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5th International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2024

作者： Gang, Mingxu Yan, Bingjun Hu, Bo 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

ISBN: (纸本)9798350385557

To improve the operation efficiency and real-time scheduling capability of existing industrial control network systems, based on the existing industrial real-time Ethernet communication protocol technology, an industrial real-time Ethernet scheduling method based on time slot reuse is proposed. This method adopts the time-division multiplexing strategy, decomposes the continuous time into different time slots, configures the data of different types of nodes to be transmitted in their respective time slots, uses the peak shift clock synchronization method and timer trigger task mechanism to improve the real-time communication, and uses the time slot multiplexing mechanism to improve the data transmission efficiency;Finally, a test platform is built to verify the proposed method. The experimental results show that the proposed method has high clock synchronization accuracy and real-time scheduling capability. © 2024 IEEE.

关键词： Synchronization

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Characteristics of laser-induced breakdown spectroscopy of liquid slag

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Plasma Science and Technology 2024年第2期26卷 86-93页

作者：董长言于洪霞孙兰香李洋刘修业周平黄少文 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016People's Republic of China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016People's RepublicofChina Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169People's Republic of China Shenyang University of Technology Shenyang 110870People's Republic of China Shenyang Ligong University Shenyang 1i0142People's Republic of China Shandong Iron and Steel Company Ltd. Jinan 271105People's Republic of China

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

关键词： laser-induced breakdown spectroscopy(LIBS) slag temperature composition viscosity internal standard normalization partial least squares(PLS)

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Unsupervised Anomaly Detection Approach Based on Adversarial Memory Autoencoders for Multivariate Time Series

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Computers, Materials & Continua 2023年第7期76卷 329-346页

作者： Tianzi Zhao Liang Jin Xiaofeng Zhou Shuai Li Shurui Liu Jiang Zhu Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110000China Shenyang Institute of Automation Chinese Academy of SciencesShenyang110000China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110000China University of Chinese Academy of Sciences Beijing100000China

The widespread usage of Cyber Physical Systems(CPSs)generates a vast volume of time series data,and precisely determining anomalies in the data is critical for practical *** is the mainstream method for time series anomaly detection,and the anomaly is judged by reconstruction ***,due to the strong generalization ability of neural networks,some abnormal samples close to normal samples may be judged as normal,which fails to detect the *** addition,the dataset rarely provides sufficient anomaly *** research proposes an unsupervised anomaly detection approach based on adversarial memory autoencoders for multivariate time series to solve the above ***,an encoder encodes the input data into low-dimensional space to acquire a feature ***,a memory module is used to learn the feature vector’s prototype patterns and update the feature *** updating process allows partial forgetting of information to prevent model *** that,two decoders reconstruct the input ***,this research uses the Peak Over Threshold(POT)method to calculate the threshold to determine anomalous samples from normal *** research uses a two-stage adversarial training strategy during model training to enlarge the gap between the reconstruction error of normal and abnormal *** proposed method achieves significant anomaly detection results on synthetic and real datasets from power systems,water treatment plants,and computer *** F1 score reached an average of 0.9196 on the five datasets,which is 0.0769 higher than the best baseline method.

关键词： Anomaly detection autoencoder memory module adversarial training

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A Model Integrating Wavelet Convolution and Linear Attention Mechanism for Inventory Management in Power Warehouses 4

A Model Integrating Wavelet Convolution and Linear Attention...

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4th IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Li, Tao Zhang, Zhengli Li, Ligang Du, Guozheng State Grid Shandong Electric Power Company Material Company Jinan China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China

ISBN: (纸本)9798350363586

Accurate inventory management in power warehouses is crucial for maintaining consistency between records and actual stock levels. However, the complex storage layout and the diversity of stored materials often lead to human errors during manual inventory checks, resulting in inefficiencies. To address these challenges, we collected 2,000 images from power warehouse environments and created a binary classification dataset containing images of correctly and incorrectly placed items. We propose a novel network, CWAMNet, specifically designed for visual inventory management in complex power warehouse environments. CWAMNet integrates wavelet convolution and a linear attention mechanism to overcome the limitations of traditional convolutional neural networks (CNNs) and standard attention mechanisms, achieving a balance between model capacity and computational efficiency. © 2024 IEEE.

关键词： Convolutional neural networks

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Design and Implementation of High Precision Clock Synchronization System Based on RT1064 6

Design and Implementation of High Precision Clock Synchroniz...

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6th International Conference on Communications, Information System and Computer Engineering, CISCE 2024

作者： Gang, Mingxu Yan, Bingjun Hu, Bo Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350353174

To realize the high-precision clock synchronization of various types of control equipment in the industrial process control network, a high-precision clock synchronizing system is designed and implemented. The system uses RT1064 microprocessor as the core, combined with ieee1588v2 high-accuracy clock synchronization protocol, and uses the MAC kernel integrated in rt1064 to support hardware timestamp function to achieve high-precision time synchronization between devices;Finally, the test verification platform is built to test and verify the accuracy. The test results show that the clock synchronization accuracy is within ± 400ns after the system runs stably, which meets the design requirements. © 2024 IEEE.

关键词： Mechanical clocks

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive Systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

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Multi-UAVs Cooperative Pollution Source Localization Based on Improved Particle Swarm Optimization Algorithm

Multi-UAVs Cooperative Pollution Source Localization Based o...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Du, Meiyi Gao, Zhijun Yang, Liying Jiang, Han Huang, Zhaoxiong School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350316308

Accidents involving hazardous gas leakage from chemical plants occur frequently, highlighting the critical importance of accurately locating air pollution sources. Rapid localization of pollution sources through the collaborative efforts of multiple unmanned aerial vehicles (UAVs) can help prevent major disasters. To address this, this paper presents an air pollution source tracking algorithm based on an improved particle swarm optimization (IPSO) algorithm. By enhancing the inertia weight coefficient, the search efficiency and accuracy of the UAV swarm are significantly improved. The simulation environment considers a Gaussian plume model, which incorporates various atmospheric constraints such as temperature and wind speed, for UAV swarm navigation. The simulation results demonstrate that employing the particle swarm optimization algorithm to guide UAVs in locating pollution sources enables them to accurately identify the sources within a short period, exhibiting a high level of effectiveness and robustness. © 2023 IEEE.

关键词： Antennas

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Industrial Internet for intelligent manufacturing:past, present, and future

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Frontiers of Information Technology & Electronic Engineering 2024年第9期25卷 1173-1192页

作者： Chi XU Haibin YU Xi JIN Changqing XIA Dong LI Peng ZENG State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China

Industrial Internet, motivated by the deep integration of new-generation information and communication technology(ICT) and advanced manufacturing technology, will open up the production chain, value chain, and industry chain by establishing complete interconnections between humans, machines, and things. This will also help establish novel manufacturing and service modes, where personalized and customized production for differentiated services is a typical paradigm of future intelligent manufacturing. Thus, there is an urgent requirement to break through the existing chimney-like service mode provided by the hierarchical heterogeneous network architecture and establish a transparent channel for manufacturing and services using a flat network architecture. Starting from the basic concepts of process manufacturing and discrete manufacturing, we first analyze the basic requirements of typical manufacturing tasks. Then, with an overview on the developing process of industrial Internet, we systematically compare the current networking technologies and further analyze the problems of the present industrial *** this basis, we propose to establish a novel “thin waist” that integrates sensing, communication, computing, and control for the future industrial Internet. Furthermore, we perform a deep analysis and engage in a discussion on the key challenges and future research issues regarding the multi-dimensional collaborative sensing of task–resource, the end-to-end deterministic communication of heterogeneous networks, and virtual computing and operation control of industrial Internet.

关键词： Intelligent manufacturing Industrial Internet Thin waist Transparent service Manufacturing as a service

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POWERLINK Communication Fault Detection Method Based on Data Frames Sequence Analysis

POWERLINK Communication Fault Detection Method Based on Data...

引用

2022 International Conference on Signal Processing and Communication Technology, SPCT 2022

作者： Wang, Jian Xie, Chuang Dong, Ce Key Laboratory of Networked Control System ShenYang China Shenyang institute of automation Chinese academy of sciences ShenYang China Institutes for Robotics and Intelligent Manufacturing ChineseAcademy of Sciences ShenYang China

ISBN: (纸本)9781510664333

Fault diagnosis, location and maintenance of industrial networks are extremely important components of network management, which can effectively improve network availability, shorten network failure time, help improve network performance, satisfy network service quality and ensure network security. This paper proposes a communication fault detection method based on the analysis of communication protocol message flow for POWERLINK, an industrial Ethernet protocol widely used in the field of industrial communication at present. By monitoring network status and building fault judgment logic, it can analyze the rationality of message sequence and protocol consistency in the message flow so as to effectively detect the dynamic upper layer protocol fault in the network and determine the location of the fault. In order to verify the effectiveness of this method, we designed a POWERLINK network communication fault diagnosis system, which can correctly identify and analyze the wrong data frame sequence in the data message flow and finally achieve the diagnosis and location of POWERLINK network communication fault. © 2023 SPIE.

关键词： Fault detection

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ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformers

arXiv

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arXiv 2023年

作者： Ausserlechner, Philipp Haberger, David Thalhammer, Stefan Weibel, Jean-Baptiste Vincze, Markus Vision for Robotics Laboratory Automation and Control Institute TU Wien Austria

As robotic systems increasingly encounter complex and unconstrained real-world scenarios, there is a demand to recognize diverse objects. The state-of-the-art 6D object pose estimation methods rely on object-specific training and therefore do not generalize to unseen objects. Recent novel object pose estimation methods are solving this issue using task-specific fine-tuned CNNs for deep template matching. This adaptation for pose estimation still requires expensive data rendering and training procedures. MegaPose for example is trained on a dataset consisting of two million images showing 20,000 different objects to reach such generalization capabilities. To overcome this shortcoming we introduce ZS6D, for zero-shot novel object 6D pose estimation. Visual descriptors, extracted using pre-trained Vision Transformers (ViT), are used for matching rendered templates against query images of objects and for establishing local correspondences. These local correspondences enable deriving geometric correspondences and are used for estimating the object's 6D pose with RANSAC-based PnP. This approach showcases that the image descriptors extracted by pre-trained ViTs are well-suited to achieve a notable improvement over two state-of-the-art novel object 6D pose estimation methods, without the need for task-specific fine-tuning. Experiments are performed on LMO, YCBV, and TLESS. In comparison to one of the two methods we improve the Average Recall on all three datasets and compared to the second method we improve on two datasets. Copyright © 2023, The Authors. All rights reserved.

关键词： Template matching

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