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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Zhang, Qingtao Gao, Diju Zhang, Dan Cai, Haiqing Gu, Haohan Chen, Wei Wu, Wencong Chen, Zhihao Institute of Logistics Engineering Shanghai Maritime University Shanghai China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9789819608966

With the further development of "double high" characteristics of power system, the traditional stability problem dominated by synchronous generator has gradually evolved into a new stability problem dominated by power electronic equipment control. In addition, different types of failure problems can occur in wind power systems. In order to achieve multi-objective coordinated and stable operation of high proportion wind power system, a damping control method with parameters tuning is proposed, which includes the design of filtering link and proportional amplification link. Among them, the key parameters of the proportional link are adjusted. Finally, the feasibility of the proposed control method is verified by simulation tests. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electric power system stability

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Research on Wind Turbine Control Hardware in Loop Real-time Simulation and its Application

Research on Wind Turbine Control Hardware in Loop Real-time ...

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2023 IEEE Sustainable Power and Energy Conference, iSPEC 2023

作者： Zeng, Guanming Tu, Liang Zhu, Yihua Li, Chengxiang Liu, Mingqun He, Peng State Key Laboratory of HVDC and CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&D Centre Guangdong Provincial Key Laboratory of Intelligent Operation Control for New Energy Power System Guangdong Guangzhou China Yunnan Power Grid Co. Ltd. Electric Power Research Institute Yunnan Kunming China

ISBN: (纸本)9798350322699

With the construction of new power system, high-capacity renewable energy sources including wind power are integrated into the power system, whose transient response characteristics have a significant impact on the safe and stable operation of both renewable energy sources and power system. Real-time simulation has become an effective method to study interaction between high-capacity renewable energy sources and power system because of its high accuracy and reliability, and precise wind turbine real-time simulation model is of great significance in research mentioned above. Therefore, the wind turbine control hardware in loop (CHIL) real-time simulation method is proposed in the paper, whose feasibility and accuracy are also verified by comparing simulation data from CHIL platform and on-site testing data. It's further used in the analysis of large-scale offshore wind farm cluster and connected power system as a practical reference case. © 2023 IEEE.

关键词： control hardware in loop power system analysis real-time simulation wind turbine

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Fault diagnosis for small samples based on VMR

Fault diagnosis for small samples based on VMR

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2024 China Automation Congress, CAC 2024

作者： Wu, Xuejin Wu, Yali Hu, Yanghu Department of Information and Control Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratoiy of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd Xi'an710016 China

ISBN: (纸本)9798350368604

The scarcity of fault samples presents a significant challenge for fault diagnosis in industrial processes. Conventional methods often fail to deliver satisfactory results when dealing with small sample sizes. In addressing the issue of small sample fault diagnosis in industrial processes, this paper utilizes the Variational Mode Reconstruction(VMR) algorithm to screen the best components decomposed by the Variational Mode Decomposition(VMD) through the envelope entropy then random weighting them and signal reconstruction to achieve data enhancement, to enrich the sample size and to prevent the model overfitting phenomenon due to the scarcity of samples. Meanwhile, this paper integrates Convolutional Neural Network (CNN) and Long Short-term Memory Neural Network (LSTM) to propose a network model of spatio-temporal feature fusion for feature extraction and classification. The experiments demonstrate that this model not only enhances data diversity but also ensures consistency before and after enhancement, effectively mitigating overfitting. Furthermore, it guarantees high recognition and generalization rates in fault diagnosis. © 2024 IEEE.

关键词： Convolutional neural networks

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Linear Modulation of the Resonant Frequency of a Double-bubble Model Below an Air-Water Interface

Linear Modulation of the Resonant Frequency of a Double-bubb...

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IEEE/OES China Ocean Acoustics (COA)

作者： Xuan Cheng Shiyu Li Zhixiong Gong Jun Fan School of Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China State Key Laboratory of Ocean Engineering Key Laboratory of Marine Intelligent Equipment and System School of Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China State Key Laboratory of Ocean Engineering School of Ocean and Civil Engineering Key Laboratory of Marine Intelligent Equipment and System Shanghai China

ISBN: (数字)9798350340297

ISBN: (纸本)9798350340303

The study of sound wave propagation across the air-water interface is important for several potential applications, e.g., acoustic communication between underwater environments and air. However, only 0.1% of the power of the incident wave perpendicular to the interface can cross the interface owing to the large acoustic-impedance mismatch between air and water. This renders the propagation of acoustic energy between the media inefficient, leading to the failure of effective acoustic communication between these media. This situation could be solved using designed bubble systems because bubbles are good acoustic impedance matchers. The existing research is mainly limited periodic single-bubble systems, which are not suitable for acoustic propagation in the broadband frequency range. This is because the large sound transmission coefficient between the air-water interface occurs only near a sharp resonant frequency and decreases rapidly away from the resonance. In this work, we propose a periodic double-bubble model below the air-water interface for efficient propagation over a wide frequency range. A numerical simulation model based on COMSOL was developed and validated through comparison with a theoretically analyzed periodic single-bubble system. Then, a periodic double- bubble model was built to study the modulation effect of the resonance frequency versus the vertical interval between the two bubbles. Numerical simulations show that the resonant frequency of the periodic double-bubble system varies linearly with the vertical interval. Therefore this study offers a potential method for designing broadband acoustic communication techniques across the sea-air interface.

关键词： Frequency modulation Acoustic communication (telecommunication) Atmospheric modeling Resonant frequency Media Numerical simulation Resonance Numerical models Broadband communication Impedance

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Testing the Limits: Unusual Text Inputs Generation for Mobile App Crash Detection with Large Language Model 24

Testing the Limits: Unusual Text Inputs Generation for Mobil...

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44th ACM/IEEE International Conference on Software Engineering, ICSE 2024

作者： Liu, Zhe Chen, Chunyang Wang, Junjie Chen, Mengzhuo Wu, Boyu Tian, Zhilin Huang, Yuekai Hu, Jun Wang, Qing State Key Laboratory of Intelligent Game Beijing China Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Technical University of Munich Munich Germany DiDi Global Inc The Pennsylvania State University Work Done during the Internship at Iscas United States Science & Technology on Integrated Information System Laboratory China

ISBN: (纸本)9798400702174

Mobile applications have become a ubiquitous part of our daily life, providing users with access to various services and utilities. Text input, as an important interaction channel between users and applications, plays an important role in core functionality such as search queries, authentication, messaging, etc. However, certain special text (e.g., -18 for Font Size) can cause the app to crash, and generating diversified unusual inputs for fully testing the app is highly demanded. Nevertheless, this is also challenging due to the combination of explosion dilemma, high context sensitivity, and complex constraint relations. This paper proposes InputBlaster which leverages the LLM to automatically generate unusual text inputs for mobile app crash detection. It formulates the unusual inputs generation problem as a task of producing a set of test generators, each of which can yield a batch of unusual text inputs under the same mutation rule. In detail, InputBlaster leverages LLM to produce the test generators together with the mutation rules serving as the reasoning chain, and utilizes the in-context learning schema to demonstrate the LLM with examples for boosting the performance. InputBlaster is evaluated on 36 text input widgets with cash bugs involving 31 popular Android apps, and results show that it achieves 78% bug detection rate, with 136% higher than the best baseline. Besides, we integrate it with the automated GUI testing tool and detect 37 unseen crashes in real-world apps. © 2024 ACM.

关键词： Android (operating system)

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STDHL: Spatio-Temporal Dynamic Hypergraph Learning for Wind Power Forecasting

arXiv

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arXiv 2024年

作者： Dong, Xiaochong Zhang, Xuemin Yang, Ming Mei, Shengwei State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan250061 China

Leveraging spatio-temporal correlations among wind farms can significantly enhance the accuracy of ultra-short-term wind power forecasting. However, the complex and dynamic nature of these correlations presents significant modeling challenges. To address this, we propose a spatio-temporal dynamic hypergraph learning (STDHL) model. This model uses a hypergraph structure to represent spatial features among wind farms. Unlike traditional graph structures, which only capture pair-wise node features, hypergraphs create hyperedges connecting multiple nodes, enabling the representation and transmission of higher-order spatial features. The STDHL model incorporates a novel dynamic hypergraph convolutional layer to model dynamic spatial correlations and a grouped temporal convolutional layer for channel-independent temporal modeling. The model uses spatio-temporal encoders to extract features from multi-source covariates, which are mapped to quantile results through a forecast decoder. Experimental results using the GEFCom dataset show that the STDHL model outperforms existing state-of-the-art methods. Furthermore, an in-depth analysis highlights the critical role of spatio-temporal covariates in improving ultra-short-term forecasting accuracy. Copyright © 2024, The Authors. All rights reserved.

关键词： Wind forecasting

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Distributed Real-time state Estimation for Combined Heat and Power systems

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Journal of Modern Power systems and Clean Energy 2021年第2期9卷 316-327页

作者： Tingting Zhang Wen Zhang Qi Zhao Yaxin Du Jian Chen Junbo Zhao the Key Laboratory of Power System Intelligent Dispatch and Control Ministry of EducationShandong UniversityJinan 250061China the Department of Electrical and Computer Engineering Mississippi State UniversityStarkvilleMS 39762USA

This paper proposes a distributed real-time state estimation(RTSE)method for the combined heat and power systems(CHPSs).First,a difference-based model for the heat system is established considering the dynamics of heat *** heat system model is further used along with the power system steady-state model for holistic CHPS state estimation.A cubature Kalman filter(CKF)-based RTSE is developed to deal with the system nonlinearity while integrating both the historical and present measurement ***,a multi-timescale asynchronous distributed computation scheme is designed to enhance the scalability of the proposed method for largescale *** distributed implementation requires only a small amount of information exchange and thus protects the privacy of different energy *** carried out on two CHPSs show that the proposed method can significantly improve the estimation efficiency of CHPS without loss of accuracy compared with other existing models and methods.

关键词： Combined heat and power system(CHPS) cubature Kalman filter(CKF) heat dynamics multi-time-scale asynchronous distributed scheme real-time state estimation(RTSE)

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Resonance frequency prediction approach of lattice structure fabricated by selective laser melting

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Advances in Astronautics Science and Technology 2022年第4期5卷 309-316页

作者： Zhou, Hao Jia, Heran Zeng, Huizhong Tu, Yonggang Li, Linli Zhang, Xiaoyu Lei, Hongshuai Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering China Academy of Space Technology No. 104 Youyi Road Beijing 100094 China Beijing Key Laboratory of Lightweight Multi-Functional Composite Materials and Structures Beijing Institute of Technology No. 5 Zhongguancun South Street Beijing 100081 China

Lightweight structures composed of a closed shell and internal lattice infill are highly desirable in satellites on account of their superior specific stiffness and buckling strength, which are brought about by the sandwich effect. These lattice structures can be fabricated by various additive manufacturing techniques, such as selective laser melting (SLM). However, the sub-millimeter-scale shell thickness and lattice strut diameter of the fabricated structure often deviate from the designed dimensions and lead to noteworthy discrepancies between the resonance frequencies of the fabricated structure and those of the initial design model. In this work, a bracket structure for a satellite is designed via topology optimization-based lattice infill approach and fabricated using SLM. A resonance frequency prediction approach based on X-ray micro-computed tomography and the stiffness equivalence is then proposed. Vibration tests are conducted to obtain the resonance frequencies of the fabricated structure. The prediction errors of resonance frequencies for the first three modes are less than 1%, whereas that of the traditional approach based on finite element analysis is as large as 14%. © 2022, Chinese Society of Astronautics.

关键词： Additive manufacturing Geometric reconstruction Lattice structure Prediction approach Resonance frequency

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An Approach for Predicting and Compensating the End Deformation of a Heavy Load Robot for Friction Stir Welding 16th

An Approach for Predicting and Compensating the End Deformat...

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16th International Federation of Theory of Machines and Mechanisms World Congress, IFToMM WC 2023

作者： Bai, Yujie Liu, Haitao Meng, Shaofei Ma, Yue Yue, Wei Li, Guangxi Xiao, Juliang Wang, Guofeng Ding, Yabin Key Laboratory of Mechanism Theory and Equipment Design of State Ministry of Education Tianjin University Tianjin300072 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Dongguan University of Technology Dongguan523808 China

ISBN: (纸本)9783031457043

Aiming at solving the problem of insufficient plunge depth by the deformation of friction stir welding robots, this paper presents a method for predicting and compensating for the end deformation of friction stir welding robots. Firstly, the numerical model of FSW is established using DEFORM-3D software, then the axial force on the welding tool is obtained. Subsequently, the robot stiffness model is established based on the screw theory to realize the prediction of robot deformation in the workspace. Finally, a deformation compensation method based on the mirror principle is proposed to realize the compensation of the welding trajectory. Taking the 10 mm AA6061 aluminium alloy FSW as an example, the compensation method proposed in this paper is verified by using computer simulation. The results show that the stiffness model established in this paper can accurately predict the end deformation of the robot. The maximum plunge depth deviation of the compensation method proposed in this paper is reduced by 95.17% compared with the uncompensated case, which proves the effectiveness of the proposed compensation method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Friction stir welding

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Automatic microinjection of batch zebrafish larvae based on precise positioning of the yolk

Automatic microinjection of batch zebrafish larvae based on ...

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IEEE International Conference on robotics and Biomimetics

作者： Peiyao Zhang Can Wang Yaowei Liu Xin Zhao Mingzhu Sun Institute of Robotics and Automatic Information System (IRAIS) The Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Yolk microinjection of zebrafish larvae is widely used in various biological experiments. In this study, we introduce a visual detection method based on deep learning to the micromanipulation of zebrafish larvae and propose a microinjection method for zebrafish larvae based on the precise positioning of the yolk. The YOLO visual detection algorithm is used to distinguish different zebrafish body parts so that the yolk part of zebrafish larvae could be automatically moved to the center of the microscopic FOV to complete the automatic injection. Experimental results show that the success rate of visual detection is 95.54%, which meets the needs of subsequent experiments to distinguish the categories of zebrafish body parts. Further, the online injection experiments verify the effectiveness of this method.

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