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Industrial Wireless control Networks:From WIA to the Future

Engineering 2022年第1期8卷 18-24页

作者： Haibin Yu Peng Zeng Chi Xu 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

*** Industrial automation is undergoing a significant innovation as information,communication,and operation technologies are deeply integrating with each *** this trend,industrial wireless control networks(IWCNs)are becoming increasingly attractive to industrial automation since they can help speed up production efficiency,reduce cost,enhance safety,and finally realize intelligent manufacturing[1].

关键词： attractive integrating becoming

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Improved Detection of Transmission Tower Equipment Using YOLOv7 with Saliency Data Augmentation 5

Improved Detection of Transmission Tower Equipment Using YOL...

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5th International Conference on Clean Energy and Electric Power Engineering, ICCEPE 2024

作者： Xu, Yingying Song, Chunhe Sun, Yong Yu, Shimao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350390315

Transmission towers are critical infrastructure for power transmission, and the reliable operation of their equipment is essential to ensure electricity supply. However, the detection of transmission tower equipment faces challenges such as target overlap, large variations in size, small targets, and class imbalance due to the characteristics of the equipment. To tackle the identified issues, this study introduces a method based on YOLOv7 for the detection of transmission tower components, utilizing saliency-based data augmentation. Initially, an approach focusing on importance is employed to augment the sample size in categories with limited numbers, thereby enhancing the effectiveness of detection. Secondly, an adaptive adjustment module is introduced into the multi-head self-attention mechanism to dynamically adjust attention allocation based on the actual size of the targets and integrate contextual information, thus better handling targets with large size variations and overlaps. Finally, incorporating dynamic convolution within the backbone network significantly improves the ability to extract features from small objects. The outcomes of the experiments confirm the efficiency of the suggested approach in the smart surveillance of devices within intricate transmission settings, offering a reliable solution for maintaining power supply dependability. © 2024 IEEE.

关键词： Critical infrastructures

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Design and Experimental Validation of a Worm-Like Tensegrity Robot for In-Pipe Locomotion

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Journal of Bionic Engineering 2023年第2期20卷 515-529页

作者： Xiaolin Dai Yixiang Liu Wei Wang Rui Song Yibin Li Jie Zhao School of Control Science and Engineering Shandong UniversityJinan250061China Engineering Research Center of Intelligent Unmanned System of Ministry of Education Jinan250061China Shandong Research Institute of Industrial Technology Jinan250061China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150080China

Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and *** soft in-pipe robots have great improvements in flexibility,they still have manufacturing difficulties due to their reliance on high-performance soft *** structure is a kind of self-stressed spatial structure consisting discrete rigid struts connected by a continuous net of tensional flexible strings,which combines the advantages of both rigid structures and soft *** applying tensegrity structures into robotics,this paper proposes a novel worm-like tensegrity robot for moving inside ***,a robot module capable of body deformation is designed based on the concept of tensegrity and its deformation performance is ***,the optimal parameters of the module are obtained based on the tensegrity *** deformation ability of the tensegrity module is tested ***,the worm-like tensegrity robot that can crawl inside pipes is developed by connecting three modules in *** performance and load capacity are tested on the prototype of the worm-like tensegrity robot by experiments of moving in horizontal pipe,vertical pipe,and elbow *** results demonstrate the effectiveness of the proposed design and suggest that the robot has high compliance,mobility,and adaptability although with simple structure and low cost.

关键词： Bio-inspired robot Soft robot application Tensegrity structure Pipe crawling

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Extraction algorithm for longitudinal and transverse mechanical information of AFM

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Nanotechnology and Precision Engineering 2022年第2期5卷 27-37页

作者： Chunxue Hao Shoujin Wang Shuai Yuan Boyu Wu Peng Yu Jialin Shi School of Information and Control Engineering Shenyang Jianzhu UniversityShenyang 110168China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of SciencesShenyang 110169China

The atomic force microscope(AFM)can measure nanoscale morphology and mechanical properties and has a wide range of *** traditional method for measuring the mechanical properties of a sample does so for the longitudinal and transverse properties separately,ignoring the coupling between *** this paper,a data processing and multidimensional mechanical information extraction algorithm for the composite mode of peak force tapping and torsional resonance is *** the basis of a tip–sample interaction model for the AFM,longitudinal peak force data are used to decouple amplitude and phase data of transverse torsional resonance,accurately identify the tip–sample longitudinal contact force in each peak force cycle,and synchronously obtain the corresponding characteristic images of the transverse amplitude and *** results show that the measured longitudinal mechanical characteristics are consistent with the transverse amplitude and phase characteristics,which verifies the effectiveness of the ***,a new method is provided for the measurement of multidimensional mechanical characteristics using the AFM.

关键词： Atomic force microscope Peak force tapping Torsional resonance Mechanical characteristic measurement Background subtraction algorithm Coupled mechanical model

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Robustness to Disturbances of Ellipsoid-Shape Underwater Vehicle with Multi-Link Manipulator

Robustness to Disturbances of Ellipsoid-Shape Underwater Veh...

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International Russian Automation Conference (RusAutoCon)

作者： Ivan Lipko Kirill Dementiev Vadim Kramar Robotics and Intelligent Control Systems Laboratory Sevastopol State University Sevastopol Russian Federation

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

This article is devoted to the issue of analyzing the influence of external disturbances on the underwater vehicle in the form of a flattened ellipsoid body with a multilink manipulator when performing technological operations. The relevance of the study is related to the automation of such operations as underwater welding, transfer of objects, twisting, bending, etc., performed underwater. For this purpose, we have built a mathematical model of the underwater apparatus with an ellipsoid shape, indicated the ways of influence of moments and forces arising in the manipulator on the apparatus body. It was found out that this influence leads to nonlinear effects in transients. This influence is different, depending on the axis in which the motion of the apparatus is performed. Since the body is flattened in the horizontal axis, the most unpleasant effect occurs in the vertical motion, due to the increased hydrodynamic resistance. The model is considered without a control loop in the apparatus, and it is the effect of the housing on the accuracy of movements of a multilink manipulator with a standard control system in the form of PID controllers that is important to us.

关键词： Automation Shape Welding Manipulators control systems Robustness Transient analysis Underwater vehicles Standards Ellipsoids

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Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

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Petroleum Science 2023年第2期20卷 1142-1154页

作者： Yun-Peng He Chuan-Zhi Zang Peng Zeng Ming-Xin Wang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyangLiaoning 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyangLiaoning 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyangLiaoning 110169China University of Chinese Academy of Sciences Beijing100049China Shenyang University of Technology ShenyangLiaoning 110870China School of Automation and Electrical Engineering Shenyang Ligong UniversityShenyangLiaoning 110159China

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

关键词： Few-shot learning Indicator diagram Meta-learning Soft thresholding Sucker-rod pumping system Time–frequency signature Working condition recognition

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Towards Disturbance Rejection in Feature Pyramid Network

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 946-958页

作者： Hu, Xiaobo Xu, Wei Gan, Yi Su, Jianbo Zhang, Jun Shanghai Jiao Tong University Joint Institute of UM-SJTU Shanghai200240 China Shanghai Jiao Tong University Research Center of Intelligent Robotics Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

The multiscale problem is one of the challenging topics in the object detection field. Among the current studies toward this problem, feature pyramid network (FPN) has been shown a superior performance. The core principle of FPN is a mapping for the detectable objects into hierarchy features. These features are designed with different size of receptive fields, which brings good scale invariance in the classification and localization subtasks. However, a disturbance of information dilution is generated by the assignment for the detectable objects into different features. This dilution disturbance is associated with the convolution or pooling operation during the hierarchy feature extraction process. Both of the imprecise localization information in the top features and the fuzzy classification information in the bottom ones limit the performance of FPN. Aiming at the disturbance rejection problem of information dilution, this article presents a feature compensation method. A cross compensation between the semantic information and the localization information in hierarchy features is used to enhance the vanilla FPN. Then, the evaluation metrics in an object detection task are examined. Not only the overall performance, but also the respective metrics for multiscale objects validate a considerable improvement of the FPN with a disturbance compensation mechanism. The experimental results demonstrate an effectiveness of the proposed method in this article. © 2020 IEEE.

关键词： Object detection

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High-Accuracy Pose Estimation for 3D Reconstruction Considering the Manipulator Motion Constraints with an Eye-in-Hand RGB-D Camera 42

High-Accuracy Pose Estimation for 3D Reconstruction Consider...

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42nd Chinese control Conference, CCC 2023

作者： Zhou, Yanling Zhang, Xuebo Wang, Runhua Zhang, Shiyong Yuan, Mingxing Yuan, Jing Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300350 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education China

ISBN: (纸本)9789887581543

Three-dimensional(3D) environmental reconstruction of the manipulator workspace is a prerequisite to enable autonomous collision-free path planning and subsequent task execution, wherein the positioning accuracy of the equipped sensor is one key issue to determine the performance of 3D reconstruction. In this paper, an eye-in-hand RGB-D camera is used to complete the manipulator workspace scanning and a novel high-accuracy pose estimation method for 3D reconstruction is proposed, which not only considers the geometric and photometric constraints constructed from the visual information used in traditional methods, but also considers the manipulator motion constraints since the positioning accuracy of the manipulator is usually high. Based on above three constraints, three error functions are constructed respectively and fused with different weights to form an integrated objective function. Then, the problem is converted into solving the least squares problem by the Gaussian Newton nonlinear iterative method, which involves the computation of Jacobian matrices and residuals of the three error functions. To this end, the mathematical derivation of their formulas considering the manipulator motion constraints are given in detail. By qualitative and quantitative experimental comparison with traditional methods, the proposed method can greatly improve the accuracy of pose estimation and 3D reconstruction, which always maintains the error within 3 cm, and show good robustness even in the challenging environments with weak texture or geometric features. (Supplemented video link: https://***/FkFTxssnWms) © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Manipulators

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Advances and Challenges in Large Model Compression: A Survey 24

Advances and Challenges in Large Model Compression: A Survey

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, DEAI 2024

作者： Xu, Yingying Song, Chunhe Sun, Yong Yu, Shimao 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 Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798400717147

With the development of computer technology, large-scale models have gradually evolved from early simple algorithms to today's complex deep neural networks with huge parameter scale and high computational complexity. These large-scale models have greatly advanced the artificial intelligence technology, which has realized revolutionary progress in the fields of image, speech, text and so on. However, the computational and storage requirements of large-scale models are also growing rapidly, which seriously constrains their deployment and application in computing resource-constrained environments. In order to solve this problem, model compression technology has emerged and has been greatly developed. In this paper, we systematically review the key technologies, application scenarios, challenges and future directions of large-scale model compression from the perspective of model compression technology. Our work aims to provide practitioners and researchers with detailed references on the development of the technology, and emphasizes the important role of model compression technology in promoting the development of lightweight artificial intelligence. © 2024 Owner/Author.

关键词： Deep neural networks

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Research and Implementation of Industrial Real-Time Ethernet Scheduling Method Based on Time Slot Reuse 5

Research and Implementation of Industrial Real-Time Ethernet...

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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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