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A generalized model for predicting the optimal overlap rate and height of successive single-layer involved in laser metal deposition process based on the aspect ratio

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Optics & Laser technology 2025年 191卷

作者： Enjie Dong Tingyu Chang Gan Li Ze Liu Liming Xia Linjie Zhao Junwen Lu Jiaxuan Chen Mingjun Chen Jian Cheng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China Department of Mechanical Engineering City University of Hong Kong Hong Kong China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Guangdong 518055 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou 310027 China Aircraft Repair & Overhaul Plant/Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance Civil Aviation Flight University of China Guanghan 618307 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou 450000 China

The surface flatness of single-layer islands deposition is essential for high-quality multi-layer component deposition and the stability of the Laser metal deposition (LMD) manufacturing process. The aspect ratio of single-track deposition and the overlap rate are critical factors influencing the flatness of single-layer island deposition. Existing methods for determining the optimal overlap rate, whether through experimental approaches or simplified recursive overlap models, still suffer from long development cycles and limited accuracy. In this study, a generalized, efficient and reliable model for predicting the optimal overlap rate only using the aspect ratio of the single-track deposition as the input parameter was developed after fully understanding the influence of the aspect ratio and overlap rate on the morphology, stacking effect and flatness of single-layer islands. Besides, a prediction model for the height of the single-layer island, based on the input parameters of the aspect ratio and the overlap rate has also been developed. Further, verification datasets from different experimental batches and materials were used to validate the accuracy and generalizability of the island height prediction model. The validation results indicated that the relative error between the predicted and actual values was less than 10%. The single-track aspect ratio can be directly used to guide the LMD multi-layer component deposition, regardless of the combination of powder and substrate materials, using these reliable and generalized prediction models for the optimal overlap rate and the island height developed in current study. The single-layer island deposition stage was completely eliminated, thereby significantly shorten the development cycle and reduce the cost of LMD process parameter development.

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Anchor-based spatio-temporal attention 3D convolutional networks for dynamic 3D point cloud sequences

arXiv

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arXiv 2020年

作者： Wang, Guangming Chen, Muyao Liu, Hanwen Yang, Yehui Liu, Zhe Wang, Hesheng The Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge

With the rapid development of measurwement technology, LiDAR and depth cameras are widely used in the perception of the 3D environment. Recent learning based methods for robot perception most focus on the image or video, but deep learning methods for dynamic 3D point cloud sequences are underexplored. Therefore, developing efficient and accurate perception method compatible with these advanced instruments is pivotal to autonomous driving and service robots. An Anchor-based Spatio-Temporal Attention 3D Convolution operation (ASTA3DConv) is proposed in this paper to process dynamic 3D point cloud sequences. The proposed convolution operation builds a regular receptive field around each point by setting several virtual anchors around each point. The features of neighborhood points are firstly aggregated to each anchor based on the spatio-temporal attention mechanism. Then, anchor-based 3D convolution is adopted to aggregate these anchors' features to the core points. The proposed method makes better use of the structured information within the local region and learns spatio-temporal embedding features from dynamic 3D point cloud sequences. Anchor-based Spatio-Temporal Attention 3D Convolutional Neural Networks (ASTA3DCNNs) are built for classification and segmentation tasks based on the proposed ASTA3DConv and evaluated on action recognition and semantic segmentation tasks. The experiments and ablation studies on MSRAction3D and Synthia datasets demonstrate the superior performance and effectiveness of our method for dynamic 3D point cloud sequences. Our method achieves the state-of-the-art performance among the methods with dynamic 3D point cloud sequences as input on MSRAction3D and Synthia datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

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Modeling of service correlation for service composition in cloud manufacturing 31

Modeling of service correlation for service composition in c...

引用

31st European Modeling and Simulation Symposium, EMSS 2019

作者： Wang, Fei Laili, Yuanjun Zhang, Lin Xing, Chi Guo, Liqin School of Automation Science and Electrical Engineering Beihang University China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing Simulation Center China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center China

ISBN: (纸本)9788885741263

Cloud manufacturing (CMfg), integrating distributed manufacturing resources as services to cloud center, aims at intelligent, green, and economic customized manufacturing. The optimal composition of services to fulfill particular manufacturing requirement is a core issue to realize efficient cloud manufacturing. Many researchers have studied the problem considering the Quality-of-Service (QoS) of independent services. However, the correlation between services is rarely considered. In this paper, the importance of service correlation is emphasized. Two kinds of service correlation, service exclusion and service collaboration, are modeled for service composition. An improved algorithm DET, which combines Differential Evolution Algorithm (DE) with a Tabu table based on service exclusive and collaborative relationships, is designed to filter composable services and find better solutions for complex tasks. Experiments have shown the effects of service correlation on the quality of composed services and demonstrated the effectiveness of the proposed method DET compared with traditional DE. © 2019 Dime Universita di Genova, DIMEG University of Calabria.

关键词： Quality of service

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Learning Hidden Markov Models for Linear Gaussian systems with Applications to Event-based state Estimation

arXiv

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arXiv 2020年

作者： Zheng, Kaikai Shi, Dawei Shi, Ling State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong

This work attempts to approximate a linear Gaussian system with a finite-state hidden Markov model (HMM), which is found useful in solving sophisticated event-based state estimation problems. An indirect modeling approach is developed, wherein a state space model (SSM) is firstly identified for a Gaussian system and the SSM is then used as an emulator for learning an HMM. In the proposed method, the training data for the HMM are obtained from the data generated by the SSM through building a quantization mapping. Parameter learning algorithms are designed to learn the parameters of the HMM, through exploiting the periodical structural characteristics of the HMM. The convergence and asymptotic properties of the proposed algorithms are analyzed. The HMM learned using the proposed algorithms is applied to event-triggered state estimation, and numerical results on model learning and state estimation demonstrate the validity of the proposed algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Hidden Markov models

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Dynamic Reconfiguration of Distribution Network Based on Temporal Constrained Hierarchical Clustering and Fireworks Algorithm

Dynamic Reconfiguration of Distribution Network Based on Tem...

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IEEE/IAS Industrial and Commercial Power system Asia (I&CPS Asia)

作者： Yumin Zhang Xingquan Ji Jiabin Xu Ziyang Yin Xueshan Han Chao Zhang College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Dongying Power Supply Company State Grid Dongying China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

For the dynamic reconfiguration problem of distribution networks, the handling of switching cost constraint and the division of time period are the two key aspects that affect the performance of the reconfiguration algorithm. In this paper, an improved temporal constrained hierarchical clustering algorithm for dynamic reconfiguration of distribution networks is proposed. Firstly, the improved hierarchical clustering approach considering the temporal constraint is used to divide the operating status of the distribution network into multiple time intervals according to the similarity of loads and the output power of distributed generations (DGs). The dynamic reconfiguration of distribution networks is then transformed into multiple single-stage static reconfiguration problems, and the cluster center is used to approximately represent the load state and DG output state of the period. In order to reduce the number of infeasible solutions and poor solutions, a coding method based on heuristic rules to reduce the solution space of distribution network reconfiguration is proposed. An improved fireworks algorithm based on heuristic rules is proposed to solve the reconfiguration problem. Finally, a modified IEEE-33 test system is used to verify the validity of the proposed method.

关键词： Explosions Heuristic algorithms Switches Fireworks algorithm Power system dynamics Sparks Clustering algorithms

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A decentralized social networking architecture enhanced by blockchain

A decentralized social networking architecture enhanced by b...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Zeng, Shuai Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728128535

The privacy issues become a major problem that should be resolved for the existing centralized online social networks, which have prompted researchers to consider the decentralization framework for online social networks. In this paper, we propose a novel decentralized social networking architecture enhanced by blockchain technology. We use a sharding framework to increase the system scalability, a blockchain system to ensure the data integrity and consistency, a reputation-based authority control method to improve the system security. © 2019 IEEE.

关键词： Blockchain

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Shell layer oxygen vacancies enhance the microwave-absorbing properties of TiN@CN/WO3-x multiple heterogeneous materials

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Diamond and Related Materials 2025年 157卷

作者： Li, Qian Shi, Guimei Wang, Nan Guo, Qing Geng, Mingqian Dai, Yuxiang Qi, Yang Zhang, Bowen School of Materials Science and Engineering Shenyang University of Technology Liaoning Shenyang110870 China School of Science Shenyang University of Technology Economic Liaoning Shenyang110870 China School of Intelligent Medicine China Medical University Liaoning Shenyang110122 China Department of Materials Physics and Chemistry School of Materials Science and Engineering and State Key Laboratory of Rolling and Automation Northeastern University Liaoning Shenyang110819 China

In this study, TiN@CN/WO3-x nanocomposites were prepared by the combination of reactive plasma-metal reaction method, self-polymerization reaction of dopamine and heat-treated process. The cubic crystal shape of TiN, nitrogen-doped carbon shell layer (5–8 nm thickness) and heterogeneous composite of WO3-x were confirmed by XRD, Raman spectroscopy, XPS and TEM characterization. Electromagnetic parameter tests show that the introduction of WO3-x modulates the synergistic effect of dielectric loss (Ε″) and magnetic loss (μ″) through interfacial polarization and oxygen vacancy defects. The reflection loss results show that the TCW-2 sample has an optimal reflection loss of −56.20 dB at a thickness of 3.1 mm, and an effective absorption bandwidth (RL 3-x optimizes the impedance matching and attenuation factor of the material, which provides a new strategy for the development of broadband and high-efficiency wave-absorbing materials. © 2025 Elsevier B.V.

关键词： Plasma polymerization

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state Estimation for Integrated Energy systems: Motivations, Advances, and Future Work

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IEEE Transactions on Power systems 2024年

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on state Estimation (SE) for Integrated Energy systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy systems-state Estimation (IES-SE) and more established Electric Power system-state Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： Power system analysis

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Online reinforcement learning control by direct heuristic dynamic programming: from time-driven to event-driven

arXiv

引用

arXiv 2020年

作者： Zhao, Qingtao Si, Jennie Sun, Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China Department of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

In this paper time-driven learning refers to the machine learning method that updates parameters in a prediction model continuously as new data arrives. Among existing approximate dynamic programming (ADP) and reinforcement learning (RL) algorithms, the direct heuristic dynamic programming (dHDP) has been shown an effective tool as demonstrated in solving several complex learning control problems. It continuously updates the control policy and the critic as system states continuously evolve. It is therefore desirable to prevent the time-driven dHDP from updating due to insignificant system event such as noise. Toward this goal, we propose a new event-driven dHDP. By constructing a Lyapunov function candidate, we prove the uniformly ultimately boundedness (UUB) of the system states and the weights in the critic and the control policy networks. Consequently we show the approximate control and cost-to-go function approaching Bellman optimality within a finite bound. We also illustrate how the event-driven dHDP algorithm works in comparison to the original time-driven dHDP. Copyright © 2020, The Authors. All rights reserved.

关键词： Learning algorithms

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Maintenance Optimization for Combined Heat and Power Unit Based on Opportunistic Maintenance Strategy

Maintenance Optimization for Combined Heat and Power Unit Ba...

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IEEE/IAS Industrial and Commercial Power system Asia (I&CPS Asia)

作者： Yumin Zhang Xingquan Ji Yixiao Yu Bo Xu Xueshan Han Lin Zhang College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Energy Research Institute Co. Beijing China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

Integrated energy system is composed of different multiple energy systems. When the combined heat and power (CHP) unit fails, more than one energy systems can be influenced. Therefore, it is very important to improve the reliability of CHP unit. In this paper, we propose a maintenance decision making model for CHP unit based on opportunistic maintenance strategy. Firstly, the expression of the availability of CHP unit considering opportunistic maintenance is derived. And then, in order to quantify the impact of different maintenance strategies on system operation, system operation risk is given taking electrical load loss and thermal load loss into account. Finally, maintenance decision making model of the CHP unit is established with maintenance constraints. Case studies show that the model can optimize maintenance strategies and improve the reliability of CHP unit and the overall system efficiency.

关键词： Maintenance engineering Cogeneration Reliability Power system reliability Resistance heating Couplings

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