereinafter referred to as RHR temperature control system. The RHR temperature control system should not only avoid the thermal shock to the low pressure injection pipeline during the automatic heat-up and cool down process, but also maintain the stable flow rate of the RIS low pressure injection pipeline. The design of RHR temperature control system is complicated. During the first test of Validation, there were some anomalies such as temperature setpoint fluctuation and full closing of actuator. Finally, through design modification and parameter optimization, the test Validation for the control system was completed. And the automatic heat-up and cool down control of primary loop temperature in the cold shutdown stage of nuclear power plant has been realized, which improves the intelligent level of nuclear power plant. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Nuclear power plants

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A Novel Foreign Object Detection Method in Transmission Lines Based on Improved YOLOv8n

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Computers, Materials & Continua 2024年第4期79卷 1263-1279页

作者： Yakui Liu Xing Jiang Ruikang Xu Yihao Cui Chenhui Yu Jingqi Yang Jishuai Zhou School of Mechanical and Automotive Engineering Qingdao University of TechnologyQingdao266520China State Key Laboratory of Electrical Insulation and Power Equipment Xi’an Jiaotong UniversityXi’an710049China Key Lab of Industrial Fluid Energy Conservation and Pollution Control Qingdao University of TechnologyMinistry of EducationQingdao266520China

The rapid pace of urban development has resulted in the widespread presence of construction equipment andincreasingly complex conditions in transmission corridors. These conditions pose a serious threat to the safeoperation of the power *** vision technology, particularly object recognition technology, has beenwidelyemployed to identify foreign objects in transmission line images. Despite its wide application, the technique faceslimitations due to the complex environmental background and other auxiliary factors. To address these challenges,this study introduces an improved YOLOv8n. The traditional stepwise convolution and pooling layers are replacedwith a spatial-depth convolution (SPD-Conv) module, aiming to improve the algorithm’s efficacy in recognizinglow-resolution and small-size objects. The algorithm’s feature extraction network is improved by using a LargeSelective Kernel (LSK) attention mechanism, which enhances the ability to extract relevant features. Additionally,the SIoU Loss function is used instead of the Complete Intersection over Union (CIoU) Loss to facilitate fasterconvergence of the algorithm. Through experimental verification, the improved YOLOv8n model achieves adetection accuracy of 88.8% on the test set. The recognition accuracy of cranes is improved by 2.9%, which isa significant enhancement compared to the unimproved algorithm. This improvement effectively enhances theaccuracy of recognizing foreign objects on transmission lines and proves the effectiveness of the new algorithm.

关键词： YOLOv8n data enhancement attention mechanism SPD-Conv Smoothed Intersection over Union(SIoU)Loss

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Higher-order properties and extensions for indirect MRAC and APPC of linear systems

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science China(Information sciences) 2024年第4期67卷 218-238页

作者： Yanjun ZHANG Zhipeng ZHANG Jian SUN Lei WANG Kangkang ZHANG National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center College of Control Science and Engineering Zhejiang University Department of Electrical and Electronic Engineering Imperial College London KIOS Research and Innovation Center of Excellence University of Cyprus

Recently, a reference derived some new higher-order output tracking properties for direct model reference adaptive control（MRAC） of linear time-invariant（LTI） systems: limt→∞ e（i）（t） = 0, i = 1,..., n*-1, where n*and e（i）（t） denote the relative degree of the system and the i-th derivative of the output tracking error, respectively. However, a naturally arising question involves whether indirect adaptive control（including indirect MRAC and indirect adaptive pole placement control） of LTI systems still has higher-order tracking properties. Such properties have not been reported in the literature. Therefore, this paper provides an affirmative answer to this question. Such higher-order tracking properties are new discoveries since they hold without any additional design conditions and, in particular, without the persistent excitation condition. Given the higher-order properties, a new adaptive control system is developed with stronger tracking features.（1） It can track a reference signal with any order derivatives being unknown.（2） It has higher-order exponential or practical output tracking properties.（3） Finally, it is different from the usual MRAC system, whose reference signal's derivatives up to the n*order are assumed to be known. Finally, two simulation examples are provided to verify the theoretical results obtained in this paper.

关键词： higher-order tracking indirect adaptive control model reference adaptive control adaptive pole placement control

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Preclinical Assessment of Upper Limb Tremor in Parkinson's Disease with Deep Learning and Wearable technology

Preclinical Assessment of Upper Limb Tremor in Parkinson's D...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Lin, Fang Wang, Zhelong Qiu, Sen Zhao, Hongyu School of Control Science and Engineering Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Liaoning Dalian China

ISBN: (纸本)9798350337020

Tremors are typically experienced by patients at the beginning of Parkinson's disease (PD). Clinicians evaluate clinical symptoms based on scale and experience, but mild tremors do not have significant characteristics and are difficult to observe with the naked eye. Implementing an intelligent and objective method to identify PD patients with early tremor symptoms and healthy controls (HC) is necessary. This study used wearable sensors to collect 9-axis inertial signals and 2-channel sEMG signals at the wrists of 13 HC and 24 PD patients from Dalian Municipal Central Hospital. Based on a Long Short-Term Memory Network (LSTM), an attention mechanism, and a Fully Convolutional Network (FCN), we develop a model to classify and recognize data from PD patients. Compared the proposed method with several classification methods, the results showed that the proposed method achieved higher classification accuracy (91.78%), precision (100%), recall (87.50%), and F1-score (93.33%) of PD class than Support Vector Machine, FCN, and LSTM. The computing time of the proposed method is approximately 1 second. The proposed method identifies early PD patients by pre-clinical assessment of mild upper limb tremors, which is valuable for early treatment and rehabilitation. © 2023 IEEE.

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Feedback Generative Adversarial Network With Channel-Space Attention for Image-Based Optimal Path Search Planning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4293-4307页

作者： Sun, Tao Li, Jian-Sheng Zhang, Yi-Fan Ru, Xin-Feng Wang, Ke Tsinghua University Department of Automation Beijing100084 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tongji University School of Economics and Management Shanghai200092 China

Path planning and seeking is one of the most challenging and interesting problems in the field of artificial intelligence. In this article, we propose a new image-based path planning algorithm to overcome traditional design concepts based on complex topological networks. Specifically, a novel feedback generative adversarial network learning model with channel-space attention (CSA-FGAN) is developed to search and plan an optimal path. It is worth noting that the input and output of the proposed feedback learning model are RGB images with complex spatial obstacle environment maps and RGB images with feasible paths, respectively. In particular, in order to further enhance the feature extraction ability and path prediction accuracy of image data, the feedback attention mechanism controls and improves the depth of the network by forming a closed loop of the proposed learning model. Final, three application scenario image examples are conducted to verify the superiority of the proposed path planning policy. © 2020 IEEE.

关键词： Motion planning

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Mechanistic data-driven combined modelling and predictive control method for coal-fired power unit 5

Mechanistic data-driven combined modelling and predictive co...

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5th International Conference on industrial Artificial Intelligence, IAI 2023

作者： Hu, Jingyu Han, Zhongyang Zhao, Jun Wang, Wei Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Liaoning 116024 China

ISBN: (纸本)9798350325294

With the increase of the proportion of new energy sources connected to the grid, challenges are also emerged for modeling and control of the conventional coal-fired power units to increase their operational flexibility of deep peak-regulation. Traditional data-driven modelling (DDM) requires a large amount of training data containing a variety of operating conditions, which are hard to be fully satisfied in engineering practice. This paper investigates the mechanics and dynamic characteristics of boiler-turbine systems in the coal-fired power unit, and proposes a mechanistic data-driven combined modelling (M-DDM) method. It not only requires less amount of data comparing with the DDM based method, but also covers a wide range of operating conditions by considering the dynamic characteristics of the coal-fired power unit. A model predictive control (MPC) based method was subsequently designed as the control vehicle. In order to improve the computing efficiency and reduce the probability of model mismatch considering the involved ordinary differential equations (ODEs) and nonlinearities. reinforcement learning is embedded into the MPC. Finally, simulations are conducted for demonstrating the superior performance of the proposed methods comparing with other commonly deployed modeling and control methods. © 2023 IEEE.

关键词： Model predictive control

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Diminishing ether-oxygen content of electrolytes enables temperature-immune lithium metal batteries

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science China Chemistry 2023年第9期66卷 2700-2710页

作者： Tao Liu Jingnan Feng Zhe Shi Huajun Li Weina Zhao Minglei Mao Xiangzhen Zhu Yong-Sheng Hu Hong Li Xuejie Huang Liquan Chen Liumin Suo Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China Qingdao Industrial Energy Storage Research Institute Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdao 266101China Department of Nuclear Science and Engineering and Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control Guangdong Key Laboratory of Environmental Catalysis and Health Risk ControlSchool of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China

The reversibility of lithium(Li) metal anodes is highly susceptible to temperature,owing to the aggravated side reactions at high temperatures and serious Li dendrite growth at low *** it is extremely challenging to simultaneously realize the high Li reversibility in both low and high temperature ***,an oxygen-free solvent(n-hexane,HEX) assisted with the hexyl methyl ether and 1 mol L^(-1)lithium bis(fluorosulfonyl)imide is proposed to constitute an electrolyte for temperatureimmune lithium metal *** demonstrates that the HEX not only greatly suppresses the solvent reduction even at high temperatures but also weaken the Li~+-solvent interaction for the facile Li-ion desolvation,leading to high Li Coulombic efficiencies(99.59% at 25℃,99.30%at 60℃ and 98.75% at -30℃) and the dendrite-free Li plating from -30℃ to 60℃.Benefitting from the low density and temperature-immune properties of our electrolyte,the sulfurized polyacrylonitrile(3.8mAh cm^(-2))||Li(60 μm) pouch-cells deliver 278 Wh kg^(-1)energy density and maintain the stable performance over 50 cycles,and retain 248 and 320 Wh kg^(-1) energy density at -30℃ and 60℃,*** work provides a new perspective on the electrolyte design for wide-temperature Li metal batteries.

关键词： wide temperature range oxygen-free solvent dendrite-free Li plating high Coulombic efficiencies lithium metal batteries

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A Survey on Design,Actuation,Modeling,and control of Continuum Robot

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Cyborg and Bionic Systems 2022年第1期2022卷 22-34页

作者： Jingyu Zhang Qin Fang Pingyu Xiang Danying Sun Yanan Xue Rui Jin Ke Qiu Rong Xiong Yue Wang Haojian Lu State Key Laboratory of Industrial Control and Technology Zhejiang UniversityHangzhou 310027China Institute of CyberSystems and Control The Department of Control Science and Engineering Zhejiang UniversityHangzhou 310027China Department of Plastic Surgery Sir Run Run Shaw HospitalZhejang University of MedicineHangzhou 310016China

Inthis paper,we describethe advances inthe design,actuation,modeling,and controlfield of continuum *** decades ofpioneering research,many innovativeve structural designandUntethered magnetic robots are agood example;its external actuationcharteristigotten a lot of interest ***,modeling approachesbased on continuunnechals after years oof *** when combined withnumerical analytic methodschtFifecodle-b *** the control,*** and hybrid control methodscombined with sensor *** the other hand,tladeg and control of continum *** data-driven modeling technique simplifies modeling aproves anti-interference and generalization *** paper discusses the current development and challenges of continum robots in the above felds and provides prospectsfor the future.

关键词： Robot modeling generalization

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An Improved Machine Learning Model for Pure Component Property Estimation

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engineering 2024年第8期39卷 61-73页

作者： Xinyu Cao Ming Gong Anjan Tula Xi Chen Rafiqul Gani Venkat Venkatasubramanian State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Department of Physics Bard College at Simon’s RockGreat BarringtonMA 01230USA PSE for SPEED Company Charlottenlund DK-2920Denmark Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 510000China Department of Applied Sustainability Széchenyi István UniversityGyör 9026Hungary Complex Resilient Intelligent Systems Laboratory Department of Chemical EngineeringColumbia UniversityNew YorkNJ 10027USA

Information on the physicochemical properties of chemical species is an important prerequisite when performing tasks such as process design and product ***,the lack of extensive data and high experimental costs hinder the development of prediction techniques for these ***,accuracy and predictive capabilities still limit the scope and applicability of most property estimation *** paper proposes a new Gaussian process-based modeling framework that aims to manage a discrete and high-dimensional input space related to molecular structure representation with the group-contribution approach.A warping function is used to map discrete input into a continuous domain in order to adjust the correlation between different *** selection techniques,including prior elicitation and prior predictive checking,are also applied during the building procedure to provide the model with more information from previous research *** framework is assessed using datasets of varying sizes for 20 pure component *** 18 out of the 20 pure component properties,the new models are found to give improved accuracy and predictive power in comparison with other published models,with and without machine learning.

关键词： Group contribution Gaussian process Warping function Prior predictive checking

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Mechanical responses and acoustic emission behaviors of coal under compressive differential cyclic loading(DCL):a numerical study via 3D heterogeneous particle model

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International Journal of Coal science & technology 2023年第3期10卷 136-154页

作者： Zhengyang Song Yunfeng Wu Yong Zhang Yi Yang Zhen Yang State Key Laboratory of Water Resource Protection and Utilization in Coal Mining BeijingChina Department of Civil Engineering University of Science&Technology BejingBeijing 100083China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and TechnologyHuainan 232001China

The stability of coal walls(pillars)can be seriously undermined by diverse in-situ dynamic *** on a 3D par-ticle model,this work strives to numerically replicate the major mechanical responses and acoustic emission(AE)behaviors of coal samples under multi-stage compressive cyclic loading with different loading and unloading rates,which is termed differential cyclic loading(DCL).A Weibull-distribution-based model with heterogeneous bond strengths is constructed by both considering the stress-strain relations and AE *** previously loaded samples were respectively grouped to indicate two DCL regimes,the damage mechanisms for the two groups are explicitly characterized via the time-stress-dependent variation of bond size multiplier,and it is found the two regimes correlate with distinct damage patterns,which involves the competition between stiffness hardening and *** numerical b-value is calculated based on the mag-nitudes of AE energy,the results show that both stress level and bond radius multiplier can impact the numerical *** proposed numerical model succeeds in replicating the stress-strain relations of lab data as well as the elastic-after effect in DCL *** effect of damping on energy dissipation and phase shift in numerical model is summarized.

关键词： Differential cyclic loading(DCL) Particle model Acoustic emission(AE) Discrete element method(DEM)Damage mechanism

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