Edge computing-based defect identification model of power IoT edge side devices
文献类型：会议论文
| 作者 | Li DW(李大伟)1; Jia GT(贾耕涛)1; Song CH(宋纯贺)2,3,4 ; Yu SM(于诗矛)2,3,4
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| 出版日期 | 2020 |
| 会议日期 | November 6-8, 2020 |
| 会议地点 | Chongqing, China |
| 关键词 | Edge computing isolated forest smart sensor fault diagnosis |
| 页码 | 728-732 |
| 英文摘要 | There are various types of devices on the terminal side of the power Internet of Things, and the data collected through various sensors shows an exponential growth. The current in-depth application of edge computing technology can not only ease the pressure of network transmission, but also improve the timeliness of fault diagnosis. Edge computing technology is A new way to solve the fault diagnosis of equipment on the edge of the power grid. From the perspective of edge fault diagnosis, this paper expounds the fault diagnosis model of power IoT edge devices based on edge computing, and combines the isolated forest algorithm to design smart sensor data-based power IoT edge device fault diagnosis algorithms. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 IEEE. |
| 源文献作者 | Chengdu Global Union Academy of Science and Technology ; Chongqing Geeks Education Technology Co., Ltd ; Chongqing Global Union Academy of Science and Technology ; Chongqing University of Technology ; Global Union Academy of Science and Technology ; IEEE Beijing Section |
| 产权排序 | 2 |
| 会议录 | Proceedings of 2020 IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2020
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-5224-0 |
| 源URL | [http://ir.sia.cn/handle/173321/28216]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 通讯作者 | Li DW(李大伟) |
| 作者单位 | 1.Start Grid Shanghai Information Telecommunication Company, Shanghai 200122, China 2.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 11016, China 4.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Li DW,Jia GT,Song CH,et al. Edge computing-based defect identification model of power IoT edge side devices[C]. 见:. Chongqing, China. November 6-8, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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