Pub Date : 2019-08-01DOI: 10.1109/ICSGEA.2019.00039
Wanzeng Cai, Binwen Wang, Shoulong Zhang
Digital oscilloscope is widely used in signal measurement and processing systems, but it can only deal with signals simply and raw waveform data can only be stored manually. More importantly, it is difficult to operate when multiple oscilloscopes are working in measurement systems simultaneously. In this paper, we proposed an implementation scheme of applying LabVIEW to build a user interface, which can be used for controlling two oscilloscopes remotely and acquiring data via network. This system has several common functions of oscilloscope and more some extensional functions than oscilloscope itself.
{"title":"Remote Control and Data Acquisition of Multiple Oscilloscopes Using LabVIEW","authors":"Wanzeng Cai, Binwen Wang, Shoulong Zhang","doi":"10.1109/ICSGEA.2019.00039","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00039","url":null,"abstract":"Digital oscilloscope is widely used in signal measurement and processing systems, but it can only deal with signals simply and raw waveform data can only be stored manually. More importantly, it is difficult to operate when multiple oscilloscopes are working in measurement systems simultaneously. In this paper, we proposed an implementation scheme of applying LabVIEW to build a user interface, which can be used for controlling two oscilloscopes remotely and acquiring data via network. This system has several common functions of oscilloscope and more some extensional functions than oscilloscope itself.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133813095","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}
Pub Date : 2019-08-01DOI: 10.1109/ICSGEA.2019.00107
Xu Linjuan, Liu Junhua, Zhao Wanjie, W. Yuanjian, Jiang Enhui
The erosion-resisting capacity of cohesive soil is relatively strong, and its starting factors are very complex, while the physical and mechanical properties of cohesive soil itself have a greater impact on its starting. Based on the experiment of starting erosion of cohesive soil in the lower reaches of the Yellow River, the starting condition of cohesive soil is studied from the point of view of soil mechanics. The physical phenomena of starting of cohesive soil are expounded, and the relationship between starting of cohesive soil and its physical and mechanical properties is analyzed. The experimental results show that the incipient shear stress of cohesive soil increases with the increase of dry density, and the relationship between them is approximately an increasing power function. The incipient shear stress increases with the decrease of water content, and increases with the increase of shear strength. This study can reflect the characteristics of cohesive soil preferably, and it is laid the foundation to further study on the anti-scouribility of cohesive soil.
{"title":"Experimental Study on Starting Shear Stress of Cohesive Soil in The Lower Yellow River","authors":"Xu Linjuan, Liu Junhua, Zhao Wanjie, W. Yuanjian, Jiang Enhui","doi":"10.1109/ICSGEA.2019.00107","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00107","url":null,"abstract":"The erosion-resisting capacity of cohesive soil is relatively strong, and its starting factors are very complex, while the physical and mechanical properties of cohesive soil itself have a greater impact on its starting. Based on the experiment of starting erosion of cohesive soil in the lower reaches of the Yellow River, the starting condition of cohesive soil is studied from the point of view of soil mechanics. The physical phenomena of starting of cohesive soil are expounded, and the relationship between starting of cohesive soil and its physical and mechanical properties is analyzed. The experimental results show that the incipient shear stress of cohesive soil increases with the increase of dry density, and the relationship between them is approximately an increasing power function. The incipient shear stress increases with the decrease of water content, and increases with the increase of shear strength. This study can reflect the characteristics of cohesive soil preferably, and it is laid the foundation to further study on the anti-scouribility of cohesive soil.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124639406","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}
In order to solve the problem of low accuracy of current uhv transmission line fault location method, a fault area location method based on transient recording technology is proposed. According to the principle of transient wave recording, fault collector of transmission line is designed to collect fault data. The fault signal collected by wavelet scale decomposition is used to determine the time when the fault traveling wave head reaches the detection point. Calculate the traveling wave velocity of the fault, and calculate the distance between the fault point and the detection point based on the arrival time of the wave head, so as to locate the fault area of uhv transmission line. Through the comparison with the current line fault location method, it is proved that the proposed fault area location method for uhv transmission line based on transient recording technology can effectively improve the fault location accuracy of the line by nearly twice, and is worth popularizing.
{"title":"Research on Fault Area Location Method of UHV Transmission Line Based on Transient Recording Technology","authors":"Chuan Zhang, Zhilu Wang, Haichao Peng, Guangxin Zhang, Liying Zhao, Minzhen Wang","doi":"10.1109/ICSGEA.2019.00020","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00020","url":null,"abstract":"In order to solve the problem of low accuracy of current uhv transmission line fault location method, a fault area location method based on transient recording technology is proposed. According to the principle of transient wave recording, fault collector of transmission line is designed to collect fault data. The fault signal collected by wavelet scale decomposition is used to determine the time when the fault traveling wave head reaches the detection point. Calculate the traveling wave velocity of the fault, and calculate the distance between the fault point and the detection point based on the arrival time of the wave head, so as to locate the fault area of uhv transmission line. Through the comparison with the current line fault location method, it is proved that the proposed fault area location method for uhv transmission line based on transient recording technology can effectively improve the fault location accuracy of the line by nearly twice, and is worth popularizing.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127054424","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}
Pub Date : 2019-08-01DOI: 10.1109/icsgea.2019.00014
W. Si, C. Fu, K. Gao, Jia-Min Zhang, Lin He, Hailong Bao, Xin-ye Wu
Nowadays, the detection of acoustical emission is widely used for fault diagnosis of gas insulated substations (GIS) in normal operation and factory tests, which is called 'non-conventional' method recommended in the standard IEC TS 62478-2016 and GIGRE D1.33 444. In this paper, to develop a data analyzer for acoustic detection (AD) system to make an assistant diagnosis for technical personnel or equipment operation and maintenance personnel, based on the previous research on the experimental research, pattern identification with phase compensation and the software development, the algorithm model design and its application is given in detail. For the acoustical emission signals (n, ti, qi), the BP artificial neural network optimized by genetic algorithm (GA-BP) is used as a classifier based on the fingerprint consisting of several statistic operators, which are derivate form typical 2D histograms of PRPD with identification with phase compensation (IPC). Experimental results show that the comprehensive algorithm model designed for identification is practical and effective.
{"title":"Research on a General Fast Analysis Algorithm Model for Pd Acoustic Detection System: The Algorithm Model Design and Its Application","authors":"W. Si, C. Fu, K. Gao, Jia-Min Zhang, Lin He, Hailong Bao, Xin-ye Wu","doi":"10.1109/icsgea.2019.00014","DOIUrl":"https://doi.org/10.1109/icsgea.2019.00014","url":null,"abstract":"Nowadays, the detection of acoustical emission is widely used for fault diagnosis of gas insulated substations (GIS) in normal operation and factory tests, which is called 'non-conventional' method recommended in the standard IEC TS 62478-2016 and GIGRE D1.33 444. In this paper, to develop a data analyzer for acoustic detection (AD) system to make an assistant diagnosis for technical personnel or equipment operation and maintenance personnel, based on the previous research on the experimental research, pattern identification with phase compensation and the software development, the algorithm model design and its application is given in detail. For the acoustical emission signals (n, ti, qi), the BP artificial neural network optimized by genetic algorithm (GA-BP) is used as a classifier based on the fingerprint consisting of several statistic operators, which are derivate form typical 2D histograms of PRPD with identification with phase compensation (IPC). Experimental results show that the comprehensive algorithm model designed for identification is practical and effective.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130008967","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}
Pub Date : 2019-08-01DOI: 10.1109/ICSGEA.2019.00079
He Xi, Duan Zhengjie, L. Tao, Yuan Junfeng
The big data sources within an enterprise include physical power grid operation and maintenance, power supply marketing service and grid enterprise operation. Currently, various unstructured data shows an explosive growth, how to use the data-intensive science brought about by big data to make technological innovation still needs to be studied so as to serve the society better. This paper studies the intelligent matching of power big data based on the Chinese word segmentation technology.
{"title":"Study on the Intelligent Matching of Power Big Data Based on the Chinese Word Segmentation Technology","authors":"He Xi, Duan Zhengjie, L. Tao, Yuan Junfeng","doi":"10.1109/ICSGEA.2019.00079","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00079","url":null,"abstract":"The big data sources within an enterprise include physical power grid operation and maintenance, power supply marketing service and grid enterprise operation. Currently, various unstructured data shows an explosive growth, how to use the data-intensive science brought about by big data to make technological innovation still needs to be studied so as to serve the society better. This paper studies the intelligent matching of power big data based on the Chinese word segmentation technology.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130902058","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}
Pub Date : 2019-08-01DOI: 10.1109/ICSGEA.2019.00127
Chen Ping
Through the analysis and research of visual design and information transmission of the interface of e-commerce website, this paper summarizes the psychological state of the interface visual design of e-commerce website to consumers and its element manifestations. By the relevant theoretical basis, research and analysis and expression techniques, the consumer's visual perception of e-commerce website interface is conveyed. Then, taking an e-commerce website as an example, the perceptual knowledge and evaluation of the user is converted into the level selection of the design elements of the web interface with the perceptual knowledge and evaluation of the product details page as the starting point, by using the theory of Kansei Engineering. Aiming at higher user preferences, the integrated algorithm of BP neural network and genetic algorithm is used to optimize the web interface globally. It truly realizes the user's perceptual needs into the design of web pages to achieve user-centered optimization design of web interface, which effectively conveys visual information and enable it to be accurate and powerful for the expression of visual information.
{"title":"A Visual Communication Design Method for E-Commerce Websites","authors":"Chen Ping","doi":"10.1109/ICSGEA.2019.00127","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00127","url":null,"abstract":"Through the analysis and research of visual design and information transmission of the interface of e-commerce website, this paper summarizes the psychological state of the interface visual design of e-commerce website to consumers and its element manifestations. By the relevant theoretical basis, research and analysis and expression techniques, the consumer's visual perception of e-commerce website interface is conveyed. Then, taking an e-commerce website as an example, the perceptual knowledge and evaluation of the user is converted into the level selection of the design elements of the web interface with the perceptual knowledge and evaluation of the product details page as the starting point, by using the theory of Kansei Engineering. Aiming at higher user preferences, the integrated algorithm of BP neural network and genetic algorithm is used to optimize the web interface globally. It truly realizes the user's perceptual needs into the design of web pages to achieve user-centered optimization design of web interface, which effectively conveys visual information and enable it to be accurate and powerful for the expression of visual information.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"23 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130938767","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}
Pub Date : 2019-08-01DOI: 10.1109/ICSGEA.2019.00065
X. Zou
Object detection is widely used in the field of computer vision and crucial for variety of applications, e.g., self-driving car. During the development of half a century, object detection methods have been continuously developed, and generated numerous approaches which obtained promising achievements. At present, the approach of object detection has been largely evolved into two categories which are traditional machine learning methods utilizing varied computer vision techniques and deep learning method. This article presents a review of object detection techniques. Firstly, the existing methods based on traditional machine learning are summarized and introduced. Then, two main schools of deep learning methods, R-CNN and YOLO, are selected for analysis and introduction. At the end of the article, the methods mentioned are briefly compared and discussed.
{"title":"A Review of Object Detection Techniques","authors":"X. Zou","doi":"10.1109/ICSGEA.2019.00065","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00065","url":null,"abstract":"Object detection is widely used in the field of computer vision and crucial for variety of applications, e.g., self-driving car. During the development of half a century, object detection methods have been continuously developed, and generated numerous approaches which obtained promising achievements. At present, the approach of object detection has been largely evolved into two categories which are traditional machine learning methods utilizing varied computer vision techniques and deep learning method. This article presents a review of object detection techniques. Firstly, the existing methods based on traditional machine learning are summarized and introduced. Then, two main schools of deep learning methods, R-CNN and YOLO, are selected for analysis and introduction. At the end of the article, the methods mentioned are briefly compared and discussed.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123175500","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}
Pub Date : 2019-08-01DOI: 10.1109/ICSGEA.2019.00078
Jian Chen, Luchuan Dai
To develop the vehicle detection function for preceding car, this paper chooses the method based on machine vision learning for vehicle detection. The LBP and Haar features of cars are used as descriptors, and the positive and negative samples of the vehicle are trained by AdaBoost network, to achieve the detection network. The preceding car video is detected by the training network. Then, Kalman filter technology is introduced to solve the problem of CamShift which is prone to heel-and-miss when the moving state of the target changes. At the same time, the improved Mixture Gauss model and the designed tracking matrix list are used to realize the full automatic multi-target tracking based on CamShift algorithm. The simulation results show that the proposed scheme has fast detection speed, low tracking time complexity and good effect, which also has good comprehensive performance compared with similar algorithms.
{"title":"Research on Vehicle Detection and Tracking Algorithm for Intelligent Driving","authors":"Jian Chen, Luchuan Dai","doi":"10.1109/ICSGEA.2019.00078","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00078","url":null,"abstract":"To develop the vehicle detection function for preceding car, this paper chooses the method based on machine vision learning for vehicle detection. The LBP and Haar features of cars are used as descriptors, and the positive and negative samples of the vehicle are trained by AdaBoost network, to achieve the detection network. The preceding car video is detected by the training network. Then, Kalman filter technology is introduced to solve the problem of CamShift which is prone to heel-and-miss when the moving state of the target changes. At the same time, the improved Mixture Gauss model and the designed tracking matrix list are used to realize the full automatic multi-target tracking based on CamShift algorithm. The simulation results show that the proposed scheme has fast detection speed, low tracking time complexity and good effect, which also has good comprehensive performance compared with similar algorithms.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121181005","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}
Pub Date : 2019-08-01DOI: 10.1109/ICSGEA.2019.00086
Shishi Chen
aiming at the problem that the traditional ideological and political teaching resource integration platform cannot meet the rapid resource integration in the era of big data, this paper constructs the ideological and political teaching resource integration platform based on big data. Through the collection of various types of teaching resources on the Internet, and the collection of resources to filter, classify, review and other processing of teaching resources metadata. In the database to discharge weight, conversion, cleaning to complete the data integration. The integrated data will be stored in the platform database, and the platform users can download and use teaching resources through data interaction to complete the construction of the resource integration platform. By comparing the speed of resource integration with traditional resource integration platform, it is verified that the constructed resource integration platform can meet the requirements of resource integration in the era of big data.
{"title":"Construction of Ideological and Political Teaching Resource Integration Platform Based on Big Data","authors":"Shishi Chen","doi":"10.1109/ICSGEA.2019.00086","DOIUrl":"https://doi.org/10.1109/ICSGEA.2019.00086","url":null,"abstract":"aiming at the problem that the traditional ideological and political teaching resource integration platform cannot meet the rapid resource integration in the era of big data, this paper constructs the ideological and political teaching resource integration platform based on big data. Through the collection of various types of teaching resources on the Internet, and the collection of resources to filter, classify, review and other processing of teaching resources metadata. In the database to discharge weight, conversion, cleaning to complete the data integration. The integrated data will be stored in the platform database, and the platform users can download and use teaching resources through data interaction to complete the construction of the resource integration platform. By comparing the speed of resource integration with traditional resource integration platform, it is verified that the constructed resource integration platform can meet the requirements of resource integration in the era of big data.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"163 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116690734","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}
Pub Date : 2019-08-01DOI: 10.1109/icsgea.2019.00019
Wang Zuchuan, Yao Haiting, Wu Xiaoye
This paper reports the research results of high power silicon carbide Schottky barrier diode (SiC SBD) in three aspects, namely the quality and type selection of SiC materials, device structure of SBD and the manufacturing process of SiC devices. Besides, the key processes of manufacturing SiC SBD, i.e. p-type ion implantation and activation process, ohmic contact process, Schottky metal preparation process, and passivation layer preparation process, are analyzed in detail. The paper introduces the preparation method of SiC SBD with a withstand voltage of 1200V, a current density of more than 120A/cm2 and a junction capacitance of less than 0.4pf, proposing a new technical route and process flow for preparation of high-power SiC SBD.
{"title":"Technical Research on High Power Silicon Carbide Schottky Barrier Diode","authors":"Wang Zuchuan, Yao Haiting, Wu Xiaoye","doi":"10.1109/icsgea.2019.00019","DOIUrl":"https://doi.org/10.1109/icsgea.2019.00019","url":null,"abstract":"This paper reports the research results of high power silicon carbide Schottky barrier diode (SiC SBD) in three aspects, namely the quality and type selection of SiC materials, device structure of SBD and the manufacturing process of SiC devices. Besides, the key processes of manufacturing SiC SBD, i.e. p-type ion implantation and activation process, ohmic contact process, Schottky metal preparation process, and passivation layer preparation process, are analyzed in detail. The paper introduces the preparation method of SiC SBD with a withstand voltage of 1200V, a current density of more than 120A/cm2 and a junction capacitance of less than 0.4pf, proposing a new technical route and process flow for preparation of high-power SiC SBD.","PeriodicalId":201721,"journal":{"name":"2019 International Conference on Smart Grid and Electrical Automation (ICSGEA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114617039","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：