Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering最新文献_第9页

Fault Diagnosis Using Extended Belief Rule-Based Systems with Novel Rule Weight Calculation Method 基于扩展信念规则系统的故障诊断与新规则权重计算方法

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3386966

Haizhen Zhu, M. Xiao, Weijie Kang

引用次数: 0

Adaptive-Rate Compressive Sensing for Monitoring Video Based on Fast Sparsity Estimation 基于快速稀疏度估计的监控视频自适应压缩感知

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3386961

Jianming Wang, Jianhua Chen

引用次数: 2

The Partial Discharge Diagnosis and Location of C-GIS Cable Joint Based on Multiple Detection Method: High Voltage and Insulation Technology 基于高压和绝缘多重检测方法的C-GIS电缆接头局部放电诊断与定位

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3387022

Jin He, Y. Man, Liming Zhang, Rong Chen, Wei Wang, Meng Cao

{"title":"The Partial Discharge Diagnosis and Location of C-GIS Cable Joint Based on Multiple Detection Method: High Voltage and Insulation Technology","authors":"Jin He, Y. Man, Liming Zhang, Rong Chen, Wei Wang, Meng Cao","doi":"10.1145/3386415.3387022","DOIUrl":"https://doi.org/10.1145/3386415.3387022","url":null,"abstract":"In this paper, a suspension discharge case in the cable joint of 35kV Cubicle Gas Insulated Switchgear(C-GIS) is analyzed detailedly, and the C-GIS is operated by two outlet cable. First, this paper presents the comprehensive detection process based on ultrasonic, UHF (Ultra High Frequency) and HF (High Frequency) method, and detection results show that it is helpful to approve the accuracy of partial discharge (PD) detection by using this comprehensive idea, which can play the role of mutual corroboration. Second, this paper presents the location process, which is carried out under the coordination guidance of UHFUHF location method and acoustic-UHF location method, and the defect position is located in the range between 10cm and 20cm. At last, by dismantling this C-GIS, the accuracies of detection and location results are demonstrated, and the dismantling result shows that the broken wire of charged display devices and poor bonding in stress cone, caused by plugging and pulling the cable joint repeatedly, are the fundamental reason for this PD defect.","PeriodicalId":250211,"journal":{"name":"Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117311464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Visible and Infrared Image Fusion Using Convolutional Dictionary Learning with Consensus Auxiliary-Auxiliary Coupling 基于一致性辅助-辅助耦合的卷积字典学习的可见光和红外图像融合

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3386958

Chengfang Zhang, Xingchun Yang, Zhen Yue

引用次数: 3

Design and Implementation of Intelligent Garbage Classification System 智能垃圾分类系统的设计与实现

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3387088

Gukai Li, Juanjuan Li, Can Ge, Guoxing Yang, Zelin Yu, Xuan Chen, Jingjing Liao, Zhiheng Mu, Xiangyu Gao, Jiahao Tang, Fei He, Yifan Xia

引用次数: 0

Design of Simple Resistance Automatic Tester Based on STC89C52 基于STC89C52的简易电阻自动测试仪的设计

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3387045

Yongchao Xie, Li Yang, Jun Yan

引用次数: 0

A Review on Hierarchical Control Strategy in Microgrid 微电网分层控制策略研究进展

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3387038

Zixuan Yang, Langchen Huang, Zongao Yi, Yingxin Hu

引用次数: 1

Analyzing The Development of Technology from The Perspective of Patent: Taking Ships Diesel Engine as An Example 从专利的角度分析技术发展——以船舶柴油机为例

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3386976

Danyang Li, Xinlai Li

引用次数: 0

Multi Target Detection of UAV Video Based on Deep Convolution Neural Network 基于深度卷积神经网络的无人机视频多目标检测

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3386972

Xuejun Wang, Zhiguo Zhou, Yun Li

引用次数: 3

Research and Implementation of License Plate Location Based on Improved YOLO Algorithm 基于改进YOLO算法的车牌定位研究与实现

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering Pub Date : 2019-12-06 DOI: 10.1145/3386415.3386967

Jianmin Tao, Weiping Hu, Jiabin Ouyang

{"title":"Research and Implementation of License Plate Location Based on Improved YOLO Algorithm","authors":"Jianmin Tao, Weiping Hu, Jiabin Ouyang","doi":"10.1145/3386415.3386967","DOIUrl":"https://doi.org/10.1145/3386415.3386967","url":null,"abstract":"At present, license plate location technology mainly has traditional methods and deep learning methods. The traditional license plate location mainly relies on manual extraction of features, and according to the shape and proportion of the license plate to achieve license plate positioning. However, the traditional license plate location method is difficult to meet the requirements of license plate size, shape, illumination and other changes, and it is difficult to achieve the robustness of license plate location. The license plate location technology based on deep learning does not need to select features and design classifiers manually. Its implementation is mainly based on the network automatically learning features of the data to achieve end-to-end license plate location. In this paper, we mainly study You Only Look Once (YOLO) algorithm, which is not accurate enough for the small target positioning, and in order to further improve the license plate location accuracy and speed, we propose to use the large feature map size of 14x14, improve the loss function by adding the Generalized Intersection over Union (GIoU) loss, and when it is training, the Intersection over Union (IoU) calculation method is changed to GIoU, the feature extraction network uses ShuffleNetV2, MobileNetV2 and other networks to extract more accurate features. In the data about campus bayonet vehicles, compared with Single Shot MultiBox Detector (SSD) and YOLOv2, the improved YOLO algorithm has better location accuracy and less location time. The Mean Average Precision (mAP) of improved DetNet59 have reached 99.79% and the precision (prec) has reached 99.97%. For the color image with a width of 680 pixels, and height of 480 pixels, the license plate location time is about 47 milliseconds (ms).","PeriodicalId":250211,"journal":{"name":"Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116982143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1