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2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Meihui Li Chunhe Song Xia Yu Mengmeng Chu Rui Li Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Shenyang University of Technology Shenyang China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

Printed circuit board defect recognition is of great significance to ensuring the quality of electronic products. This paper proposes an improved PCB defect detection method based on YOLOV8. Firstly, the data augmentation method PredMix (prediction mix) is adopted to simulate scenarios such as overlapping and occlusion in images, where the displays are incomplete or blurred, thereby enhancing the robustness of the network model. Secondly, BiFPN is used to replace PAN-FPN in the fusion layer to strengthen the feature fusion capability. Finally, the CESE_C2f module is employed in the Backbone part, leveraging a lightweight attention mechanism to improve the detection effect while reducing the number of parameters. Experimental results show that compared with the original YOLOV8, the MAP value of this improved algorithm reaches $\mathbf{92.6}\%$, with a $\mathbf{2.3\%}$ increase in accuracy.

关键词： Accuracy Costs Printed circuits Diversity reception Production Feature extraction Data augmentation Data models Real-time systems Defect detection

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Transmission Optimization Based on Industrial Internet Information Model 4

Transmission Optimization Based on Industrial Internet Infor...

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4th International Conference on Machine Learning and Computer Application, ICMLCA 2023

作者： Feng, Haiwen Tian, Hao Wang, Ting Zhu, Jingyang Wang, Xintong School of Software College 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

ISBN: (纸本)9798400709449

With the standardized development of industrial Internet, the communication among industrial Internet platforms, devices and gateways is more frequent. Due to the problems of heterogeneous data and low data interoperability existing in different devices, the communication between industrial Internet is hindered. With the development of industrial Internet information model, on the basis of reducing data heterogeneity and improving interoperability, it is more difficult to transmit information due to the increase of information content. Therefore, this paper will design an information model transmission optimization method, through the information model XML file content optimization compression, while in the information model may exist in the Chinese information processing, so that it can better compress the Chinese-English information. The results show that the XML file used in information transmission can be compressed by using this optimization method, and it is proved that the proposed optimization method can improve the transmission efficiency. © 2023 ACM.

关键词： Interoperability

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A Multi-Model Fusion Approach for Transformer Fault Detection 4

A Multi-Model Fusion Approach for Transformer Fault Detectio...

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

作者： Zhou, Ke Zhang, Wei Li, Ligang Pan, Shaoming Huang, Chengwei Electric Power Research Institute of Guangxi Power Grid CO. LTD. Guangxi Power Grid Equipment Monitoring and Diagnosis Technology Innovation Center Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Nanning530023 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems China Power Supply Bureau of Guangxi Hezhou Power Grid Co. Ltd. China

ISBN: (纸本)9798350363586

Addressing the weak generalization capability and suboptimal prediction performance of single mechanistic and data-driven models, this paper proposes a transformer fault detection method based on the fusion of mechanism and data models. Firstly, vibration and current data are collected on-site to train the SVM vibration model and the Adaboost current model. Secondly, current simulation data is obtained using laboratory simulation software. This simulation data, combined with the current data collected under the same conditions on-site, is used as input to train the GBDT error compensation model. Finally, these three models are used as inputs to the GRNN, completing the overall model design. This fusion of mechanistic and data-driven models not only addresses the parameter mismatch issue of the mechanistic model under complex working conditions but also deeply mines time-series data. Experimental results show that The mean squared error of the fusion model is 0.002 lower than that of the data model, and the coefficient of determination is improved by 5.07% compared to the mechanistic model, enhancing the overall predictive accuracy of the model. © 2024 IEEE.

关键词： Data accuracy

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Path Planning with Potential Field-Based Obstacle Avoidance in a 3D Environment by an Unmanned Aerial Vehicle

arXiv

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arXiv 2023年

作者： Batinovic, Ana Goricanec, Jurica Markovic, Lovro Bogdan, Stjepan University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Unska 3 Zagreb10000 Croatia

In this paper we address the problem of path planning in an unknown environment with an aerial robot. The main goal is to safely follow the planned trajectory by avoiding obstacles. The proposed approach is suitable for aerial vehicles equipped with 3D sensors, such as LiDARs. It performs obstacle avoidance in real time and on an on-board computer. We present a novel algorithm based on the conventional Artificial Potential Field (APF) that corrects the planned trajectory to avoid obstacles. To this end, our modified algorithm uses a rotation-based component to avoid local minima. The smooth trajectory following, achieved with the MPC tracker, allows us to quickly change and re-plan the UAV trajectory. Comparative experiments in simulation have shown that our approach solves local minima problems in trajectory planning and generates more efficient paths to avoid potential collisions with static obstacles compared to the original APF method. © 2023, CC BY-SA.

关键词： Motion planning

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A 5G-Based Switching Method between a Local controller and an Edge controller 6

A 5G-Based Switching Method between a Local Controller and a...

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6th International Conference on intelligent robotics and control Engineering, IRCE 2023

作者： Wang, Xiulian Lin, Jinggao Jin, Xi Xia, Changqing Xu, Chi College of Automation and Electrical Engineering Shenyang Ligong University China 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)9798350326338

With the rapid development of edge computing, industrial automation has evolved a two-layer distributed computing architecture, including local controllers communicating through wired networks and edge controllers communicating wirelessly. The edge controllers in existing studies use WIFI, which has a limited working distance and requires independent network deployment, so they are unsuitable for future large-scale complex industrial production. At present, 5G technology is undergoing rapid development in the field of industrial automation, with wide coverage and excellent mobility, gradually becoming suitable for future large-scale and complex industrial production scenarios. Therefore, this paper proposed an SW5G method based on 5G, which combined the local controller with the edge controller. The controllers were switched according to the constantly changing 5G network transmission delay, thereby optimizing the overall system control performance. Finally, simulation experiments demonstrated good control performance of SW5G in various network scenarios. © 2023 IEEE.

关键词： controllers

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Research on Sensorless control of Pulse Generator based on Sliding Mode Observer

Research on Sensorless Control of Pulse Generator based on S...

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Artificial Intelligence and Automation control (AIAC), International Conference on

作者： Hui Zhang Zhiguo Wu Bopi Jin Shengxuan Yang Guoliang Yin College of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China Shenyang Institute of Automation & Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences College of Electrical and Control Engineering Shenyang Jianzhu University & State Key Laboratory of Robotics Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences & Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

To address the problems of chattering and slow response in the sliding mode control system of surface-mounted permanent magnet synchronous motor (SPMSM), a novel sliding mode controller combined with an enhanced sliding mode observer is proposed. A new reaching law of sliding mode is designed, which uses the tanh function as the switching function of the control system to smooth the switching process. The terminal attractor is introduced to improve the convergence speed and control quality of the system. An improved sliding mode observer is developed, which replaces the sign function with a continuous function, compensates for the observation error, reduces the chattering effect, and improves the observation accuracy. A simulation model of double closed-loop speed control system based on the proposed sliding mode controller and observer is established, and a simulation experiment is conducted to compare it with the PI control system and the sliding mode control system based on exponential reaching law. The simulation results show that the proposed control strategy can effectively diminish the chattering effect, enhance the system convergence, and better track the given signal.

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Design and Validation of a Wireless Drone Docking Station

arXiv

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arXiv 2023年

作者： Stuhne, Dario Vasiljević, Goran Bogdan, Stjepan Kovačić, Zdenko LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb10000 Croatia

Drones are increasingly operating autonomously, and the need for extending drone power autonomy is rapidly increasing. One of the most promising solutions to extend drone power autonomy is the use of docking stations to support both landing and recharging of the drone. To this end, we introduce a novel wireless drone docking station with three commercial wireless charging modules. We have developed two independent units, both in mechanical and electrical aspects: the energy transmitting unit and the energy receiving unit. We have also studied the efficiency of wireless power transfer and demonstrated the advantages of connecting three receiver modules connected in series and parallel. We have achieved maximum output power of 96.5 W with a power transfer efficiency of 56.6% for the series connection of coils. Finally, we implemented the system in practice on a drone and tested both energy transfer and landing. Copyright © 2023, The Authors. All rights reserved.

关键词： Drones

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Pedestrian Target Detection Model Based on Improved Yolov8 5

Pedestrian Target Detection Model Based on Improved Yolov8

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5th International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2024

作者： Huang, Jinglun Liang, Jianan Cao, Yongjun School of Electronics and Information Engineering Wuyi University Guangdong Jiangmen China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing Gdas Guangdong Guangzhou China South China Robotics Innovation Research Institute Guangdong Foshan China School of Mechanical & Automotive Engineering South China University of Technology Guangdong Guangzhou China

ISBN: (纸本)9798350366174

Dense pedestrian detection is a key technology in public intelligent surveillance. It identifies the location and number of pedestrians in videos through object detection methods, thereby achieving intelligent surveillance of crowds. However, in crowded scenes, due to occlusion and small pedestrian targets, it is easy to miss pedestrians. To solve this problem, this paper proposes an improved YOLOv8 detection algorithm, YOLOv-8FastTCD. Firstly, the FasterNet module is used to replace the backbone network. Secondly, a task collaborative dynamic detection head (TCDDH) is introduced after the neck network. The performance of this model on the CrowdHuman dense pedestrian detection dataset has been improved, with mAP50 and mAP50-95 reaching 78.4% and 51.5% respectively, which are 2.1% and 2.0% higher than the original YOLOv8n model. © 2024 IEEE.

关键词： FasterNet Pedestrian Detection TCDDH YOLOv8

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Virtual chain: A storage model supporting cross-blockchain transaction

Virtual chain: A storage model supporting cross-blockchain t...

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作者： Wang, Yan Yang, Bingqing Liu, Jingxin Zeng, Hui Xia, Changqing College of Information Liaoning University Shenyang China State key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

At present, blockchain is not only applied in the financial field, but also extended to the medical, insurance, internet of things, and many other fields. Its independence leads to more and more significant problems of network isolation. To address the problem of the cooperative operation between different blockchains, this article proposes virtual chain, a storage model supporting cross-blockchain transaction. It not only ensures that cross-chain transactions are tamper-proof and traceable but also realizes completely decentralized storage. First, to tackle the multidimensional heterogeneous problem existing in cross-chain trading, a data structure based on prefix tree is proposed to manage cross-chain trading data on top of source chain and target chain. Second, a signature verification mechanism based on elliptic curve is proposed to meet the operational atomicity requirements of both parties of cross-chain transaction. Third, the data fusion technology is used to expand the block capacity indirectly to achieve the high throughput of cross-chain transactions. Finally, by using the credibility-based access control and block chain technology to ensure the security of the data storage model, and conduct security analysis from three aspects of tamper-proof, data protection and anti-conspiracy node attack. The experiment shows that the proposed cross-chain transaction storage model can realize the efficient storage of the heterogeneous data, and satisfy the high requirement of the cross-chain transaction. Moreover, the virtual chain storage model establishes a safe and reliable working environment. © 2020 John Wiley & Sons Ltd.

关键词： Blockchain

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An Optimization Method for SLAM Feature Point Extraction in Fuzzy Scenes

An Optimization Method for SLAM Feature Point Extraction in ...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Yunmeng Wang Long Cui Zaoming Liu Nailong Liu State Key Laboratory of Robotics Shenyang Institute of Automation 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 Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China

In order to solve the problem that image blur is easily caused by camera shaking of micro-robots during surgical navigation, which leads to the accumulation of SLAM errors, this paper studies the feature point extraction optimization method based on deep learning in fuzzy scenes, proposes an improved defuzzification network, and finally applies the network to the front end of SLAM, and conducts experimental verification on the open data set TUM. The results show that the proposed algorithm significantly improves the accuracy of front-end feature extraction and matching.

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