检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Jin, Xi Chai, Haoxuan Xia, Changqing Xu, Chi Zeng, Peng Key Laboratory of Networked Control Systems 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 Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

5G is an advanced solution for industrial wireless motion control. However, since the scheduling model of 5G new radio (NR) is more complicated than those of other wireless networks, existing real-time scheduling algorithms cannot be used to improve the 5G performance. This results in NR resources not being fully available for industrial systems. Supervised learning has been widely used to solve complicated problems, and its advantages have been demonstrated in multiprocessor scheduling. One of the main reasons why supervised learning has not been used for 5G NR scheduling is the lack of training datasets. Therefore, in this paper, we propose two methods based on optimization modulo theories (OMT) and satisfiability modulo theories (SMT) to generate training datasets for 5G NR scheduling. Our OMT-based method contains fewer variables than existing work so that the Z3 solver can find optimal solutions quickly. To further reduce the solution time, we transform the OMT-based method into an SMT-based method and tighten the search space of SMT based on three theorems and an algorithm. Finally, we conduct extensive evaluations. The evaluation results indicate that our SMT-based method reduces the solution time by 74.7% compared to existing ones. © 2022, The Authors. All rights reserved.

关键词： Scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection of Marine Diesel Engine Valve System based on Mahalanobis Distance

Anomaly Detection of Marine Diesel Engine Valve System based...

引用

2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020

作者： Sun, Yue Xu, Aidong Wang, Kai Jia, Shuli Guo, Haifeng Han, Xiaojia Laboratory of Industrial Control Network and System State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Shenyang China Automation Engineering Department Shanghai Marine Diesel Engine Research Institute Shanghai China

ISBN: (纸本)9781728159454

Diesel engine is an important energy equipment. The valve system is the core component of diesel engine with high failure rate. It is of great significance to study the abnormal detection method of the diesel engine valve system and realize the failure warning before the failure occurs for avoiding the unexpected shutdown of the diesel engine. In this paper, an anomaly detection method of marine diesel engine valve system based on Mahalanobis distance (MD) is proposed. The failure mode of diesel engine system is analyzed. Three thermal parameters are selected as monitoring parameters for the failure mode of roller fragmentation. Fault features are extracted by MD method and the failure threshold is determined by Box-Cox transformation. Finally, the effectiveness of the proposed method is verified by the durability test of diesel engine. © 2020 IEEE.

关键词： Diesel engines

来源：评论

学校读者我要写书评

暂无评论

Edge computing-based defect identification model of power IoT edge side devices

Edge computing-based defect identification model of power Io...

引用

2020 IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2020

作者： Li, Dawei Jia, Gengtao Song, Chunhe Yu, Shimao Start Grid Shanghai Information Telecommunication Company Shanghai200122 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang11016 China

ISBN: (纸本)9781728152240

There are various types of devices on the terminal side of the power Internet of Things, and the data collected through various sensors shows an exponential growth. The current in-depth application of edge computing technology can not only ease the pressure of network transmission, but also improve the timeliness of fault diagnosis. Edge computing technology is A new way to solve the fault diagnosis of equipment on the edge of the power grid. From the perspective of edge fault diagnosis, this paper expounds the fault diagnosis model of power IoT edge devices based on edge computing, and combines the isolated forest algorithm to design smart sensor data-based power IoT edge device fault diagnosis algorithms. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 IEEE.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Distributed computing framework of intelligent sensor network for electric power internet of things 9

Distributed computing framework of intelligent sensor networ...

引用

9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Li, Dawei Yu, Ruimo Song, Chunhe Li, Shu Jia, Gengtao Zhou, Xiaoli Start Grid Shanghai Information Telecommunication Company Shanghai200122 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

The power IoT terminal environment is complex, and current smart sensor sensors have problems such as poor networking capabilities and large processing delays, and few specific edge-side automatic networking capabilities. This paper analyzes and elaborates the distributed intelligent sensor computing framework from the perspective of edge intelligent networking, designs a computing model for intelligent sensors of power Internet of Things terminals, and gives the edge-based deployment of convolutional neural network architecture, data aggregation, model training, and intelligent reasoning. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Information modeling and verification method for edge computing of power internet of things 9

Information modeling and verification method for edge comput...

引用

9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Li, Dawei Chen, Xiaolu Song, Chunhe Yu, Shimao Start Grid Shanghai Information Telecommunication Company Shanghai200122 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

There are various types of power Internet of Things terminals, and a unified edge-side information fusion model is the basis of data unification. This article describes the unified modeling method of power Internet of Things terminal information, and describes the construction method of the Internet of Things terminal information model from three aspects: attribute, message and service. Combined with the characteristics of the electric power Internet of Things information model, a model verification method is given. Finally, through the terminal data on the edge side of the power Internet of Things, the feasibility and effectiveness of the model verification method are verified. © 2020 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Kernel-VIO : An Optimization-based Tightly Coupled Indirect Visual-Inertial Odometry

Kernel-VIO : An Optimization-based Tightly Coupled Indirect ...

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Shuyue Lin Xuetao Zhang Yisha Liu Yuqing Chen Yan Zhuang Intelligent Robotics Laboratory School of Artificial Intelligence Also School of Control Science and Engineering Dalian University of Technology Dalian China School of Information Science and Technology Dalian Maritime University Dalian China

ISBN: (纸本)9781665431545

This paper proposes an optimization-based tightly coupled Indirect Visual-Inertial Odometry (Kernel-VIO), which weights outliers with hybrid kernel functions. The novelty is that the hybrid weighting method based on kernel functions is firstly extended to the indirect-based VIO, which reduces the weight of outliers by dynamically weighting reprojection residual items, thereby the method suppresses adverse effects of outliers on the state estimator. Specifically, the proposed system processes the visual measurements and the IMU pre-integration in a tightly coupled way, next aligns the two information to complete the system initialization. Then, a nonlinear optimization framework is established by jointly minimizing the IMU pre-integration residuals, the reprojection residuals and prior information of sliding window marginalization to estimate the state of drones. The comparative experiments on the public dataset show that the accuracy and robustness of Kernel-VIO is better than the VINS-Mono without loop closure, and simulations demonstrate the effectiveness of the proposed Kernel-VIO.

关键词： Visualization Mechatronics Machine vision Robustness Kernel State estimation Optimization

来源：评论

学校读者我要写书评

暂无评论

Multimode Industrial Process Monitoring using Hierarchical Mode Division and Serial Independent Component Analysis

Multimode Industrial Process Monitoring using Hierarchical M...

引用

第32届中国过程控制会议(CPCC2021)

作者： Shuai Li Xiaofeng Zhou Haibo Shi 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 University of Chinese Academy of Sciences

With the increasing scale and complexity,how to analyze the hybrid characteristics including multimode,nonGaussianity and nonlinearity is one of the most difficult problems faced by multimode industrial process *** paper proposes a monitoring method using hierarchical mode division with serial independent component analysis for multimode processes with *** the multimodal uncertainty and transition mode,hierarchical mode information with transitions is first obtained by mode division using hierarchical density peaks ***,by integrating independent component analysis(ICA) and kernel independent component analysis(KICA) using the serial structure,a hybrid non-Gaussian and nonlinear process modeling method using serial independent component analysis is used for hierarchical process ***,the stable and transition mode identification using geodesic distance is developed for multimode industrial process *** monitoring results for the penicillin fermentation process show the feasibility and effectiveness.

关键词： Process monitoring multimode industrial process transition mode hierarchical mode division serial independent component analysis

来源：评论

学校读者我要写书评

暂无评论

Design and implementation of FPGA-based hardware acceleration system for target detection

Design and implementation of FPGA-based hardware acceleratio...

引用

Chinese Automation Congress (CAC)

作者： Canyu Zhan Bingjie Zhao Huangliang Zhang Zhongpeng Yan Jie Wu Da Yuan Shenyang University of Chemical Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China Shenyang University of Technology Shenyang China

Since the application of target detection in convolutional neural networks is becoming more and more widespread, and the computational volume is increasing, the complexity of the network hierarchy and the memory requirements are gradually increasing, so according to the Field Programmable Gate Array (FPGA) parallel computing characteristics, using FPGA to accelerate the convolutional neural network hardware, can design a CPU+FPGA target detection hardware acceleration system. The system adopts the YOLOv2 target detection algorithm and divides the tasks according to the network structure of the algorithm, and at the same time, it quantifies the 32-bit floating-point numbers of the algorithm with 16-bit fixed points, optimizes the convolutional, pooling, and reordering layers of the algorithm, and finally designs the algorithm by using the HLS high-level synthesis. The system uses PYNQ-Z2 platform to implement the convolutional neural network YOLOv2, and the final system performance reaches 27.06GOPs (Giga Operations Per Second, 1 billion operations/s), and the power consumption is only 2.609W, compared to CPU (E5-2620V4), its performance is 6.58 times that of CPU, and the power consumption is only 3% of the CPU, which has certain advantages compared with current target detection systems.

关键词： Power demand System performance Software algorithms Object detection Software System-on-chip Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Towards Collision Detection, Localization and Force Estimation for a Soft Cable-driven Robot Manipulator

Towards Collision Detection, Localization and Force Estimati...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Yuxin Wang Hesheng Wang Fan Xu Junzhi Yu Weidong Chen Yun-Hui Liu Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Institute of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai China College of Engineering Peking University Beijing China The Chinese University of Hong Kong Hong Kong

Soft robots have been applied widely to various constrained scenarios due to the advantages over traditional rigid manipulators such as softness, deformability and adaptability to constrained surroundings. To make full use of this merit, this paper proposes a method that integrates collision detection, localization and force estimation for a cable-driven soft manipulator without any prior geometrical knowledge of its surroundings. First of all, a collision detection algorithm is presented based upon Cosserat-rod statics by a threshold method through using the cable tension and the shape information, which are obtained by the load cells and the Vicon system, respectively. Secondly, a collision localization and force estimation method is proposed through optimizing the discrepancy between the actual and the theoretical shapes. Finally, experiments are carried out to validate these algorithms. The experimental results demonstrate that the site, the magnitude as well as the direction can be estimated.

关键词： Location awareness Shape Conferences Force Estimation Soft robotics Manipulators

来源：评论

学校读者我要写书评

暂无评论

Hybrid Vision/Force control for Interaction with the Bottle-like Object

Hybrid Vision/Force Control for Interaction with the Bottle-...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Lijun Han Hesheng Wang Weidong Chen Jingchuan Wang Jianjun Yuan Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Shanghai Robotics Institute School of Mechatronic Engineering and Automation Shanghai University Shanghai China

This study proposes a hybrid vision/force control scheme for interaction with the inner surface of the bottle-like object. Based on the geometry of the object, a new generalized constraint called the bottleneck (BN) constraint is proposed, which ensures the tool passes through a fixed 3-D region and avoid collisions with the boundary of the region. To realize the hybrid vision/force control under the BN constraint, a novel dynamic controller is designed inspired by the hierarchical operational space, which can complete the different tasks defined in the decoupled subspace. To enhance the robustness of the algorithm, we develop a data-driven method and an adaptive method to estimate the Jacobian matrix online in force space and image space, respectively. The asymptotic stability of the closed-loop system is rigorously proved by the Lyapunov theory. Experiments are conducted to validate the performance of the proposed method.

关键词： Jacobian matrices Geometry Heuristic algorithms Robot vision systems Force Aerospace electronics Tools

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：