期刊文献+

学生宿舍违规电器监控系统设计 被引量:3

Design of Monitoring System for Illegal Electrical Appliance in Student Dormitory
下载PDF
导出
摘要 针对学生宿舍用电安全问题,文章提出一种基于智能电表的宿舍用电器监控系统。系统分为智能电表和后台监控平台两个部分。通过智能电表完成用电器特征数据的采集与处理,通过4G模块将采集到的数据上传至后台监控平台进行分析处理。构建BP神经网络用电器识别系统,实现在线数据采集与监控,降低学生宿舍因用电设备短路、过载等问题而导致电气事故发生的概率,提高高校后勤对学生宿舍用电安全的管理效率。 Aiming at the problem of electricity safety in students'dormitory,this paper proposes a dormitory electrical appliance monitoring system based on intelligent electricity meter.The system is divided into two parts:intelligent electricity meter and background monitoring platform.Complete the collection and processing of electrical appliance characteristic data through the intelligent electricity meter,and upload the collected data to the background monitoring platform for analysis and processing through the 4G module.The BP neural network electrical appliance identification system is constructed to realize online data acquisition and monitoring,reduce the probability of electrical accidents caused by short circuit and overload of electric equipments in student dormitories,and improve the management efficiency of University logistics for electricity safety in student dormitories.
作者 刘扬 张朝霞 卢允杰 LIU Yang;ZHANG Chaoxia;LU Yunjie(School of Mechatronic Engineering and Automation,Foshan University,Foshan 528225,China;Guangdong Haodi Innovation Technology Co.,Ltd.,Foshan 528000,China)
出处 《现代信息科技》 2021年第20期1-5,10,共6页 Modern Information Technology
关键词 数据处理 BP神经网络 智能电表 在线监测 data processing BP neural network intelligent electricity meter online monitoring
  • 相关文献

参考文献6

二级参考文献62

  • 1罗雄彪,陈铁群.超声无损检测的发展趋势[J].无损检测,2005,27(3):148-152. 被引量:76
  • 2汤胜清,程小华.一种基于多层前向神经网络的谐波检测方法[J].中国电机工程学报,2006,26(18):90-94. 被引量:58
  • 3郑建国,石智,权豫西.非平稳信号的小波包阈值去噪方法[J].信息技术,2007,31(3):16-18. 被引量:10
  • 4MALLAT S. Theory for multi-resolution tion: the wavelet represention [J]. IEEE signal decomposi- Transactions on Pattern Analysis and Machine Intelligence, 1989,11 (7): 674-693.
  • 5HART G W.Nonintrusive appliance load monitoring[J].Proceedings of the IEEE,1992,80(12):1870-1891.
  • 6AHMED Z,ALEXANDER G,MUHAMMAD A I,et al.Nonintrusive load monitoring approaches for disaggregated energy sensing:a survey[J].Sensors,2012,12:16838-16866.
  • 7LIANG J,NG S K K,KENDALL G,et al.Load signature study—part I:basic concept,structure,and methodology[J].IEEE Transactions on Power Delivery,2010,25(2):551-560.
  • 8DINESH C,NETTASINGHE B W,GODALIYADDA R I,et al.Residential appliance identification based on spectral information of low frequency smart meter measurements[J].IEEE Transactions on Smart Grid,2015:1-12.
  • 9PARK H.Load profile disaggregation method for home appliances using active power consumption[J].Journal of Electrical Engineering and Technology,2013,8(3):572-580.
  • 10HASSAN T,JAVED F,ARSHAD N.An empirical investigation of V-I trajectory based load signatures for non-intrusive load monitoring[J].IEEE Transactions on Smart Grid,2014,5(2):870-878.

共引文献47

同被引文献23

引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部