检索结果-内蒙古大学图书馆

Single-ended protection method for hybrid HVDC transmission line based on transient voltage characteristic frequency band

引用

Protection and control of Modern Power Systems 2023年第2期8卷 207-217页

作者： Hongchun Shu Shixin Wang Shunguang Lei Yunnan Key Laboratory of Green Energy Electric Power Measurement DigitalizationControl and ProtectionKunming University of Science and TechnologyKunming 650500Yunnan ProvinceChina School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001Heilongjiang ProvinceChina

Hybrid high-voltage direct current(HVDC)transmission has the characteristic of long transmission distance,complex corridor environment,and rapid fault evolution of direct current(DC)*** high fault current can easily cause irreversible damage to power devices,rapid and reliable line protection and isolation are necessary to improve the security and reliability of hybrid HVDC transmission *** address such requirement,this paper proposes a single-ended protection method based on transient voltage frequency band ***,the frequency characteristics of the smoothing reactor,DC filter,and DC line are analyzed,and the characteristic frequency band is defined.A fault criterion is then constructed based on the voltage characteristic frequency band energy,and faulty pole selection is performed according to the fault voltage characteristic frequency band energy *** proposed protection method is verified by simulation,and the results show that it can rapidly and reliably identify internal and external faults,accurately select faulty poles without data communication synchronization,and has good fault-resist-ance and anti-interference performance.

关键词： Boundary frequency characteristics Characteristic frequency band Hybrid HVDC Single-end protection Transient voltage

来源：评论

学校读者我要写书评

暂无评论

Research on the Wirtinger Flow algorithm based on quadratic distribution initial value 1

Research on the Wirtinger Flow algorithm based on quadratic ...

引用

1st Advanced Imaging and Information Processing Conference, AIIP 2023

作者： Xie, Zhenfei Yu, Xuelian Wang, Zhengxian Li, Heng Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin150080 China Shenzhen Engineering Laboratory of Aerospace Detection and Imaging College of Electronic and Information Engineering Harbin Institute of Technology Shenzhen518055 China

ISBN: (纸本)9781510671904

Phase retrieval algorithms, such as the Wirtinger Flow (WF) algorithm, are widely used in various fields. As a non-convex optimization algorithm for phase retrieval, WF is commonly employed in the reconstruction of holograms in holographic image projection. These types of algorithms typically involve two stages: an initialization stage and an iterative optimization stage. In the initialization stage, an initial value is provided, and a spectral method is used to calculate an approximate solution as the initial guess. The iterative optimization stage then utilizes the Wirtinger gradient to iteratively compute and converge the initial guess to a nearby real solution, thereby obtaining the global optimal solution. However, due to the random nature of the initial values, the computed results often exhibit significant instability. To address this issue, this paper proposes an approach based on a quadratic distribution for improving the stability of the results. In the initialization stage, the initial value is set as the quadratic distribution initial value. Then, the spectral method is applied again to calculate the initial guess. Since the quadratic distribution initial value is artificially assigned, it enhances the stability of the computed results. To validate this method, the paper applies the quadratic distribution initial value to both the initialization stage of the WF algorithm and the Truncated Amplitude Flow (TAF) algorithm. A comparison is made between the results obtained using random initial value and those obtained using the quadratic distribution initial values. The results demonstrate that compared to random initial values, the quadratic distribution initial values can achieve faster and equally accurate computation results with higher stability. Finally, this method is applied to simulation experiments of in-line digital holography, and the reconstruction results from the experiments further confirm the effectiveness of our approach. © 2023 SPIE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Design of improved road sign recognition system based on deep learning

Design of improved road sign recognition system based on dee...

引用

2022 International Conference on Geographic Information and Remote Sensing technology, GIRST 2022

作者： Ding, Wenfei Li, Wen Ma, Dezhong Electronic Information Engineering Institute Harbin Huade University Harbin China College of Measurement-Control Technology & Communications Engineering Harbin University of Science & Technology Harbin China

ISBN: (纸本)9781510662186

As the basis of intelligent vehicle environment identification, street sign recognition is a necessary condition to assist safe driving. It is of great significance for realizing automatic driving, improving intelligent transportation system and promoting smart city construction. Traditional traffic sign recognition technology is limited for complex scenes, and the recognition effect is also affected by weather and light. The road sign recognition system based on deep learning includes street sign detection and street sign recognition. YOLOv3 deep learning object detection method is adopted for road sign detection, and CCTSDB standard data set is used as experimental data to perform operations such as region trimming, batch conversion of data format, BM3D noise reduction and image preprocessing and enhancement technology. 1800 images were selected to form the training set and test set, which ensured the high efficiency and timeliness of the road sign detection algorithm. The road sign recognition system adopts the image recognition method of Darknet-53, and the algorithm is optimized. The trained system is detected under the test of CCTSDB dataset, and the detection accuracy is over 97%, and the detection time reaches 0.021s. Therefore, the system meets the requirement of accurate real-time processing of traffic sign detection and recognition system. © 2023 SPIE.

关键词： Noise abatement

来源：评论

学校读者我要写书评

暂无评论

Multi-scale network for single image deblurring based on ensemble learning module

引用

Multimedia Tools and Applications 2025年第11期84卷 9045-9064页

作者： Wu, WenBo Pan, Yun Su, Na Wang, JingTao Wu, ShaoChuan Xu, ZeKun Yu, YouJian Liu, YaPeng State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China School of Computer and Cyberspace Security Communication University of China Beijing100024 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China College of Computer and Control Engineering Northeast Forestry University Harbin150040 China School of Computer and Information Engineering Tianjin Chengjian University Tianjin300384 China School of Computer Science and Technology Anhui University Hefei230601 China

In this paper, we have identified two primary issues with current multi-scale image deblurring methods. On the one hand, the blurring scale is ignored. On the other hand, the context information of images is not fully utilized, and the spatial detail information of images is lost. To better solve the above problems, on top of that, this paper proposes a multi-scale network for single image deblurring. The designed network contains two parts: 1) Ensemble Learning Model: The Weak Learning Model in this module connects multiple weak learners in series to increase network depth. Moreover, through multi-scale feature ensemble module, the output features and intermediate features of different weak learner are integrated, and finally strong learner is used to enhance the features with semantic information at different scales;2) Spatial Feature Enhancement Module: This module can preserve spatial detail information of images and compensate for the disadvantages of losing image spatial details due to continuous downsampling in the Ensemble Learning Model structure. Our proposed deblurring model has been extensively evaluated on several benchmark datasets, and the model achieves superior performance compared to the most advanced deblurring methods. In particular, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values are 33.57 dB and 0.965 on the GoPro dataset, respectively, with PSNR and SSIM improving by 0.49 dB and 0.002 over NAFNet, and 0.65 dB and 0.004 over Restormer. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

A Time-Efficient Path Navigating Landmine Detection Robot

A Time-Efficient Path Navigating Landmine Detection Robot

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective communication Technologies, INSPECT 2024

作者： Bhattacharjee, Rituraj Mukherjee, Subhradip Hardik Gururaj Rajpurohit, Manish Manipal Institute of Technology Manipal Academy of Higher Education Instrumentation & Control Engineering Department Manipal India MVJ College of Engineering Electronics and communication Department Bangalore India

ISBN: (纸本)9798350379525

The goal of a landmine detection robot is to map the remaining area on a visual map with millimeter precision after covering as much ground as it can show landmines. The prototype land mine detection robot model described in this study offers a visual interface for mapping landmines, modifying PIDs, and aligning cameras. It is also reasonably powerful, accurate, and easy to operate with other sensors. The manual, semi-auto, and auto modes of controlling the differential drive robot are emphasized. Image processing determines the exact location of the robot and provides live reckoning feedback to its dead reckoning servo control. A beat metal detector is a kind of quiet sensor used to locate landmines. The overall objective of the system is to provide the user with something robust, affordable, and easily comprehensible for the user. © 2024 IEEE.

关键词： Landmine detection

来源：评论

学校读者我要写书评

暂无评论

Wrapper-based feature selection for general data set: the quantum sand cat swarm optimization

Wrapper-based feature selection for general data set: the qu...

引用

Computer, Vision and Intelligent technology (ICCVIT), International Conference on

作者： Jin Yue Ying Guo Hongyuan Gao Dalian Institute of Measurement and Control Technology Dalian China College of Information and Communication Engineering Harbin Engineering University Harbin China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

The existing wrapper feature selection methods have problems such as the difficulty of balancing a relatively high classification accuracy rate with a low feature selection rate, and there are problems such as long time consumption. In response to these issues, this paper combines quantum computing theory and sand cat swarm optimization to design quantum sand cat swarm optimization and combined with K-nearest neighbor method for feature selection. The optimal solution of quantum sand cat swarm optimization is set as the selected optimal feature subset. Simulation experiments are executed on 6 UCI data sets to compare with 4 classical swarm intelligence algorithms. The simulation outcomes show that the wrapper feature selection on the ground of quantum sand cat swarm optimization achieves lower feature selection rate , faster time and higher classification accuracy than the comparison method. It is a high precision and practical wrapper feature selection method.

关键词： Quantum computing Accuracy High dimensional data Quantum mechanics Nearest neighbor methods Feature extraction Robustness Classification algorithms Particle swarm optimization Optimization

来源：评论

学校读者我要写书评

暂无评论

Observation and research of deep underground multi-physical fields—Huainan–848 m deep experiment

引用

Science China Earth Sciences 2023年第1期66卷 54-70页

作者： Yun WANG Yaxin YANG Heping SUN Chengliang XIE Qisheng ZHANG Xiaoming CUI Chang CHEN Yongsheng HE Qiangqiang MIAO Chaomin MU Lianghui GUO Jiwen TENG School of Geophysics and Information Technology China University of GeosciencesBeijing 100083China School of Geophysics and Measurement-control Technology East China University of TechnologyNanchang 330013China Innovation Academy for Precision Measurement Science and Technology Chinese Academy of SciencesWuhan 430077China Institution of Engineering Protection IDEAMSPLALuoyang 471023China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and TechnologyHuainan 232001China Institute of Geochemistry Chinese Academy of SciencesGuiyang 550081China

Compared with the surface,the deep environment has the advantages of allowing“super-quiet and ultra-clean”-geophysical field observation with low vibration noise and little electromagnetic interference,which are conducive to the realization of long-term and high-precision observation of multi-physical fields,thus enabling the solution of a series of geoscience *** the Panyidong Coal Mine,where there are extensive underground tunnels at the depth of 848 m below sea level,we carried out the first deep-underground geophysical observations,including radioactivity,gravity,magnetic,magnetotelluric,background vibration and six-component seismic *** concluded from these measurements that(1)the background of deep subsurface gravity noise in the long-period frequency band less than 2 Hz is nearly two orders of magnitude weaker than that in the surface observation environment;(2)the underground electric field is obviously weaker than the surface electric field,and the relatively high frequency of the underground field,greater than 1 Hz,is more than two orders of magnitude weaker than that of the surface electric field;the east-west magnetic field underground is approximately the same as that at the surface;the relatively high-frequency north-south magnetic field underground,below 10 Hz,is at least one order of magnitude lower than that at the surface,showing that the underground has a clean electromagnetic environment;(3)in addition to the highfrequency and single-frequency noises introduced by underground human activities,the deep underground space has a significantly lower background vibration noise than the surface,which is very beneficial to the detection of weak earthquake and gravity signals;and(4)the underground roadway support system built with ferromagnetic material interferes the geomagnetic *** also found that for deep observation in the“ultra-quiet and ultra-clean”environment,the existing geophysical equipment and observation technology hav

关键词： Multi-physical fields Radioactivity Gravity Geomagnetic Electromagnetic Earthquake Observations deep underground

来源：评论

学校读者我要写书评

暂无评论

Combined Classification of Hyperspectral and LiDAR Data based on Dual-Channel Cross-Transformer 23

Combined Classification of Hyperspectral and LiDAR Data base...

引用

Proceedings of the 2023 5th International Conference on Video, Signal and Image Processing

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

ISBN: (纸本)9798400709272

In the face of complex scenes, single-modal dominant classification tasks encounter limitations in performance due to insufficient information. On the other hand, joint classification of multimodal remote sensing data faces challenges such as data sample differences and lack of correlation in physical features between modalities, which can impact classification performance. To fully integrate the heterogeneous information of multimodal data and improve classification performance, we propose a dual-channel cross-transformer feature fusion extraction network. The framework leverages self-attention mechanisms to aggregate features within each modality, and the feature fusion module based on cross-modal attention fully considers the complementary information between modalities. Classification tasks are performed using the fused spatial-spectral features obtained from the joint representation of modalities. Extensive experiments conducted on the Houston and MUUFL datasets demonstrate the effectiveness of the proposed model compared to existing methods.

关键词： Hyperspectral image LiDAR data cross modality feature fusion transformer

来源：评论

学校读者我要写书评

暂无评论

Multi-Object Detection and Classification in Construction Sites Based on YOLOv5 23

Multi-Object Detection and Classification in Construction Si...

引用

Proceedings of the 2023 5th International Conference on Video, Signal and Image Processing

作者： Xintao Liang Tianqi Jiang Qiang Fu Qingyan Wang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology China School of Electronics and Information Engineering Harbin Institute of Technology China

ISBN: (纸本)9798400709272

A thorough analysis of the framework structure of the YOLO algorithm is conducted, and based on the YOLOv5 algorithm, rapid detection and classification of extracted features are implemented. Addressing the issue of multi-object detection and classification in engineering sites, this study utilizes the YOLOv5 algorithm for object detection in engineering scenarios, constructs the ResNet50 network, and achieves training and recognition of categories for engineering vehicles, whether washed or unwashed. Additionally, the YOLOv5 algorithm is employed to detect whether construction personnel are wearing safety helmets and reflective clothing, enabling fast and accurate entity detection and classification at construction sites.

关键词： Deep Learning Object Detection ResNet50 YOLOv5

来源：评论

学校读者我要写书评

暂无评论

Image stitching method based on improved optimal seam

Image stitching method based on improved optimal seam

引用

2022 International Conference on Electronic Information engineering and Computer Science, EIECS 2022

作者： Ji, Xiu Wang, Yan Li, Cong Hou, Faming Guo, Shuanghao National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control with Safety Operation Technology Changchun Institute of Engineering Changchun China

ISBN: (纸本)9781510663312

In order to improve the running time of image stitching and remove the phenomenon of ghosting, this paper proposes an image stitching method based on the improved optimal seam ***, the two input images are preprocessed using a median filter ***, image registration is performed using the ORB algorithm. Finally, the best seam method based on the Canny operator is *** experimental results show that when stitching images, whether for large scale or small scale images, the algorithm in this paper has faster running speed and better stitching effect. © 2023 SPIE.

关键词： Median filters

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：