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28th International Conference on automation and Computing, ICAC 2023

作者： Zhu, Wenhui Lin, Qingquan Fu, Xi Wu, Qinggang Tang, Kai Lu, Weining College of Mechanical Engineering Beijing Information Science and Technology University Beijing China Tsinghua University Department of Automation Beijing China Second Research Institute of Civil Aviation Administration of China Chengdu China Civil Unmanned Aircraft Traffic Management Key Laboratory of Sichuan Province Chengdu China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9798350335859

In environments with limited information, intelligent agents have restricted access to their current location, target location, and local environment details. To enhance their perception capabilities, this study introduces a fusion model called GraphSAGE-DH-Bug, which combines GraphSAGE and DH Bug algorithms. More importantly, the article presents the process of generating expert training databases and proposes three criteria for evaluating their effectiveness. These contributions establish the groundwork for applying the GraphSAGE-DH-Bug fusion model to multi-agent exploration in unknown environments. The experimental results validate the effectiveness of the generated dataset, which accurately represents the extended perception range of agents through the inclusion of neighboring agents. © 2023 IEEE.

关键词： Autonomous agents

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An improved moving object tracking algorithm based on CAMSHIFT

An improved moving object tracking algorithm based on CAMSHI...

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2021 3rd International Conference on applied Machine Learning and Data Science, ICAMLDS 2021

作者： Yang, Xiaoyan Yang, Jinyu Department of Electronic Software Engineering Institute of Guangzhou Guangdong510990 China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan610059 China

There is a problem that Camshift algorithm relies too much on color as a criterion, in order to solve it, this paper presented an improved moving object tracking algorithm which combined Kalman filter predictor with Camshift algorithm. Firstly, the object model was built by Camshift Algorithm, and the centroid coordinates of the moving objectwere extracted, then the position of the object in the next frame was predicted by using Kalman filter, and finally, the value was used as the centroid coordinates of the object searched by Camshift algorithm in the next frame, proceeding with target match. The simulation results showed that this method can effectively solve the problem of target loss caused by the similar color between the target and the back. The new algorithm can effectively reduce the tracking error accumulation in the tracking process, greatly reduce the template drift, shorten the tracking time, and can have a better practicability and real-time performance. © Published under licence by IOP Publishing Ltd.

关键词： Kalman filters

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A Novel Chain Multi-UAV Communication Relay Maintenance Control 21

A Novel Chain Multi-UAV Communication Relay Maintenance Cont...

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21st International Computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2024

作者： Cancan, Tao Yiao, Zhan Jiancheng, Zhang Pengyu, Zhang Xin, Zhao Yaowei, Yu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China School of Astronautics Harbin Institute of Technology Harbin150001 China School of Mathematics and Physics Center for Applied Mathematics of Guangxi Guangxi Minzu University Nanning530006 China School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China School of Mechanical and Electrical Engineering Hohai University Changzhou213200 China College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing211106 China

ISBN: (纸本)9798331519254

To ensure real-time feedback of the observation information from the remote tracking UAV, multiple UAVs are used to construct a communication relay chain between the tracking UAV and the ground base station. The problem is decomposed into two sub-problems: (1) initial communication relay formation;(2) continuous communication relay maintenance. For the former, a simultaneous arrival algorithm based on the Dubins curve is proposed to form the initial configuration of multi-UAV cooperative communication maintenance;for the latter, considering constraints such as platform performance, communication constraints, collision avoidance, etc., a distributed nonlinear model predictive control algorithm is used to dynamically optimize the control inputs of each UAV, achieving continuous maintenance of multi-UAV collaborative communication. The simulation results have verified the feasibility and effectiveness of the proposed method. © 2024 IEEE.

关键词： Predictive control systems

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A Novel Fruit Shape Classification Method: BLS-Levelset

A Novel Fruit Shape Classification Method: BLS-Levelset

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International Conference on Information Science and technology (ICIST)

作者： Dan Zhang Tieshan Li C.L. Philip Chen Yi Zuo College of Mechanical and Electrical Engineering Dalian Minzu University Dalian China College of Automation Engineering University of Electronic Science and Technology Chengdu China College of Computer Science and Engineering South China University of Technology Guangzhou China College of Navigation Dalian Maritime University Dalian China

ISBN: (数字)9798350353334

ISBN: (纸本)9798350353341

Although some fruits have a fixed shape, but the growth process, the shape will still be different, different fruit shape has a certain impact on the subsequent fruit classification and selection. In order to realize fruit shape classification quickly and accurately, a novel fruit shape classification method based on level set and broad learning system(BLS) is proposed in this paper. Firstly, fruit shape information is extracted based on level set, then fruit image information is extracted based on BLS, and finally, shape information and fruit information are fused to carry out fruit shape classification research. The method was applied to the classification of the fruit shape, and the experimental results showed the effectiveness of the proposed method.

关键词： Information science Shape Level set Optimization methods Lighting Feature extraction Data mining

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A Temporal Convolutional Network Based Method for Fault Diagnosis of DEH System 3

A Temporal Convolutional Network Based Method for Fault Diag...

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3rd IEEE International Conference on Communications, Information System and Computer engineering, CISCE 2021

作者： Peng, Shichen Zhang, Jiyang Glasgow College University of Electronic Science and Technology of China Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9780738112152

The Digital Electric Hydraulic (DEH) system is quite important for the safe operation of steam turbine, and the fault diagnosis of DEH has attracted a lot attention for the accident reduction of turbines. In this paper, a Temporal Convolutional Network (TCN) based fault diagnosis method was proposed to monitor the running state of DEH system. Building the offline modeling on the data generated from a simulated DEH system, the fault diagnosis performance was evaluated on independent data. Comparing with other methods, such as LSTM and SVM, our TCN model outperformed them in both fault detection accuracy and false alarm rate, which indicated that our proposed TCN model had great potentiality in the application of DEH system. © 2021 IEEE.

关键词： Failure analysis

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An ${H_\infty }$ Load Frequency Control Scheme for Multi-Area Power System Under Cyber-Attacks and Time-Varying Delays

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IEEE Transactions on Power Systems 2022年第2期38卷 1336-1349页

作者： Guangdou Zhang Jian Li Olusola Bamisile Yankai Xing Dongsheng Cai Qi Huang Power System Wide-Area Measurement and Control Sichuan Province Key Laboratory School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu Sichuan China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan China

In the power system, the application of the signals transmitted from the sensors to the controller can significantly improve the dynamic performance. However, cyber-attacks and time delays exist widely in the communication network, which has a considerable effect on stability, operation, and control. In this paper, an ${{\boldsymbol{H}}_\infty }$ load frequency control (LFC) scheme for multi-area power systems under cyber-attacks and time-varying delays is investigated. First, false data injection attacks (FDIA), as well as denial of service (DoS) attacks, are viewed as two typical cyber-attacks and introduced into the multi-area power system. Then, the state-space equations of the LFC power system under these two attacks and time-varying delays are analyzed and modeled. Furthermore, by using Lyapunov stability theory and linear matrix inequality (LMI) method, an ${{\boldsymbol{H}}_\infty }$ LFC scheme for attacked and delayed power systems is developed. The purpose of the proposed controller is to guarantee the closed-loop system exponentially mean-square stable with prescribed ${{\boldsymbol{H}}_\infty }$ performance. Finally, a three-area LFC system is employed to demonstrate the effectiveness of the proposed mechanism. The simulation results verified that the control performance of an attacked and delayed system can be improved significantly via the designed controller.

关键词： Power system stability Delays Frequency control Delay effects Stability analysis Mathematical models Time-varying systems

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Research on Fine Modeling of Dispersion Fuel Plate Based on Lattice Method

SSRN

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SSRN 2023年

作者： Chen, Yuqing Liu, Pengfei Li, Song Lou, Lei Li, Ang College of Nuclear Science and Technology Naval University of Engineering Wuhan China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China

For Double Heterogeneous(DH) systems, the analysis shows that the lattice modeling method has a great advantage in efficiency compared to the stochastic explicit modeling method, but the Lattice Modeling Method with Single-Particle Universe(LMMSU) has difficulties in calculating the problem of DH system with multiple particle sizes. In this paper, a Lattice Modeling Method with Multiple -Particles Universe(LMMMU) is proposed . The LMMMU has a computational error of less than 30 pcm when dealing with particle-dispersed fuel systems and still less than 50 pcm when dealing with particle-dispersed burnable poison systems. The memory footprint is reduced to 5.21% and the computation time is reduced to 1.25% compared to the stochastic explicit modeling method. The LMMMU also shows good compatibility when dealing with the problem of filling by two types of dispersed particles. Comprehensive analysis shows that the LMMMU is better than LMMSU in terms of applicability, efficiency, and accuracy. © 2023, The Authors. All rights reserved.

关键词： Efficiency

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Development, Validation and Application of Sub-Channel Thermal-Hydraulic Analysis Code for Liquid Metal Cooled Reactor

SSRN

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SSRN 2024年

作者： Wang, Jinshun Chen, Ronghua Liang, Yu Gui, Minyang Zhu, Xinyang Tian, Wenxi Qiu, Suizheng Su, Guanghui School of Nuclear Science and Technology Shaanxi Key Laboratory of Advanced Nuclear Energy and Technology State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong University Xi’an710049 China Nuclear Power Institute of China 328 Changshun Avenue Chengdu610213 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China College of Nuclear Science and Technology Harbin Engineering University Harbin150001 China

The liquid metal reactor, specifically the lead-based fast reactor and the sodium-cooled fast reactor, are generally recognized as the most significant representatives of the Gen IV reactors due to their sustainability, economy, security and reliability. In order to conduct thermal-hydraulic safety analysis for liquid metal cooled fast reactors, adaptive improvements are made to the model and solution algorithms based on the sub-channel analysis method, and a Sub-channel Analysis Code Of Safety for Liquid Metal cooled Reactor (SACOS-LMR) is developed. The validation of SACOS-LMR is conducted using classic experimental data of liquid metal. The results show that the dimensionless temperature deviations of ORNL 19-pin test and Toshiba 37-pin test are within 10%, and the relative temperature deviations of KIT-KALLA 19-pin test are within 25%. These findings confirm the accuracy and reliability of SACOS-LMR in predicting the temperature distribution of liquid metal reactors. Ultimately, calculations conducted on the ALFRED lead-cooled fast reactor demonstrated the practical utility of the code and have certain guiding significance for its subsequent design and development. © 2024, The Authors. All rights reserved.

关键词： Liquid metals

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A Novel Attention-based Explainable Deep Learning Framework Towards Medical Image Classification

A Novel Attention-based Explainable Deep Learning Framework ...

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Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Gladys W. Muoka Ding Yi Chiagoziem Chima Ukwuoma Moindi Duke Martin Ahmet Arif Aydin Mugahed A. Al-Antari School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan Chengdu China Department of Computer Science Unicaf University Lilongwe Lilongwe Malawi Department of Computer Engineering Faculty of Engineering İnönü University Turkey Department of Artificial Intelligence College of Software & Convergence Technology Daeyang AI Center Sejong University Seoul Korea

Deep learning applications for medical image classification have shown remarkable promise, particularly incorporating attention-based neural networks. This is particularly relevant in medical imaging, where the integration of Artificial Intelligence assists with various imaging tasks, including classification, segmentation, and detection. Deep learning is revolutionizing medical research and playing a significant role in advancing personalized clinical treatment. However, the lack of interpretability in these models presents a significant obstacle to their adoption in clinical practice. Therefore, there is a growing need for a comprehensive understanding of artificial intelligence systems and their internal mechanisms, capabilities, and limitations, which is the focus of the field of explainable AI. This study proposes a novel attention-based explainable deep learning framework for medical image classification tasks, including Covid-19, breast cancer (BreakHis), lung cancer (LC2500), and Retinal optical coherence tomography (OCT). The proposed framework recorded overall accuracies of 98% (Covid-19 Radiography), 95% (BreakHis), 99.8% (LC2500), and 95%(OCT). For visual analysis of the outcomes, we employ and use the LIME, SHAP, and ELI-5 to analyze the achieved results. The study’s primary goal is to bridge the gap between the high performance achieved by attention-based models and the necessity for transparency and interpretability in medical image diagnostics.

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Design and Implementation of Controller for IGBT Moudle Performance Test

Design and Implementation of Controller for IGBT Moudle Perf...

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Annual Conference of Industrial Electronics Society

作者： Tianshu Zhao Jiancong Yang Chuan Xie Glasgow College University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering Southwest Jiaotong University Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

The study focuses on the reliability and lifespan of Insulated Gate Bipolar Transistors (IGBTs), which play a vital role in renewable energy power generation systems. To assess the performance of IGBT-based power devices, a power cycle test platform is developed. This platform incorporates a single-phase inverter bridge circuit with Sinusoidal Pulse Width Modulation (SPWM) control technology. By simulating real-world operating conditions across various application scenarios, the platform provides evaluation parameters of IGBTs' thermal characteristics and lifespan, offering data models to analyze their service life. The research covers multiple aspects, including the design of main circuit parameters, current closed-loop control design and hardware circuit test. Additionally, a semi-physical simulation platform is designed to validate the research findings by reproducing working conditions and measuring the junction temperature.

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