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Annual Meeting Industrial and Commercial Power systems Technical Conference

作者： Feiyu Sun Dongsheng Cai Zhenyuan Zhang Qi Huang College of Nuclear Technology and Automation Engineering Chengdu University of Technology China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang P.R. China

ISBN: (数字)9798350345308

ISBN: (纸本)9798350345315

Wind and solar energy inverter-based resources (IBRs) has been employed extensively with the aim of carbon neutrality. Power systems also make extensive use of power electronic converters, leading to interactions between IBRs and with the grid, causing high frequency oscillation (HFO) problems. It damages equipment and jeopardizes the security of the system. To identify HFO components above 100 Hz, this research use Phasor Measurement Unit (PMU) instantaneous value data to determine the HFO associated characteristics. To reduce the influence of spectral leakage and the fence effect, as well as to improve the identification accuracy of the related parameters, this paper adopts the RV self-convolutional window based Discrete Fourier Transform (DFT) and the Hanning double-window based all-phase Fast Fourier Transform (apFFT) hybrid algorithm to identify the HFO modal parameters. We take into account the identification accuracy in complex cases, such as non-nominal frequencies, with noise effects and multiple HFO modes. The simulation results show that the proposed method has high identification bandwidth, accuracy and strong flexibility.

关键词： Accuracy Wind energy Simulation Discrete Fourier transforms Noise Bandwidth Hafnium oxide

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3d Surface Detection and Segmentation from Point Clouds Via Quadric Fits Based on Dbscan Clustering

SSRN

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SSRN 2024年

作者： Xie, Tingting Chen, Hui Liu, Wanquan Zhou, Rongyu Li, Qilin College of Automation Engineering Shanghai University of Electric Power Shanghai200090 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China School of Electrical Engineering Computing and Mathematical Sciences Curtin University BentleyWA Australia

Extracting surfaces from 3D point clouds is significant in reconstructing and transforming these discrete points into their corresponding models. Scannedpoint clouds are often accompanied by noise, and the existing methods mainly rely on local feature similarities for surface extractions. Errors in estimatingthe feature information may lead to incorrect surface detection. In this paper we propose a surface extraction and boundary detection method based onclustering technique. The method can be described in three steps: In the first step, a normal correction is carried out using the information from theneighbourhood of points with sharp features. The second step is to cluster the points that meet the coplanar condition of the local quadric surface (LQS).In the third step, surface merger is performed by merging the local surfaces satisfying the merging conditions. Experimental validation is carried outto determine the effectiveness of the proposed method. The experimental results show improved surface extraction accuracy of the proposed methodin comparison to RANSAC, RG, LCCP, C2NO and HT methods. © 2024, The Authors. All rights reserved.

关键词： Merging

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Variable Frequency Phase-Shift Modulation Technique for Single Stage Dual-Active-Bridge AC-DC Converter

Variable Frequency Phase-Shift Modulation Technique for Sing...

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International Conference on Power Electronics (ICPE)

作者： Dongxin Guo Panbao Wang Chunguang Ren Josep M. Guerrero School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Shanxi Key Lab. of Power System Operation and Control Taiyuan University of Technology Taiyuan China Department of Energy Technology Aalborg University Aalborg Denmark

This article proposes a variable frequency phase-shift modulation technique for single stage dual-active-bridge (DAB) AC-DC converter. This isolated single-stage single-phase converter consists of a DAB and a full bridge (FB) inverter. The proposed strategy applies a composite control strategy combining frequency modulation and extended phase shift (EPS) method to overcome the drawback of the non-linear power control of traditional phase-shift control scheme, which significantly reduces the complexity of the controller algorithm. Moreover, the synchronous inverter control applied to the back-end FB inverter is designed, which can realize the energy conversions in a single-stage, and a high frequency (HF) filter capacitor can replace the electrolytic capacitor at the output side DC-link. Thus, the safety of system operation improves and the power density of the system increases. Finally, simulation results confirm the validity and practical feasibility of the proposed control strategy.

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Improved Res2Net Based on Multi-scale Attention Mechanism for Breast Cancer Image Classification 12th

Improved Res2Net Based on Multi-scale Attention Mechanism fo...

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12th International Conference on Computer engineering and Networks, CENet 2022

作者： Lei, Suqin Deng, Xing Shao, Haijian Xia, Wang Department of Computer Jiangsu University of Science and Technology Jiangsu Zhenjiang212003 China College of Automation Key Laboratory of Ministry of Education of Complex Engineering System Measurement and Control Southeast University Jiangsu Nanjing210009 China School of Information Science and Technology Nantong University Nantong Jiangsu226019 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

ISBN: (纸本)9789811969003

Breast cancer is one of the most common cancers among female diseases. Since the classification accuracy of pathological images is crucial to the diagnosis of breast cancer, in order to reduce the error of manual diagnosis and improve the automatic classification accuracy of pathological images, this paper proposes a high-accuracy breast cancer classification method based on multi-scale attention mechanism enhanced Res2Net. By constructing a multi-channel residual connection in the residual block, and introducing a convolutional attention mechanism to enhance the feature extraction ability of Res2Net, and using group convolution to replace part of the ordinary convolution. In addition, since the channel information interaction across groups cannot be realized in the group convolution, which reduces the feature extraction ability. In this paper, the channel shuffling operation is used to reorganize the feature maps after the group convolution to achieve the information interaction between different groups. The evaluation results on the BreaKHis dataset show that, the accuracy and precision of the method in this paper have reached 98.5% and 98.9% respectively, in binary classification of histopathological images compared with the benchmark method, and the advantages of recall rate and F1 value are also more obvious. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image classification

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Multi-Scale Eca Attention Network: A Rotation Mechanical Domain Adaptation Method with Minimal Class Confusion

SSRN

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SSRN 2023年

作者： Li, Xueyi Yu, Tianyu Wang, Xiangkai Li, Daiyou Xie, Zhijie Kong, Xiangwei College of Mechanical and Electrical Engineering Northeast Forestry University Harbin150040 China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Shenyang110819 China School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China

Unsupervised rotation mechanical fault diagnosis methods have become popular, but existing unsupervised methods still have some issues. For example, it is challenging to capture vibration signal features at different scales and to address partial class confusion. To improve the diagnostic performance, this study introduces a multi-scale, Efficient Channel Attention (ECA) attention mechanism, Joint Adaptation Network (JAN), and Minimum Class Confusion (MCC) for addressing the aforementioned issues. Firstly, the authors design a multi-scale fault feature extraction module to capture discriminative information at different scales in vibration signals. Secondly, the authors introduce the ECA attention mechanism to weight the extracted features at the channel level, enhancing useful features and suppressing redundant features. Then, the authors employ the JAN method to establish local maximum mean discrepancy, enabling adaptation between corresponding sub-domains of the source and target domains, avoiding the problem of being too close. Finally, the authors use MCC as the loss function to reduce prediction confusion between correct and ambiguous categories in target samples, thus improving transfer performance. Experimental results demonstrate that the proposed method exhibits excellent performance in unsupervised rotation mechanical fault diagnosis tasks. © 2023, The Authors. All rights reserved.

关键词： Fault detection

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A Compatibility Evaluation Method for Substation Protection and Monitoring system Based on G1 Method and Expert Investigation 3

A Compatibility Evaluation Method for Substation Protection ...

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3rd International Conference on New Energy and Power engineering, ICNEPE 2023

作者： Xia, Hao Deng, Xiongyao Ma, Shizhong Yan, Yuxiang Xue, Ancheng Liu, Yu Shu, Zhihuai Chang, Naichao Li, Zhongqing Meng, Jiangwen Dou, Xuewei Wang, Shenqiang Wu, Fangying Fan, Chen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source North China Electric Power University Beijing China National Electric Power Dispatching and Control Center of State Grid Corporation of China Beijing China China Electric Power Research Institute Beijing China Beijing Sifang Engineering Co. Ltd Beijing China China Electric Power Research Institute Power Automation Department Nanjing China

ISBN: (纸本)9798350393224

In existing protection and monitoring system of substation(S-PMS), there are compatibility problems between hardware and software or between software-hardware combinations and systems, including differences in communication protocols between different manufacturers and differences in system adaptation. Compatibility issues have become a growing focus area for the power industry. This paper proposes a method to evaluates the compatibility of the protection and monitoring system of substation based on the G1 and expert investigation, for the existing or unbuilt substations. In detail, Firstly, according to the compatibility requirements of the substation protection and monitoring system, corresponding indicators are proposed and a comprehensive compatibility evaluation model is constructed. Secondly, based on the comprehensive evaluation model, the evaluation results of typical stations without domestic chips and optimized stations using domestic chips are compared to verify the feasibility of the proposed method. © 2023 IEEE.

关键词： Compatibility evaluation G1 method Protection and monitoring system

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Adaptive Estimation for Environmental Monitoring Using an Autonomous Underwater Vehicle

Adaptive Estimation for Environmental Monitoring Using an Au...

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IEEE Conference on Decision and control

作者： Ziwen Yang Joana Fonseca Shanying Zhu Cailian Chen Xinping Guan Karl H. Johansson Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Digital Futures

This paper considers the problem of monitoring and adaptively estimating an environmental field, such as temperature or salinity, using an autonomous underwater vehicle (AUV). The AUV moves in the field and persistently measures environmental scalars and its position in its local coordinate frame. The environmental scalars are approximately linearly distributed over the region of interest, and an adaptive estimator is designed to estimate the gradient. By orthogonal decomposition of the velocity of the AUV, a linear time-varying system is equivalently constructed, and the sufficient conditions on the motion of the AUV are established, under which the global exponential stability of the estimation error system is rigorously proved. Furthermore, an estimate of the exponential convergence rate is given, and a reference trajectory that maximizes the estimate of the convergence rate is obtained for the AUV to track. Numerical examples verify the stability and efficiency of the system.

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Performance Analysis of the Modified Flux-Coupling-Type SFCL in VSC-HVDC system

Performance Analysis of the Modified Flux-Coupling-Type SFCL...

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Iranian Conference on electrical engineering (ICEE)

作者： Mohammad Khakroei Ashkan Mirzaei Rajeooni Mahdi Rahimi Pirbasti Hossein Heydari MAPNA Electric & Control Engineering & Manufacturing Company (MECO) Alborz Iran Department of Engineering and R&D MAPNA Generator Engineering and Manufacturing Company (PARS) Alborz Iran Department of Electrical Engineering (Center of Excellence for Power System Automation and Operation) Iran University of Science and Technology (IUST) Tehran Iran

Although Voltage Source Converters based on HVDC (VSC-HVDC) systems have several advantages, they are vulnerable to DC fault currents. Concerning the inherent characteristics of high-temperature superconducting (HTS) material, using HTS in the fault current limiter could be a solution to limit the current in VSC-HVDC. The present paper seeks to provide an elaborately better solution to the problem mentioned above of the fault currents than what has previously been proposed. The object of this research is a modified flux coupling type superconductor fault current limiter (MFC-SFCL) to attenuate the fault current in VSC-HVDC network. The principle mechanism and operation of the SFCL and VSC-HVDC systems are modeled in detail, involving interplay or synergy between electrical and thermal properties. The simulation results demonstrate that the purposed MFC-SFCL has the proper function to mitigate the fault current.

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A Stackelberg Game Approach for Signal Temporal Logic control Synthesis with Uncontrollable Agents

arXiv

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arXiv 2025年

作者： Cui, Bohan Yu, Xinyi Giua, Alessandro Yin, Xiang Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China Thomas Lord Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Electrical and Electronic Engineering University of Cagliari Cagliari09123 Italy

In this paper, we investigate the control synthesis problem for Signal Temporal Logic (STL) specifications in the presence of uncontrollable agents. Existing works mainly address this problem in a robust control setting by assuming the uncontrollable agents are adversarial and accounting for the worst-case scenario. While this approach ensures safety, it can be overly conservative in scenarios where uncontrollable agents have their own objectives that are not entirely opposed to the system’s goals. Motivated by this limitation, we propose a new framework for STL control synthesis within the Stackelberg game setting. Specifically, we assume that the system controller, acting as the leader, first commits to a plan, after which the uncontrollable agents, acting as followers, take a best response based on the committed plan and their own objectives. Our goal is to synthesize a control sequence for the leader such that, for any rational followers producing a best response, the leader’s STL task is guaranteed to be satisfied. We present an effective solution to this problem by transforming it into a single-stage optimization problem and leveraging counterexample guided synthesis techniques. We demonstrate that the proposed approach is sound and identify conditions under which it is optimal. Simulation results are also provided to illustrate the effectiveness of the proposed framework. © 2025, CC BY.

关键词： control system synthesis

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PIGWN: Physics-Informed Graph WaveNet for Airport Flight Traffic Flow Prediction

PIGWN: Physics-Informed Graph WaveNet for Airport Flight Tra...

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Zhichao Yang Yinghao Zhu Ziyue Niu Yanru Huang Chengwei Pan Xiwang Dong School of Artificial Intelligence Beihang University Beijing China China Academy of Launch Vehicle Technology Beijing China School of Artificial Intelligence Institute of Unmanned System School of Automation Science and Electrical Engineering Beijing China Science and Technology on Aircraft Control Laboratory Beihang University Beijing China

ISBN: (数字)9798350356618

ISBN: (纸本)9798350356625

The continuous growth of global travel demand leads to the continuous rise of airport flight flow, leading a rising need to accurately predict the airport flight traffic flow. Current research predominantly employs Graph Convolutional Neural Networks (GCN) to model intra-airport traffic changes, but overlooks comprehensive modeling of air traffic routes and temporal dimensions. Furthermore, existing models rely on data-driven approaches lacking a deep understanding of traffic change mechanisms, resulting in poor performance in new scenarios. To solve these problems, we propose a deep learning network framework Physics-Informed Graph WaveNet (PIGWN) based on multi-scale feature data fusion and constructs two new airport domain data sets. We integrated a physics-based module prior to GraphWaveNet to learn and integrate multi-scale spatio-temporal information of airports, embedding physical formulas reflecting airport traffic changes. The physics learning module fuses multi-scale spatio-temporal feature data considering the time delay and traffic conservation relationship between different airports. The Graph WaveNet (GWN) structure learns and predicts multi-scale spatio-temporal feature data, and uses the time-space convolution block model to capture and model spatio-temporal features. PIGWN model has certain theoretical significance and practical application value in the field of airport flight flow prediction, which realizes the accurate prediction of airport flight flow and provides certain decision support and reference for air traffic management. We have made the code publicly available at https://***/yzc0912/PIGWN.

关键词： Deep learning Measurement Adaptation models Atmospheric modeling Data integration Predictive models Airports Graph neural networks Data models Physics

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