检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Wang, Jiang He, Yuanzheng Su, Daobilige Itoyama, Katsutoshi Nakadai, Kazuhiro Wu, Junfeng Huang, Shoudong Li, Youfu Kong, He The Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology No. 1088 Xueyuan Avenue Shenzhen China The College of Engineering China Agricultural University Beijing China The Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan The School of Data Science The Chinese University of Hong Kong Shenzhen China The Robotics Institute University of Technology Sydney Sydney Australia The Department of Mechanical Engineering City University of Hong Kong Hong Kong

Robot audition systems with multiple microphone arrays have many applications in practice. However, accurate calibration of multiple microphone arrays remains challenging because there are many unknown parameters to be identified, including the relative transforms (i.e., orientation, translation) and asynchronous factors (i.e., initial time offset and sampling clock difference) between microphone arrays. To tackle these challenges, in this paper, we adopt batch simultaneous localization and mapping (SLAM) for joint calibration of multiple asynchronous microphone arrays and sound source localization. Using the Fisher information matrix (FIM) approach, we first conduct the observability analysis (i.e., parameter identifiability) of the above-mentioned calibration problem and establish necessary/sufficient conditions under which the FIM and the Jacobian matrix have full column rank, which implies the identifiability of the unknown parameters. We also discover several scenarios where the unknown parameters are not uniquely identifiable. Subsequently, we propose an effective framework to initialize the unknown parameters, which is used as the initial guess in batch SLAM for multiple microphone arrays calibration, aiming to further enhance optimization accuracy and convergence. Extensive numerical simulations and real experiments have been conducted to verify the performance of the proposed method. The experiment results show that the proposed pipeline achieves higher accuracy with fast convergence in comparison to methods that use the noise-corrupted ground truth of the unknown parameters as the initial guess in the optimization and other existing frameworks. © 2024, CC BY.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Analysis of electricity loss and electricity consumption law in low-voltage areas: A case study 2

Analysis of electricity loss and electricity consumption law...

引用

2nd International Conference on Advanced Electrical and Energy Systems, AEES 2021

作者： Chen, Xi Song, Chunhe Wang, Tianran Key Laboratory of Network Control System Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China

Electric power is an important resource in energy. With the development of society, the consumption of electric power is more and more. Research on electricity consumption and power loss has become a hot *** this paper, we conduct statistical analysis on the power supply, power consumption and line loss rate of 395 power supply *** loss rate is an indicator to describe electricity *** found that the line loss rate decreased over the course of a *** overall distribution of line loss rate is approximately lognormal distribution. Total daily electricity supply and electricity consumption in the power supply area approximately obey exponential *** terms of electricity consumption, a statistical analysis was made on the daily electricity consumption of 100,000 users in three years, and it was found that the electricity distribution of users was in line with the power law distribution. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Statistical methods

来源：评论

学校读者我要写书评

暂无评论

A DDOS Attack Traffic Classification Model for Industrial Internet Based on CNN-LSTM

A DDOS Attack Traffic Classification Model for Industrial In...

引用

Chinese Automation Congress (CAC)

作者： Weixuan Wei Xianda Liu Chuan Sheng Ansong Feng Shenyang Institute of Automation Chinese Academy of Sciences. Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences College of Information Engineering. Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang University of Chemical Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences. Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Information Engineering. Shenyang University of Chemical Technology Shenyang China

With the continuous development and application of industrial Internet, the weakness of the security defense capability of industrial Internet has become increasingly prominent. This paper presents an end-to-end classification model combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network for DDoS attacks over industrial Internet. By self-learning the spatial and temporal characteristics of the original attack traffic, the model can avoid subjective errors that may occur due to manual selection of features. This method is a feasible means, with an accuracy rate of 99%.

关键词： Automation Neural networks Manuals Denial-of-service attack Internet Convolutional neural networks Security

来源：评论

学校读者我要写书评

暂无评论

Fault Detection and Isolation Based on Unknown Input Set-membership Observer

Fault Detection and Isolation Based on Unknown Input Set-mem...

引用

第三十九届中国控制会议

作者： Xiaomin Fan Wei Zhang Xiaohang Li Laboratory of Intelligent Control and Robotics Shanghai University of Engineering Science

This paper proposes an actuator fault diagnosis method for a class of discrete-time linear dynamic systems subject to unknown but bounded disturbances and noises. The proposed unknown input observer has a new structure and the actuator faults of the system are taken as unknown inputs that provides more robust and more design degrees of freedom. A direct method based on zonotopes is used to estimate the threshold of residual generated by the unknown input observer. Based on the proposed method, a fault detection and isolation strategy using a set of unknown input set-membership observers are presented. The effectiveness of the proposed method is verified by numerical simulation of a flight control system.

关键词： unknown input observer set-membership estimation zonotope fault estimation and isolation

来源：评论

学校读者我要写书评

暂无评论

Deployment Schemes of In-Band Management Mode Based on Industrial SDN Network

Deployment Schemes of In-Band Management Mode Based on Indus...

引用

6G Communications and IoT Technologies (6GIoTT), International Conference on

作者： Jinnan Piao Dong Li Ming Yang Jindi Liu Xueting Yu Zhibo Li Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang 110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110169 China

When software defined network (SDN) is used to deploy the industrial control network, the deployment schemes are different in actual according to the different industrial production business, environment and capital cost. In this paper, we use the in-band management mode to deploy the SDN network in an industrial environment. We design four deployment schemes of the in-band management mode for the industrial SDN network according to the specific requirements of industrial environment and propose an algorithm for controller location selection in the in-band management network. For the four schemes and the algorithm, we use the controller and switches to build a simulation environment according to different schemes and compare the performance between the in-band management and out-of-band management, which shows that the in-band management mode can set up a normal SDN industrial network with applicable network scale and throughput.

关键词： 6G mobile communication Costs Industrial control Production Throughput control systems Internet of Things

来源：评论

学校读者我要写书评

暂无评论

Gait-based Emotion Recognition Using Spatial Temporal Graph Convolutional Networks

Gait-based Emotion Recognition Using Spatial Temporal Graph ...

引用

Computer Information Science and Artificial Intelligence (CISAI), International Conference on

作者： Shiyi Yu Xinde Li Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China Guangdong Intelligent Robotics Institute Dongguan China

ISBN: (纸本)9781665406932

Most of the existing gait emotion recognition methods use spatial convolution or temporal convolution separately. Without integrating these two dimensions, it is easy to loss valid information for emotion analysis. In order to solve this problem, we propose a supervised learning method using Spatial Temporal Graph Convolutional Networks (ST-GCN) to classify emotions into positive, neutral and negative patterns. In addition, we made a new gait dataset called EmoGait3d including 742 real gait skeleton sequences extracted from videos, also annotated with emotion labels. According to the experiment results, our method achieves the accuracy of 92.2% which outperforms current state-of-art algorithms for gait emotion recognition.

关键词： Emotion recognition Information science Convolution Fuses Supervised learning Linguistics Skeleton

来源：评论

学校读者我要写书评

暂无评论

Design of a Novel Autonomous Docking System With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

引用

IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

AGV Semantic Attack Detection Based on Hidden Markov Model

AGV Semantic Attack Detection Based on Hidden Markov Model

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Sichao Zhang Wei Liang Yinlong Zhang Zhibo Pang 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 Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Department of Automation Technology ABB Corporate Research Sweden Vasteras Sweden

ISBN: (纸本)9781728119496

Automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method.

关键词： Wireless communication Conferences Semantics Hidden Markov models Interference Markov processes Radiofrequency interference

来源：评论

学校读者我要写书评

暂无评论

A New Method of Fault Detection and Diagnosis for the Tennessee Eastman Process

A New Method of Fault Detection and Diagnosis for the Tennes...

引用

第32届中国过程控制会议(CPCC2021)

作者： Pengbin Zhang Tao Zou Jingyang Wang Zhijia Yang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang China. Institutes for Robotics and Intelligent ManufacturingChinese Academy of Sciences University of Chinese Academy of Sciences College of Mechanical and Electrical Engineering Guangzhou University State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences Key Laboratory of Networked Control System Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences

This paper proposes a new fault detection and diagnosis(FDD) method for the Tennessee Eastman(TE) large-scale chemical *** method is built integrated with a curve-type recognizer and a dynamic Bayesian network(DBN).The fault detection is carried out utilizing the curve-type recognizer,while the diagnosis is completed using the ***,the recognizer extracts fault symptoms from different times by distinguishes the curves' ***,the DBN is constructed to handle these time-related fault symptoms *** DBN will give the probability of each fault more and more accurately as time goes *** whole procedure consists of 1) deciding monitoring variables using chemical and control engineering knowledge 2) extracting fault symptoms,3) building a *** advantage over other data-driven FDD methods in reasonability and interpretability is also *** last,the simulation results demonstrate the availability of the proposed method.

关键词： A New Method of Fault Detection and Diagnosis for the Tennessee Eastman Process

来源：评论

学校读者我要写书评

暂无评论

Improved Cascade Mask RCNN Single Character Detection Algorithm for Cast Pipe

Improved Cascade Mask RCNN Single Character Detection Algori...

引用

Big Data & Artificial Intelligence & Software Engineering (ICBASE), International Conference on

作者： Fuli Xu Yu Wang Yan Jiang Huaizhen Wang Yong Cui Ye Tao Yisheng Wang Qi Zhang School of Software Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Shanghai Ballsnow Intelligent Technology Co. Ltd Shanghai China Shenyang Zhongke Microcyber Technology Co. Ltd Shenyang China

Due to the interference of blurry background, character occlusion, and low background contrast in the Cast Pipe character images, the detection accuracy and real-time performance cannot meet the requirements of industrial scenes. To address these issues, this paper presents an improvement based on the Cascade Mask RCNN. Firstly, the Channel Attention Mechanism Module (Squeeze-and-Excitation, SE) is embedded into the ResNet structure. By constructing a bottleneck structure with two fully connected layers, the normalized weights are applied to each channel feature to enhance the network representation ability. Secondly, a bottom-up structure is introduced after the Feature Pyramid Networks (FPN) to transmit the strong localization information from lower-level features to higher-level semantic features. Thirdly, an adaptive pooling layer is added to allocate the candidate regions generated by the Region Proposal Network (RPN) to different scale feature maps. Additionally, skip connections are introduced between the bottom-level features and the highest-level features of each stage to reduce model parameters while retaining global representation capabilities. The improved algorithm is tested on a cast pipe dataset, achieving an average detection accuracy (mAP) of 98.7%, which is 2.7% higher than that of Cascade Mask RCNN. The accuracy indicates that the improved performance is superior to the original algorithm.

关键词：

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：