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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and Civil engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong LY Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat school of engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

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Recursive Filtering for Stochastic Systems With Filter-and-Forward Successive Relays

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1202-1212页

作者： Hailong Tan Bo Shen Qi Li Hongjian Liu school of Mathematics-Physics and Finance Anhui Polytechnic UniversityWuhu 241000China Anhui future Technology Research institute Anhui Polytechnic UniversityWuhu 241000China College of Information science and Technology Donghua UniversityShanghai 201620China engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China school of Information science and engineering Hangzhou Normal UniversityHangzhou 311121China

In this paper,the recursive filtering problem is considered for stochastic systems over filter-and-forward successive relay(FFSR)*** FFSR is located between the sensor and the remote filter to forward the *** the successive relay,two cooperative relay nodes are adopted to forward the signals alternatively,thereby existing switching characteristics and inter-relay interferences(IRI).Since the filter-and-forward scheme is employed,the signal received by the relay is retransmitted after it passes through a linear *** objective of the paper is to concurrently design optimal recursive filters for FFSR and stochastic systems against switching characteristics and IRI of ***,a uniform measurement model is proposed by analyzing the transmission mechanism of ***,novel filter structures with switching parameters are constructed for both FFSR and stochastic *** the help of the inductive method,filtering error covariances are presented in the form of coupled difference ***,the desired filter gain matrices are further obtained by minimizing the trace of filtering error ***,the stability performance of the filtering algorithm is analyzed where the uniform bound is guaranteed on the filtering error ***,the effectiveness of the proposed filtering method over FFSR is verified by a three-order resistance-inductance-capacitance circuit system.

关键词： filtering successive stochastic

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The Caching and Pricing Strategy for Information-Centric networking with Advertisers’Participation

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China Communications 2024年第3期21卷 283-295页

作者： Zheng Quan Yan Wenliang Wu Rong Tan Xiaobin Yang Jian Yuan Liu Xu Zhenghuan Laboratory for future networks Department of AutomationUniversity of Science and Technology of ChinaHefei 230026China institute of Artificial intelligence Hefei Comprehensive National Science CenterHefei 230088China institute of Advanced Technology University of Science and Technology of ChinaHefei 230088China Suzhou Nuclear Power Research institute Suzhou 215004China National engineering Laboratory for Public Safety Risk Perception and Control by Big Data(NEL-PSRPC) China Academy of Electronics and Information Technology of CETCBeijing 100041China

As users’access to the network has evolved into the acquisition of mass contents instead of IP addresses,the IP network architecture based on end-to-end communication cannot meet users’***,the Information-Centric networking(ICN)came into *** a technical point of view,ICN is a promising future network *** and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of *** current research on ICN pricing mechanism is focused on paid ***,we study an ICN pricing model for free content,which uses game theory based on Nash equilibrium to *** this work,advertisers are considered,and an advertiser model is established to describe the economic interaction between advertisers and ICN *** solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each *** extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.

关键词： advertisers cache free content Information-Centric networking pricing strategy

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Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

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Defence Technology（防务技术） 2024年第3期33卷 573-587页

作者： Qu Wang Meixia Fu Jianquan Wang Lei Sun Rong Huang Xianda Li Zhuqing Jiang Yan Huang Changhui Jiang school of Automation science and Electrical engineering University of Science and Technology BeijingBeijing100083China Shunde Innovation school University of Science and Technology BeijingFo Shan528399China Research institute of China Unicom Beijing100190China school of Artificial intelligence Beijing University of Posts and TelecommunicationsBeijing100876China Department of Automation Tsinghua University Beijing100084China GEOLOC Laboratory Universite Gustave EiffelParis77454France

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time ***,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with *** paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual *** at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent *** at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding *** at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude *** conduct extensive and well-designed experiments to evaluate the performance of the proposed *** experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

关键词： Indoor positioning Inertial navigation system(INS) Zero-velocity update(ZUPT) Internet of things(IoTs) Location-based service(LBS)

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Improving the electrical performances of InSe transistors by interface engineering

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Chinese Physics B 2024年第4期33卷 153-158页

作者：曹天俊郝松吴晨晨潘晨戴玉頔程斌梁世军缪峰 institute of Brain-Inspired intelligence National Laboratory of Solid State MicrostructuresSchool of PhysicsCollaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China institute of Interdisciplinary Physical sciences School of PhysicsNanjing University of Science and TechnologyNanjing 210014China

InSe has emerged as a promising candidate for next-generation electronics due to its predicted ultrahigh electrical ***,the efficacy of the InSe transistor in meeting application requirements is hindered due to its sensitivity to *** this study,we have achieved notable enhancement in the electrical performance of InSe transistors through interface *** engineered an InSe/h-BN heterostructure,effectively suppressing dielectric layer-induced ***,we successfully established excellent metal-semiconductor contacts using graphene ribbons as a buffer *** a methodical approach to interface engineering,our graphene/InSe/h-BN transistor demonstrates impressive on-state current,field-effect mobility,and on/off ratio at room temperature,reaching values as high as 1.1 mA/μm,904 cm^(2)·V^(-1)·s^(-1),and>10~6,*** computations corroborate that the graphene/InSe heterostructure shows significant interlayer charge transfer and weak interlayer interaction,contributing to the enhanced performance of InSe *** research offers a comprehensive strategy to elevate the electrical performance of InSe transistors,paving the way for their utilization in future electronic applications.

关键词： two-dimensional materials InSe van der Waals heterostructure electrical performances charge density difference

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Intelligent fault diagnosis methods toward gas turbine: A review

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Chinese Journal of Aeronautics 2024年第4期37卷 93-120页

作者： Xiaofeng LIU Yingjie CHEN Liuqi XIONG Jianhua WANG Chenshuang LUO Liming ZHANG Kehuan WANG school of Transportation science and engineering Beihang UniversityBeijing 100191China Systems engineering Research institute China State Shipbuilding CorporationBeijing 100094China

Fault diagnosis plays a significant role in conducting condition-based maintenance and health management for gas turbines(GTs) to improve reliability and reduce costs. Various diagnosis methods developed by modeling engine systems or certain components implement faults detection and diagnosis based on the measurement of systemic parameters deviations. However, these conventional model-based methods are hindered by limitations of inability to handle the nonlinear nature, measurement uncertainty, fault coupling and other implementing problems. Recently, the development of artificial intelligence algorithms has provided an effective solution to the above problems, triggering broad researches for data-driven fault diagnosis methods with better accuracy,dynamic performance, and universality. This paper presents a systematic review of recently proposed intelligent fault diagnosis methods for GT engines, according to the classification of shallow learning methods, deep learning methods and hybrid intelligent methods. Moreover, the principle of typical algorithms, the evolution of enhanced methods, and the assessment of pros and cons are summarized to conclude the present status and look forward to the future in the field of GT fault diagnosis. Possible directions for development in method validation, information fusion, and interpretability of intelligent diagnosis methods are concluded in the end to provide insightful concepts for scholars in related fields.

关键词： Fault diagnosis Health management Gas turbine Artificial intelligence Intelligent diagnosis method

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Advancements in Humanoid Robots: A Comprehensive Review and future Prospects

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 301-328页

作者： Yuchuang Tong Haotian Liu Zhengtao Zhang IEEE CAS engineering Laboratory for Intelligent Industrial Vision Institute of AutomationChinese Academy of SciencesBeijing 100190China school of Artificial intelligence University of Chinese Academy of SciencesBeijing 100049China

This paper provides a comprehensive review of the current status, advancements, and future prospects of humanoid robots, highlighting their significance in driving the evolution of next-generation industries. By analyzing various research endeavors and key technologies, encompassing ontology structure,control and decision-making, and perception and interaction, a holistic overview of the current state of humanoid robot research is presented. Furthermore, emerging challenges in the field are identified, emphasizing the necessity for a deeper understanding of biological motion mechanisms, improved structural design,enhanced material applications, advanced drive and control methods, and efficient energy utilization. The integration of bionics, brain-inspired intelligence, mechanics, and control is underscored as a promising direction for the development of advanced humanoid robotic systems. This paper serves as an invaluable resource, offering insightful guidance to researchers in the field,while contributing to the ongoing evolution and potential of humanoid robots across diverse domains.

关键词： future trends and challenges humanoid robots human-robot interaction key technologies potential applications

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Grasp Detection with Hierarchical Multi-Scale Feature Fusion and Inverted Shuffle Residual

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Tsinghua science and Technology 2024年第1期29卷 244-256页

作者： Wenjie Geng Zhiqiang Cao Peiyu Guan Fengshui Jing Min Tan Junzhi Yu State Key Laboratory of Multimodal Artificial intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China school of Artificial intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Grasp detection plays a critical role for robot *** pixel-wise grasp detection networks with encoder-decoder structure receive much attention due to good accuracy and ***,they usually transmit the high-level feature in the encoder to the decoder,and low-level features are *** is noted that low-level features contain abundant detail information,and how to fully exploit low-level features remains ***,the channel information in high-level feature is also not well ***,the performance of grasp detection is *** solve these problems,we propose a grasp detection network with hierarchical multi-scale feature fusion and inverted shuffle *** low-level and high-level features in the encoder are firstly fused by the designed skip connections with attention module,and the fused information is then propagated to corresponding layers of the decoder for in-depth feature *** a hierarchical fusion guarantees the quality of grasp ***,an inverted shuffle residual module is created,where the high-level feature from encoder is split in channel and the resultant split features are processed in their respective *** such differentiation processing,more high-dimensional channel information is kept,which enhances the representation ability of the ***,an information enhancement module is added before the encoder to reinforce input *** proposed method attains 98.9%and 97.8%in image-wise and object-wise accuracy on the Cornell grasping dataset,respectively,and the experimental results verify the effectiveness of the method.

关键词： grasp detection hierarchical multi-scale feature fusion skip connections with attention inverted shuffle residual

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Multimodal Fusion of Brain Imaging Data: Methods and Applications

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Machine intelligence Research 2024年第1期21卷 136-152页

作者： Na Luo Weiyang Shi Zhengyi Yang Ming Song Tianzi Jiang Brainnetome Center and National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China school of Artificial intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Excellence in Brain science and intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Research Center for Augmented intelligence Zhejiang LaboratoryHangzhou 311100China

Neuroimaging data typically include multiple modalities,such as structural or functional magnetic resonance imaging,dif-fusion tensor imaging,and positron emission tomography,which provide multiple views for observing and analyzing the *** lever-age the complementary representations of different modalities,multimodal fusion is consequently needed to dig out both inter-modality and intra-modality *** the exploited rich information,it is becoming popular to combine multiple modality data to ex-plore the structural and functional characteristics of the brain in both health and disease *** this paper,we first review a wide spectrum of advanced machine learning methodologies for fusing multimodal brain imaging data,broadly categorized into unsupervised and supervised learning *** by this,some representative applications are discussed,including how they help to under-stand the brain arealization,how they improve the prediction of behavioral phenotypes and brain aging,and how they accelerate the biomarker exploration of brain ***,we discuss some exciting emerging trends and important future ***,we intend to offer a comprehensive overview of brain imaging fusion methods and their successful applications,along with the chal-lenges imposed by multi-scale and big data,which arises an urgent demand on developing new models and platforms.

关键词： Multimodal fusion supervised learning unsupervised learning brain atlas cognition brain disorders

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the school of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer engineering University of Illinois at ChicagoChicago IL 60607 USA the school of Information and Control engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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