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SSRN 2024年

作者： Zhao, Bin Zhang, Yu Yang, Dongpeng Yang, Songzhou Zhang, Jian Sun, Gaofei Yao, Meng Ren, Taiyang Junjie, Yang Meng, XiangKai Zhang, Guoyu School of Optoelectronic Engineering Changchun University of Science and Technology Changchun130022 China State Key Laboratory of High Power Semiconductor Laser of Changchun University of Science and Technology Jilin Changchun130022 China Institute of Aerospace Ground Simulation Test and Testing Technology Changchun University of Science and Technology Changchun130022 China Optical Measurement and Control Instrumentation Jilin Province Engineering Research Center Changchun130022 China Key Laboratory of Opto-electronic Measurement and Optical Information Transmission Technology Ministry of Education Department of Instrumentation Science and Technology Changchun University of Science and Technology Changchun130022 China School of Life Science and Technology Changchun University of Science and Technology Changchun130022 China

In this study, a playback method for dynamic star map simulation fusing cosmic background radiation information was proposed to improve the playback speed of star maps. The image distortion effect before and after the fusion of star maps and cosmic background radiation was evaluated using peak signal-to-noise ratios. The performance of the proposed and the global catalog traversal generation algorithms without cosmic background radiation simulation capability, as well as the indicators, were experimentally compared. The results showed that the average refresh rates of the view cone filtering star map fast-generation algorithm and the fusion playback algorithm of the star map and cosmic background radiation were 74.2 and 73.7 Hz, respectively. Compared with the entire catalog traversal generation algorithm, the instantaneous stability of the single-frame star map was improved by 3.045 and 3.305 times, respectively, and the consumed time consistency was improved by 4.646 and 5.068 times, respectively. © 2024, The Authors. All rights reserved.

关键词： Image fusion

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Enhancement of localization accuracy based on research of conversion coefficient in coherent Φ-OTDR

TechRxiv

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TechRxiv 2023年

作者： Zhong, Zhen Zou, Ningmu Zhang, Xuping You, Chen Li, Meng Department of Measurement-Control Technology Changzhou Institute of Technology Changzhou213032 China Key Laboratory of Intelligent Optical Sensing and Manipulation Ministry of Education Nanjing University Nanjing210093 China Ingram School of Engineering Texas State University San MarcosTX78666 United States

Recently, a distributed fiber optic sensor named phase optical time domain reflectometer or phase-sensitive optical time domain reflectometer (ɸ-OTDR) has been used in the localization and monitoring of earthquake waves, underwater facilities, etc. Precision in the localization of external perturbations on the fiber is crucial for effective problem resolution. The conversion coefficient between the extracted phase signal detected by ɸ-OTDR and the corresponding perturbation signal acting on the fiber significantly impacts localization accuracy. Therefore, the characteristic of parameters relative to the conversion coefficient in ɸ- OTDR should be deeply researched. Then, based on the established mathematical model of coherent ɸ-OTDR, modulus, statistical phase, phase change, and peak difference of coherent ɸ-OTDR with and without the static region is analyzed, respectively. The analysis reveals that when coherent φ-OTDR has perturbations homogeneously distributed along the fiber, there is no static region on the phase change-fiber length plane. At this point, although the waveform like the information of external perturbation still can be found in the retrieved phase change in the direction of pulse sequence, the phase change does not have a strictly linear relationship along the fiber. It is different from what was expected in coherent ɸ-OTDR having the static region, which means that coherent ɸ-OTDR must have the static region if a higher localization accuracy is needed. A localization case demonstrates that the proposed method with the designed static region enhances localization resolution by 210% compared to the traditional coherent φ-OTDR without the static region. These findings underscore the importance of the conversion coefficient and the relevance of the static region in ɸ-OTDR for achieving accurate and effective localization. © 2023, CC BY.

关键词： Fibers

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Deep Reinforcement Learning Microgrid Optimization Strategy Considering Priority Flexible Demand Side

arXiv

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arXiv 2022年

作者： Sang, Jinsong Sun, Hongbin Kou, Lei Changchun Institute of Technology School of Electrical Engineering Changchun130012 China National and Local Joint Engineering Research Center for Smart Distribution Network Measurement Control and Safe Operation Technology Changchun130012 China Qingdao266075 China

As an efficient way to integrate multiple distributed energy resources (DERs) and the user side, a microgrid is mainly faced with the problems of small-scale volatility, uncertainty, intermittency and demand-side uncertainty of DERs. The traditional microgrid has a single form and cannot meet the flexible energy dispatch between the complex demand side and the microgrid. In response to this problem, the overall environment of wind power, thermostatically controlled loads (TCLs), energy storage systems (ESSs), price-responsive loads and the main grid is proposed. Secondly, the centralized control of the microgrid operation is convenient for the control of the reactive power and voltage of the distributed power supply and the adjustment of the grid frequency. However, there is a problem in that the flexible loads aggregate and generate peaks during the electricity price valley. The existing research takes into account the power constraints of the microgrid and fails to ensure a sufficient supply of electric energy for a single flexible load. This paper considers the response priority of each unit component of TCLs and ESSs on the basis of the overall environment operation of the microgrid so as to ensure the power supply of the flexible load of the microgrid and save the power input cost to the greatest extent. Finally, the simulation optimization of the environment can be expressed as a Markov decision process (MDP) process. It combines two stages of offline and online operations in the training process. The addition of multiple threads with the lack of historical data learning leads to low learning efficiency. The asynchronous advantage actor-critic (Memory A3C, M-A3C) with the experience replay pool memory library is added to solve the data correlation and nonstatic distribution problems during training. The multithreaded working feature of M-A3C can efficiently learn the resource priority allocation on the demand side of the microgrid and improve the flexible sche

关键词： Reinforcement learning

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An Obstacle Avoidance Path Planning Algorithm for Manipulator in Deep Crate Grasping

An Obstacle Avoidance Path Planning Algorithm for Manipulato...

引用

Chinese Automation Congress (CAC)

作者： Zhuobin Yao Yahui Gan Zao Han Huan Gao Ang Li Key Laboratory of Measurement and Control of Systems of Engineering Ministry of Education School of Automation Southeast University NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

The deep crate grasping problem is a major challenge for manipulator in industrial applications. In order to solve the issue of deep crate grasping and ensure the path quality of the algorithm, this paper proposes a new hybrid obstacle avoidance planning algorithm based on goal-biased rapidly exploring random tree and improved artificial potential field (RRT-APF). Initially, the algorithm strategizes an efficient trajectory for the working element within the operational area. Subsequently, it dissects this trajectory through sampling, creating a sequence of sub-target points. These points serve as the basis for obstacle avoidance planning within the manipulator's configuration space, mitigating planning complexities. Moreover, the RRT algorithm is employed to address the challenge of local optima within the artificial potential field method. The stochastic nature of the RRT algorithm plays a crucial role in enabling the APF algorithm to break free from local optima. Ultimately, the efficacy of the algorithm is demonstrated through the planning of a path for obstacle avoidance on the DOBOT CR5 manipulator using MATLAB.

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DynaInsRemover: A Real-time Dynamic Instance-Aware Static 3D LiDAR Mapping Framework for Dynamic Environment

DynaInsRemover: A Real-time Dynamic Instance-Aware Static 3D...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Huanfeng Zhao Meibao Yao Xueming Xiao Bo Zheng Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Opto-Electronic Measurement and Optical Information Transmission Technology Shanghai Aerospace Control Technology Institute Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Dynamic objects diversify the distribution of point cloud in the map, degrading the performance of the robotic downstream tasks. To address this problem, we present a novel real-time dynamic instance-aware static mapping framework called DynaInsRemover, which exploits the geometric discrepancies between instances to efficiently remove dynamic objects and preserve more details of static map. It contains the Instance Occupancy Check module for initial dynamic instance proposal and the Instance Belief Update module for reverting false positives. We quantitatively evaluate our approach performance on the SemanticKITTI dataset and validate it in a real-world environment. Experimental evaluations show that our method achieves very promising results in dynamic environments. The implementation of our method is available as open source at: https://***/Zhaohuanfeng/***.

关键词： Point cloud compression Three-dimensional displays Laser radar Real-time systems Windows Proposals Object recognition

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An Economic Scheduling Strategy of Photovoltaic Storage Micro-grid Considering Demand Response

An Economic Scheduling Strategy of Photovoltaic Storage Micr...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Rundong Liu Sen Zhang Yincheng Zhao Haojie Ma Luan Chen Weihao Hu Ming Tang Wei Zhan Qingjia Zhou 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 SPIC Sichuan Electric Power Co. LTD Chengdu China SPIC Southwest Energy Research Institute Chengdu China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

To realize the economic optimization dispatch of PSMG (Photovoltaic Storage Micro-grid), considering the stochastic influence of multiple uncertainties, this study formulates a day-ahead optimal dispatching strategy of PSMG with the minimum comprehensive operating cost as the objective function. Firstly, the source-load uncertainty is dealt with by scenario generation using the Monte Carlo method and k-means clustering algorithm. Then the peak shaving ability of the system is enhanced by the introduction of flexible loads, and the scheduling flexibility of the photovoltaic storage system is increased by the integrated demand response increases the scheduling flexibility of the photovoltaic storage system. Finally, simulation results show that the scheduling scheme can prompt the source-load to participate in peak shaving and valley filling at the same time, increase the new energy consumption capacity of the photovoltaic storage micro-grid, and effectively improve the economic and social benefits of the micro-grid.

关键词： Photovoltaic systems Uncertainty Fluctuations Costs Monte Carlo methods Simulation Demand response

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Research and practice on visual leakage detection technology of nitrogen gas lift in Changqing oilfield 22

Research and practice on visual leakage detection technology...

引用

2nd International Conference on control and Intelligent Robotics, ICCIR 2022

作者： Cao, Kang Luo, Yougang Li, Bing Huo, Dongkai Yan, Zhengguo Key Laboratory of Shaanxi Province for Measurement and Control Technology of Oil and Gas Wells Shaanxi Xi'an710065 China Research Institute of Oil and Gas Technology Changqing Oilfield Company Shaanxi Xi'an710018 China National Engineering Laboratory for Exploration and Development of Low-permeability Oil and Gas Fields Shaanxi Xi'an710018 China Changqing Branch PetroChina Logging Co. Ltd Shaanxi Xi'an710200 China

ISBN: (纸本)9781450397179

In the development and production of oil and gas fields in recent years, treatment of casing damage wells has always been the focus of tapping potential of old wells in major oilfields. Due to various factors, a large amount of water is discharged from the leakage point of the casing, which seriously affects the production efficiency of the oil well. In view of this, this paper presents a leak detection method for casing damaged wells, using nitrogen gases to lift technology to destroy the downhole pressure balance, resulting in liquid outflow of the casing failure point and forming fluid patterns of the wellbore. Combined with VideoLog visual logging technology, the flow direction, flow pattern and pipe wall condition of well fluid in wellbore are observed, and the water breakthrough position of casing is quickly and accurately located to realize visual leakage detection of underground nitrogen gas lift. From the actual case practice of Changqing Oilfield, it can be concluded that the visualization of leak detection by nitrogen gas lifts is an effective leak detection technology for casing breaking with oil wells, which has application and promotion value, and also provides technical guidance and practice experience of leak detection in similar oil wells. © 2022 ACM.

关键词： Gases

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Multi-objective day-ahead optimal scheduling of wind-solar microgrid considering V2G technology

Multi-objective day-ahead optimal scheduling of wind-solar m...

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第34届中国控制与决策会议

作者： LV Shuai-shuai WANG Hui WANG Ming-yue LI Zi-jie WU Di Changchun Institute of Technology National and Local Joint Engineering Research Center for Measurement Control and Safe Operation of Intelligent Distribution Networks Datang Xiangyang Wind Power Co.LTD

Although adding V2 G economic dispatch to the wind-solar load-storage microgrid has higher economic benefits,it may lead to "peaks on top of peaks".In order to solve this problem,this paper establishes a three-objective day-ahead optimal scheduling model that comprehensively considers economics,grid-connected power mean square error and grid-connected power peak-to-valley *** multi-objective gray wolf algorithm with multi-period cosine convergence factor is used to solve the transfer tram load mode and V2 G mode respectively,which effectively compensates for the disadvantage that the gray wolf algorithm is easy to fall into local ***,the numerical example analysis shows that the established optimal scheduling model is correct and effective.

关键词： Wind-solar-load-storage joint V2G Load Forecasting day-ahead optimal scheduling improved multi-objective gray wolf algorithm

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Deep self-organizing map neural networks for plantar pressure image segmentation employing marr-hildreth features

引用

International Journal of Ambient Computing and Intelligence 2021年第4期12卷 1-21页

作者： Han, Jianlin Wang, Dan Li, Zairan Shi, Fuqian Glorious Sun Guangdong School of Fashion Huizhou University Huizhou China Huidong Shoes Science and Technology Innovation Center Huizhou China Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University China Wenzhou Polytechnic Wenzhou China Rutgers Cancer Institute of New Jersey New Brunswick United States

Using the plantar pressure imaging analysis method to realize the optimization design of shoe last is still relatively preliminary. The analysis and utilization of imaging data still have problems such as single processing, incomplete information acquisition, and poor processing model robustness. A deep self-organizing map neural network based on Marr-Hildreth filter (dSOM-wh) is developed in this research. The structure and learning algorithms were optimized by learning vector quantization (LVQ) and count propagation (CP). As a kind of Marr-Hildreth filter, Laplacian of Gaussian (LoG) was developed for the preprocessing. The proposed method performed high effectiveness in accuracy (AC) (92.88%), sensitive (SE) (0.8941), and f-measurement (F1) (0.8720) by comparing with ANN, CNN, SegNet, ResNet, and pre-trained inception-v neural networks. The classification-based plantar pressure biomedical functional zoning technologies have potential applications in the comfort shoe production industry. Copyright © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

关键词： Image segmentation

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Multi-source data processing and fusion method for power distribution internet of things based on edge intelligence

arXiv

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arXiv 2022年

作者： Yuan, Quande Pi, Yuzhen Kou, Lei Zhang, Fangfang Li, Yang Zhang, Zhenming Changchun Institute of Technology Changchun China Qingdao China National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control with Safety Operation Technology Changchun Institute of Technology Changchun China Northeast Electric Power University Jilin China

With the rapid advancement of the Energy Internet strategy, the number of sensors within the Power Distribution Internet of Things (PD-IoT) has increased dramatically. In this paper, an edge intelligence-based PD-IoT multi-source data processing and fusion method is proposed to solve the problems of confusing storage and insufficient fusion computing performance of multi-source heterogeneous distribution data. First, a PD-IoT multi-source data processing and fusion architecture based on edge smart terminals is designed. Second, to realize the uniform conversion of various sensor data sources in the distribution network in terms of magnitude and order of magnitude. By introducing the Box-Cox transform to improve the data offset problem in the Zscore normalization process, a multi-source heterogeneous data processing method for distribution networks based on the Box-Cox transform Zscore is proposed. Then, the conflicting phenomena of DS inference methods in data source fusion are optimally handled based on the PCA algorithm. A multi-source data fusion model based on DS inference with conflict optimization is constructed to ensure the effective fusion of distribution data sources from different domains. Finally, the effectiveness of the proposed method is verified by an experimental analysis of an IEEE39 node system in a regional distribution network in China. Copyright © 2022, The Authors. All rights reserved.

关键词： Internet of things

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