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6th PURPLE MOUNTAIN FORUM on Smart Grid Protection and control, PMF2021

作者： Wang, Hui Lv, Shuaishuai Ji, Xiu Meng, Xiangping Wang, Chunsong College of Electrical and Information Engineering Changchun Institute of Technology Changchun China National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control with Safety Operation Technology Changchun China

ISBN: (纸本)9789811671555

In view of the large fluctuations in the output of photovoltaic microgrids, large energy storage capacity is required to solve the problem of stabilizing the load. In order to reduce energy storage investment costs, considering the energy storage characteristics of V2G, the range of decision variables, the constraints of power balance requirements and energy exchange strategies are given. Through the establishment of a coordinated scheduling model of battery and V2G in the photovoltaic microgrid with the dual goals of economy and grid-connected load fluctuation rate. There are four load modes of electric vehicles, namely none, disordered, transferring and V2G respectively. After realizing the optimal scheduling by using particle swarm optimization algorithm, the economic and safety benefits of power grid, micro-grid dispatching center and electric vehicle users are compared in the sub-mode. Finally, according to the analysis of the calculation examples, the two-level load curve and the economic income table under the four modes are solved. The comparative analysis shows that the introduction of V2G can replace some capacity batteries, so that the photovoltaic microgrid can be further optimized in terms of load peaks and valleys, tripartite economy and safety. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Vehicle-to-grid

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Research Progress of Bionic Water Strider Robot

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Recent Patents on Mechanical engineering 2022年第2期15卷 122-148页

作者： Jiang, Jingang Tan, Qiyun Yu, Xiaoyang Wu, Dianhao Yao, Liang Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin150080 China Intelligent Machine Institute Harbin University of Science and Technology Harbin150080 China School of Measurement-Control Tech and Communications Engineering Harbin University of Science and Technology Harbin150080 China

Background: The bionic water strider robot can achieve sliding, jumping, and other movements on the water surface, having advantages of small size, light weight, flexible movements, and other characteristics. It can detect the quality of water, investigate and search the water surface, and perform some other operations. It has a very broad range of applications and development prospects. Therefore, the trend of biomimetic water strider robots is attracting more and more attention. Objective: This study aimed to review the bionic water strider robot and introduce its classification, characteristics, and development. Methods: This paper reviews various productions and patents related to the bionic water strider robot from 2003 to the present. The sources of the papers include CNKI, Wanfang, Patent publication an-nouncement in China, Web of Science, IEEE, Elsevier, Springer-Verlag, Espacenet, and FPO IP Research & Communities. To obtain the results, an endnote was used for documentation, and citeSapce was used for visual analysis. Results: The mechanical structure of existing bionic water strider robots has been analyzed and com-pared. Furthermore, the typical characteristics are concluded. The main problems in its development are analyzed, and the development trend is foreseen. Furthermore, the current and future research prospects of the productions and patents on the bionic water strider robot are discussed. Conclusion: The optimization and development of the structure of the bionic water strider robot and the development of associated components help to improve the simulation of the water strider's motion and perform a better task in a complex water surface environment. In the future, with the improvement in the research, the bionic water strider robot will develop into miniaturization, intelligence, and integration. © 2022 Bentham Science Publishers.

关键词： Bionics

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Hyperspectral Image Classification Method Based On Node Similarity Feature Fusion

Hyperspectral Image Classification Method Based On Node Simi...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jiameng Wang Qingyan Wang Junping Zhang Yujing Wang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

There is abundant spectral and spatial information in Hyperspectral images (HSI). However, there exists a limitation of not using spatial information sufficiently in HSI classification. Besides, there is the limitation of mononuclear in feature extraction, resulting in insufficient feature extraction and insufficient utilization of data information. In view of these problems, a node similarity semi-supervised classification method of multiscale feature is proposed to break the limitation of mononuclear and achieve full extraction of spatial information. First, to extract pixel-level features, a three-dimensional (3-D) multiscale convolutional neural network (CNN) is used. Second, based on node similarity superpixel graph U-Net (NSGUNet) is proposed to extract superpixel-level features. Finally, the above two features are weighted fusing, the fused features are classified by sparse graph regularization. Experiments on three datasets illustrate that the proposed method is effective.

关键词： Accuracy Geoscience and remote sensing Feature extraction Convolutional neural networks Data mining Hyperspectral imaging Image classification

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Hyperspectral Image Change Detection Based on Simam Multi-Scale Joint Features

Hyperspectral Image Change Detection Based on Simam Multi-Sc...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xinling Li Qingyan Wang Junping Zhang Yujing Wang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

The remote sensing satellite system has steadily developed, and the availability of massive high-quality satellite remote sensing data has rapidly improved. The dynamic monitoring of land cover changes using hyperspectral data has received great attention. The existing change detection methods usually use the spatial correlation or spatial-spectral correlation of hyperspectral images, lacking an overall consideration of the three-dimensional temporal-spatial-spectral joint features, resulting in suboptimal change detection results. Given the considerations above, this paper proposes a SimAM multi-scale joint feature extraction network for hyperspectral image change detection. The proposed method first adopts SimAM multi-scale joint features network to consider the hyperspectral image as a whole, and extracts multi-scale temporal-spatial-spectral joint features from the network. Then, uses multi-scale feature weighted fusion module to weight different scale features after simple fusion, highlighting the change regions. Finally, adopts the batch-balance measurement module to measure the similarity of the bi-temporal fusion features and output the change detection result map. Experiments show that on two public datasets, the proposed method can achieve a good change detection effect.

关键词： Satellites Correlation Fuses Land surface Euclidean distance Feature extraction Monitoring

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Cross-Domain Few-Shot Learning With Spectral-Spatial Split-Attention For Hyperspectral Image Classification

Cross-Domain Few-Shot Learning With Spectral-Spatial Split-A...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Peng Luo Qingyan Wang Junping Zhang Shouqiang Kang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Hyperspectral image classification (HSIC) is a pivotal technology in hyperspectral remote sensing, playing a widespread role in remote sensing applications. However, the limited number of labeled samples has always made hyperspectral image classification difficult. In response to this issue, researchers have delved into cross-domain classification studies. Moreover, significant progress on cross-domain HSIC has been made in recent years. Nevertheless, existing methods exhibit shortcomings, including inadequate exploitation of spectral and spatial information and a slow training speed, rendering them unsuitable for downstream application tasks. To address these challenges, this paper introduces a model of cross-domain few-shot learning with spectral-spatial split attention(S 3 A-CFSL). Channel attention and split attention are presented to emphasize effective spectral and spatial information for HSIC adaptively. Additionally, the ResNet variant, called ResNeSt, is employed to expedite the training speed of the model. Experimental results demonstrate notable enhancements in the proposed method's classification accuracy and model training speed across two public datasets.

关键词： Training Adaptation models Accuracy Feature extraction Rendering (computer graphics) Data mining Few shot learning

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Joint Classification Of Hyperspectral And LiDAR Data Based On Heterogeneous Attention Feature Fusion Network

Joint Classification Of Hyperspectral And LiDAR Data Based O...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Zhaoyang Wang Qingyan Wang Junping Zhang Xintao Liang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

The fusion of hyperspectral image (HSI) and LiDAR data for classification has gained widespread attention. However, the current fusion methods still have limitations on the use of heterogeneous data information and the interaction of heterogeneous data features. Therefore, we propose a classification method based on heterogeneous attention feature fusion network (HAFF-Net). Firstly, The convolutional neural network is employed to capture local spatial features from multi-scale inputs of heterogeneous data. Secondly, the heterogeneous feature attention module is designed to deeply fuse the extracted local spatial features and promote the interaction of heterogeneous data. Next, a transformer encoder is utilized to extract global spectral features. Finally, the two extracted features are classified by decision fusion using different classifiers. The proposed approach exhibits effectiveness through experimental results on two datasets.

关键词： Laser radar Fuses Convolution Soft sensors Geoscience and remote sensing Feature extraction Transformers

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Research on Grid Connection control Strategy of Building Energy Router Based on Pre Synchronous VSG control technology 1

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8th Purple Mountain Forum on Smart Grid Protection and control, PMF 2023

作者： Guan, Baojin Wang, Hui Zhang, Xiaohua Yin, Pan Meng, Xiangping Safe Operation of Smart Distribution Network of the Measurement and Control Joint Engineering Research Center Changchun Institute of Technology Changchun Jilin130012 China State Grid Jilin Electric Power Co. Ltd. Yanbian Power Supply Company Jilin Yanji130012 China Jilin Institute of Chemical Technology Jinlin Jilin130012 China

ISBN: (数字)9789819992515

ISBN: (纸本)9789819992508

Aiming at the problem of unstable DC bus connection in building energy routers, this paper proposes a grid connection control strategy for building energy routers based on pre-synchronous virtual synchronous generator (VSG) control technology. Firstly, an energy router topology is designed, and secondly, the pre-synchronous VSG is analyzed. Pre-synchronous VSG control is adopted for the DC bus connection in the energy router to maintain the stability of the system and reduce the voltage and current impact of the common coupling point. In this paper, the simulation model of pre-synchronous VSG control energy router connected to the grid is established by MATLAB/simulink. In MATLAB, simulation results show that the pre-synchronous virtual synchronous machine (VSG) control has the characteristics of small overshoot. The proposed control strategy proposes a new solution for the grid-connected operation of energy routers. © 2024, State Grid Electric Power.

关键词： MATLAB

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Research on Fault Diagnosis Method and Application of Gas Turbine Based on Acoustic Imaging technology

Research on Fault Diagnosis Method and Application of Gas Tu...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Yan, Wen Hu, Mingliang Wen, Fei Guo, Peipei Guo, Ziang AVIC Shanghai Aviation Measurement & Control Technology Research Institute Shanghai201601 China Xi'an Aeronautics Computing Technique Research Institute AVIC Xi'an710068 China Department of Electronics College of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Aviation Technology for Fault Diagnosis and Health Management Technology Shanghai201601 China

Gas turbine health management is of great significant for enhancing flight safety and reducing maintenance costs. Based on the architecture of gas turbine fault identification system, a multi-arm spiral microphone array with high positioning accuracy, high beam resolution, and strong anti-interference capability is designed in this paper with simulation and experiment. On this basis, by utilizing multi-channel acoustic digital acquisition and analysis equipment, high-precision, wide dynamic range, and high-real-time acquisition of audio data from the combustion chamber of gas turbines are achieved. An audio data analysis strategy based on feature extraction and an autoencoder network construction strategy are proposed, fulfilling the imaging of audio data from the combustion chamber of gas turbines, which can effectively identify gas turbine faults. Experiments conducted on the platform of the multi-arm spiral microphone array indecates that the proposed fault detection strategy has an accuracy rate of over 98%. This is of great theoretical significance and practical value for enhancing the level of gas turbine fault detection, and improving the performance, reliability, and lifespan of gas turbine systems. © The Institution of engineering & technology 2024.

关键词： Combustion chambers

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Rydberg-Atom Terahertz Heterodyne Receiver with Ultrahigh Spectral Resolution

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Chinese Physics Letters 2024年第8期41卷 17-21页

作者： Zhenyue She Xiaojie Zhu Yayi Lin Xianzhe Li Xiaolin Yang Yanfei Shang Yuqin Teng Haitao Tu Kaiyu Liao Caixia Zhang Xiaohong Liu Jiehua Chen Wei Huang Key Laboratory of Atomic and Subatomic Structure and Quantum Control(Ministry of Education) School of PhysicsSouth China Normal UniversityGuangzhou 510006China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials South China Normal UniversityGuangzhou 510006China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Frontier Research Institute for PhysicsSouth China Normal UniversityGuangzhou 510006China GPETR Center for Quantum Precision Measurement South China Normal UniversityGuangzhou 510006China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430071China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Atomic Frequency Standards Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430071China Wuhan Institute of Quantum Technology Wuhan 430206China

Terahertz heterodyne receivers with high sensitivity and spectral resolution are crucial for various ***,we present a room-temperature atomic terahertz heterodyne receiver that achieves ultrahigh sensitivity and frequency *** a signal frequency of 338.7 GHz,we obtain a sensitivity of 2.88±0.09V·cm^(−1)·Hz^(−1/2) for electric field *** calibrated linear dynamical range spans approximately 89 dB,ranging from−110 dBV/cm to−21 dBV/*** demodulate a 400 symbol stream encoded in 4-state phase-shift keying,demonstrating excellent phase detection *** scanning the frequency of the local oscillator,we realize a terahertz spectrometer with Hz level frequency *** resolution is more than two orders of magnitude higher than that of existing terahertz *** demonstrated terahertz heterodyne receiver holds promising potential for working across the entire terahertz spectrum,significantly advancing its practical applications.

关键词： magnitude holds resolution

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Optimal Allocation Strategy of Electro-Hydrogen Hybrid Energy Storage Capacity Based on Empirical Mode 1

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8th Purple Mountain Forum on Smart Grid Protection and control, PMF 2023

作者： Shanggao, Gong Chenglin, Wang Hui, Xu Hui, Wang Jiajun, Zhang Xiu, Ji Changchun Institute of Technology Changchun130012 China Innovation Department of Jilin Electric Power Co. Ltd Changchun130012 China National and Local Joint Engineering Research Center for Measurement Control and Safe Operation of Intelligent Distribution Networks Changchun130012 China

ISBN: (数字)9789819992515

ISBN: (纸本)9789819992508

With the continuous increase of the proportion of wind power access, the energy coordination capacity in the power system is weakened and the power quality is reduced. Based on this, this paper proposes a method to solve the problem of flattening energy fluctuations in the synergistic power system of electro-hydrogen hybrid energy storage, and uses the hybrid energy storage capacity optimization method composed of supercapacitor and PEM electrolyzer to solve the problem of optimal allocation of wind power fluctuations in grid-connected. Firstly, the structure model of hybrid energy storage system with supercapacitor is proposed, and on this basis, the original signal of wind power is decomposed by empirical mode method to obtain the low-frequency component directly connected to the grid and the high-frequency component that needs to be flattened by hybrid energy storage. Then, the high-frequency fluctuation of wind power in grid-connected is solved by optimizing the hybrid energy storage capacity with supercapacitors. Finally, based on the actual wind power data in Northeast China in 2022 as an example, combined with the example analysis in the MATLAB2018B + Gurobi solution environment, the effectiveness of the flattening strategy is verified by the example analysis, which provides an effective scheme for the flattening of wind power fluctuations, which can effectively improve the system economy. © 2024, State Grid Electric Power.

关键词： Wind power

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