Research on Electrical Equipment Monitoring and Early Warning System Based on Internet of Things Technology

Author:

Lei Tianxiang12ORCID,Lv Fangcheng12,Liu Jiaomin1,Feng Jiahao3

Affiliation:

1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China

2. Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defence, North China Electric Power University, Baoding 071003, China

3. State Grid Shijiazhuang Electric Power Supply Company, Shijiazhuang 050000, China

Abstract

With the rapid increase of global population, the power load increases rapidly, and the electrical equipment such as generator, transformer, and power line in the power system is an important basis for production and life. Its safe operation is of great significance because it is related to people’s economic development and life stability. In recent years, with the rapid development of Internet of Things technology, the Internet of Things and electrical equipment safety early warning are combined to use their respective advantages to provide a new way for electrical equipment monitoring and early warning system. Through a variety of key technologies of the Internet of Things, such as sensor technology, network communication technology, and cloud computing technology, data, information exchange, and communication between electrical equipment and Internet technology are carried out according to the agreed protocol, and the safety of the operation status of electrical equipment is monitored in real time, so as to prevent power equipment failure and other problems. Based on this background, this paper studies the Internet of Things technology and electrical equipment monitoring and early warning system and analyzes its three-tier network architecture mode from the Internet of Things technology, namely, perception layer, network layer, and application layer. The combination of cloud computing and edge computing is studied and analyzed to provide theoretical support for the research of electrical equipment monitoring and safety early warning system. The wireless sensor network equipment is also installed on the electrical equipment through the Internet of Things technology to transmit data to the base station, so as to monitor whether the equipment operates safely. The monitoring and early warning system of wireless sensor system based on Internet of Things is given through case experiment. This system realizes relevant intelligent application services, which can not only ensure the stability of information transportation but also real-time monitoring of electrical equipment, early warning, shorten troubleshooting time, reduce the workload of power station staff, and achieve the functions of safety early warning, emergency command, and control. It is of great significance to the monitoring and early warning system of electrical equipment.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Failure prediction method of heat transfer tube of nuclear power steam generator based on WOA-SVR;Journal of Radiation Research and Applied Sciences;2024-06

2. Portable Data Collection Unit;2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET);2024-05-17

3. Optimal state filters for networked iterative learning control systems with data losses and noises;International Journal of Adaptive Control and Signal Processing;2024-02-07

4. Industrial Systems Optimization from Combining Internet of Things and Cloud Computing;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

5. Research on visualization monitoring technology of vulnerable high-voltage electrical equipment in substation based on BP artificial neural network;Applied Mathematics and Nonlinear Sciences;2024-01-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3