检索结果-内蒙古大学图书馆

IEEE Information Technology, Networking, Electronic and Automation control Conference

作者： Wang Gao Lin Pu Lei Li Fei Deng Lingzhi Bie Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Institute of Mechanical and Electrical Engineering Beijing China School of Geodesy and Geomatics Wuhan University Wuhan China Wuhan Tianjihang Information Technology Co. Ltd Wuhan China

Aiming at the problem that the current depth estimation of single image mostly uses the ground public data set, and there is less research on aerial images, this paper uses the collected visible and infrared aerial image data sets to study the depth estimation. We used FCRN and LapDRN to extract the depth estimation results of visible aerial image and infrared aerial image under global and single object respectively, and compared the results extracted from the two types of networks by qualitative and quantitative methods. The results show that the depth estimation accuracy of visible aerial image is higher than that of infrared image, but the increase rate of infrared image accuracy index is higher than the increase rate of image depth range. The image depth estimation results extracted by LapDRN method are superior to FCRN in accuracy, structure consistency and edge clarity, which indicates that LapDRN is more effective in the estimation of aerial image depth information.

关键词： Automation Image edge detection Estimation Data mining Indexes

来源：评论

学校读者我要写书评

暂无评论

Recurrent Attentional Reinforcement Learning for Fault Diagnosis of Hydraulic system

Recurrent Attentional Reinforcement Learning for Fault Diagn...

引用

International Conference on control, Decision and Information Technologies (CoDIT)

作者： Zhenhui Tang Ru Liu Kang Lou Chaojian Gao Jingcheng Wang SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya China Department of Automation Shanghai Jiao Tong University Shanghai China Shanghai Marine Equipment Research Institute Shanghai China Department of Automation the Key Laboratory of System Control and Information Processing Ministry of Education of China and the Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University Xi'an China

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Recognizing fault types of machinery system is a fundamental but challenging task in industrial application. Although data-driven fault diagnosis method attains remarkable progress by learning fault features automatically, the existing data-driven fault diagnosis pipelines learn non-discriminative feature. To deal with these problems, a new data-driven fault diagnosis method with recurrent attentional module is proposed to find a sequence of informative features by localizing distinguishing time fragments about each individual faults iteratively. The contextual sequence dependency between the localized time fragments is enhanced. Then, the fault types are further predicted on localized time fragments. The proposed framework also explicitly models long-term dependencies among these attentional time fragments to capture historical fault information. Experiments on hydraulic system show that the proposed framework achieves superior diagnosis performance and computation efficiency.

关键词： Fault diagnosis Location awareness Accuracy Computational modeling Pipelines Reinforcement learning Hydraulic systems Computational efficiency Information technology

来源：评论

学校读者我要写书评

暂无评论

MG-SLAM: Structure Gaussian Splatting SLAM with Manhattan World Hypothesis

arXiv

引用

arXiv 2024年

作者： Liu, Shuhong Deng, Tianchen Zhou, Heng Li, Liuzhuozheng Wang, Hongyu Wang, Danwei Li, Mingrui Department of Information Science and Technology Department of Complexity Science and Engineering The University of Tokyo Tokyo113-8654 Japan Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Mechanical Engineering Columbia University New York10027 United States School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science Dalian University of Technology Dalian116024 China

Gaussian Splatting SLAMs have made significant advancements in improving the efficiency and fidelity of real-time reconstructions. However, these systems often encounter incomplete reconstructions in complex indoor environments, characterized by substantial holes due to unobserved geometry caused by obstacles or limited view angles. To address this challenge, we present Manhattan Gaussian SLAM, an RGB-D system that leverages the Manhattan World hypothesis to enhance geometric accuracy and completeness. By seamlessly integrating fused line segments derived from structured scenes, our method ensures robust tracking in textureless indoor areas. Moreover, The extracted lines and planar surface assumption allow strategic interpolation of new Gaussians in regions of missing geometry, enabling efficient scene completion. Extensive experiments conducted on both synthetic and real-world scenes demonstrate that these advancements enable our method to achieve state-of-the-art performance, marking a substantial improvement in the capabilities of Gaussian SLAM systems. © 2024, CC BY.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

Robust Output Synchronization of Discrete-Time Linear-Time-Invariant Multi-Agent systems Using Phase Tool

Robust Output Synchronization of Discrete-Time Linear-Time-I...

引用

European control Conference (ECC)

作者： Xin Mao Dan Wang Wei Chen Li Qiu School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Mechanics and Engineering Science State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Southern University of Science and Technology Shenzhen China Hong Kong University of Science and Technology Hong Kong S.A.R. China

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In this paper, the output synchronization in large-scale discrete-time networks is examined by utilizing the novel phase tool, where the agent dynamics are allowed to be significantly heterogeneous. The synchronization synthesis problem is formulated and thoroughly investigated, with the goal of characterizing the allowable heterogeneity among the agents to ensure synchronization under a uniform controller. The solvability condition is provided in terms of the phases of the residue matrices of the agents at the persistent modes. When the condition is satisfied, a design procedure is given, producing a low-gain synchronizing controller. Numerical examples are given to illustrate the results.

关键词： Sufficient conditions Europe Heterogeneous networks Synchronization Multi-agent systems

来源：评论

学校读者我要写书评

暂无评论

Hierarchy-based extended CBBA for multi-robot task assignment

Hierarchy-based extended CBBA for multi-robot task assignmen...

引用

Chinese Automation Congress (CAC)

作者： Jiajun Liu Weiguo Xia Fuqiang Li Peng Wang China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology China

This paper studies the task assignment problem of a multi-robot system with complex constraints including the robot speed limit, the task execution time window constraints, the arrival time, the trip cost, and different priorities of the tasks. A new bidding function is then designed for each robot. Based on the k-means algorithm, a hierarchy-based extended consensus-based bundle algorithm (CBBA) is proposed to find the optimal solution for the task allocation problem. Finally, simulation examples are presented to show the feasibility of the proposed algorithm and comparisons with existing algorithms show that the proposed algorithm can reduce the task assignment time with guaranteed reward values.

关键词： Costs Automation Heuristic algorithms Numerical simulation Time factors Resource management Multi-robot systems

来源：评论

学校读者我要写书评

暂无评论

Prediction of Hybrid Asynchronous Frequency Hopping Pattern based on Deep Learning in Wideband Spectrum

Prediction of Hybrid Asynchronous Frequency Hopping Pattern ...

引用

Chinese Automation Congress (CAC)

作者： Ya Wang Jiaqi Wang Shuai Yuan Naijin Liu Yuanming Lu Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China Unit 63893 of PLA Luoyang China

In non-cooperative scenarios, wideband frequency hopping (FH) communication reconnaissance including FH signal detection, parameter estimation, and network sorting under single-channel reception is challenging. The FH pattern contains the most information about FH signals. So it is the core of FH parameter estimation. Based on the task analysis, this paper proposes a blind prediction framework combining deep learning (DL) and clustering methods to improve the accuracy and efficiency of FH pattern estimation for mixed signals in the wideband spectrum. The unique advantage of this framework is that it requires no prior signal information and anchors but exploits the inherent time-frequency (TF) properties of asynchronous FH signals. It has a strong generalization ability and can adapt to signals of any shape. Moreover, a new comprehensive evaluation metric, normalized root mean square error including missed detection (NRMSE-MD), suitable for sequence data prediction is proposed to evaluate the level of missed detection and false detection in signal monitoring. Experimental results demonstrate the superiority of the proposed framework and the effectiveness of the proposed evaluation metric.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Recurrent Attentional Reinforcement Learning for Machinery Fault Diagnosis

SSRN

引用

SSRN 2024年

作者： Tang, Zhenhui Wang, Jingcheng Wu, Shunyu The Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University No.800 Dongchuan Road Shanghai200240 China The SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya572024 China The Autonomous Systems and Intelligent Control International Joint Research Center Xi’an Technological University Xi’an710021 China

Recognizing fault types of machinery system is a fundamental but challenging task in industrial application. Although remarkable progress has been attained by learning fault features and predicting the corresponded fault type with deep neural networks, the existing fault diagnosis pipelines usually learn non-discriminative information. Contextual sequence dependency between the localized time fragments is often ignored. To deal with these problem, a recurrent attention framework with reinforcement learning is proposed to find a series of informative features of local time fragments related to different faults in an iterative manner. Fault labels are further predicted on these time fragments. The proposed framework also explicitly models long-term dependencies among these attentional time fragments to capture historical fault information. Experiments on two typical machinery systems, bearing system and hydraulic system, show that the proposed framework achieves superior diagnosis performance and increases no computation burden on CPU. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

An Efficient Planning and control Framework for Quadrotors Based on Heuristic Search and Data-Driven Model Predictive control

引用

IEEE Transactions on Industrial Electronics 2025年

作者： Wang, Sifei Wang, Yaonan Miao, Zhiqiang Wang, Xiangke He, Wei Wang, Hesheng Hunan University College of Electrical and Information Engineering Changsha 410082 China National Engineering Research Center for Robot Visual Perception and Control Changsha 410082 China National University of Defense Technology College of Intelligence Science and Technology Changsha 410073 China Beijing Information Science and Technology University School of Automation Institute of Artificial Intelligence Beijing 100083 China University of Science and Technology School of Intelligence Science and Technology Beijing 100083 China Shanghai Jiao Tong University Department of Automation Shanghai 200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai 200240 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin 150001 China

This article presents a framework for quadrotors that integrate planning and control, which employs a heuristic depth-first search (HDFS) with data-driven model predictive control (MPC). The proposed framework intends to enable multiquadrotor systems to traverse cluttered environments containing obstacles and disturbances. The heuristic function enables quadrotors to identify a secure route in a timely manner. The heuristic function setup employed by HDFS results in a reduction in the number of rasters accessed, particularly in scenarios that are not labyrinthine. This consequently leads to an enhancement in computational speed for multiquadrotor systems when compared to the A* algorithm. Furthermore, data-driven MPC enhances the nominal model of the quadrotor by modeling the disturbance while tracking the desired states. Consequently, data-driven MPC is capable of attaining superior tracking precision in a disturbance environment when compared to MPC without data-driven. The transformation from the path to the desired states of the quadrotor is achieved through the utilization of B-splines and differential flatness. Simulations and experiments substantiate the efficacy of the proposed approach. © 1982-2012 IEEE.

关键词： Collision avoidance data-driven depth-first search model predictive control multiquadrotor systems

来源：评论

学校读者我要写书评

暂无评论

Dynamic Stiffness Analysis and Experimental Verification of Axial Magnetic Bearing Based on Air Gap Flux Variation in Magnetically Suspended Molecular Pump

引用

Chinese Journal of Mechanical engineering 2020年第4期33卷 139-149页

作者： Jinji Sun Wanting Wei Jiqiang Tang Chun‑E Wang Key Laboratory of Fundamental Science for National Defense Novel Inertial Instrument and Navigation System TechnologySchool of Instrument Science and Opto‑Electronics EngineeringBeihang UniversityBeijing 100191China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China Beijing Institute of Automatic Control Equipment Beijing 100074China

Current and displacement stiffness are important parameters of axial magnetic bearing(AMB)and are usually considered as constants for the control ***,in actual dynamic work situations,time-varying force leads to time-varying currents and air gap with a specific frequency,which makes the stiffness of appear decrease and even worsens control performance for the whole *** this paper,an AMB dynamic stiffness model considering the flux variation across the air gap due to frequency is established to obtain the accurate dynamic *** dynamic stiffness characteristics are analyzed by means of the dynamic equivalent magnetic circuit *** analytical results show that the amplitude of current and displacement stiffness decreases with frequency ***,compared with the stiffness model without considering the variation of flux density across the air gap,the improved dynamic stiffness results are closer to the actual *** the dynamic stiffness measurement method of AMB,experiments of AMB in magnetically suspended molecular pump(MSMP)are carried out and the experimental results are consistent with theoretical analysis *** paper proposes the dynamic stiffness model of axial magnetic bearing considering the variation of flux density across the air gap,which improves the accuracy of the AMB stiffness analysis.

关键词： Axial magnetic bearing(AMB) Dynamic stiffness Magnetically suspended molecular pump(MSMP)

来源：评论

学校读者我要写书评

暂无评论

Tuning the Donor - Acceptor Ratio in Resorcinol - Formaldehyde Resin to Achieve Superior Photocatalytic Hydrogen Peroxide Production

SSRN

引用

SSRN 2025年

作者： Wang, Wuming Tang, Yuyang Ran, Jiaqi Peng, Cheng Chu, Wenhai State Key Laboratory of Pollution Control and Resources Reuse College of Environmental Science and Engineering Tongji University Shanghai200092 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China International Joint Research Center for Sustainable Urban Water System Tongji University Shanghai200092 China Key Laboratory of Interfacial Physics and Technology Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201800 China Tongji University China

Photocatalytic production of hydrogen peroxide (H2O2) represents a clean and sustainable method to produce H2O2 in recent years. Although this vision is very appealing, the development of high - performance catalysts remain a critical challenge in this field. Resorcinol-formaldehyde resin, a newly identified semiconductor material, has demonstrated significant potential for H2O2 production, owing to its distinctive structural characteristics and catalytic activity. Within this resin, phenolic and quinone units serve as electron donors and acceptors, respectively, forming conjugated donor - acceptor (D - A) pairs. This conjugated network facilitates charge carrier separation and migration under light irradiation, ultimately leading to the generation of H2O2 through interaction with molecular oxygen. Nevertheless, the effect of the relative content of electron donors and acceptors on photocatalytic activity has yet to be fully elucidated. To address this knowledge gap and enhance the performance of resins, this study systematically investigated the relationship between the donor - acceptor ratio and photocatalytic H2O2 production. Our findings demonstrated a robust linear correlation (R2 = 0.99) between the D - A ratio and the photocatalytic H2O2 yield. Within a specific range, a lower D - A ratio resulted in enhanced light absorption, improved charge carrier separation efficiency, and subsequently, higher photocatalytic activity for H2O2 production. The resorcinol - formaldehyde resin with optimized D - A ratio achieved an energy conversion efficiency of 1.3 % over 5 hours, outperforming all catalysts reported to date. This work provided a deeper understanding of the intrinsic structure - activity relationship within D - A type photocatalysts, offering a novel perspective for the development of high - performance catalysts. © 2025, The Authors. All rights reserved.

关键词： Light absorption

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：