摘要
电气设备状态远程监测是当前的研究热点,针对当前电气设备状态远程监测误差大,消耗时间长等不足,为了获得理想的电气设备状态远程监测结果,文中提出基于无线网络的电气设备状态远程监测系统。该系统通过无线传感器网络远程采集电气设备状态信号,并对信号进行去噪处理,然后从电气设备状态信号中提取特征,并引入机器学习算法对特征与电气设备状态之间的联系进行拟合,建立电气设备状态监测模型,从而得到电气设备状态结果。最后通过互联网将电气设备状态监测结果发送给管理人员,并对电气设备状态远程监测系统进行仿真测试。结果表明,所提系统利用无线网络的优势,可以对电气设备状态进行高精度的远程监测,同时缩短了电气设备状态远程监测时间,具有十分明显的优越性。
Remote monitoring of electrical equipment status is the current research hotspot.In view of the shortcomings of large error and long consumption time of remote monitoring of current electrical equipment status,a electrical equipments′remote status monitoring system based on wireless network is proposed to obtain the ideal remote monitoring results of electrical equipment status.The system can collect the status signal of electrical equipment remotely through wireless network,and denoise the signal.And then the features are extracted from the status signal of electrical equipments,and machine learning algorithm is introduced to fit the relationship between the features and the status of electrical equipments to establish the status monitoring model of electrical equipments,so as to obtain the status results of electrical equipments.Finally,the monitoring results of electrical equipment status are sent to the management personnel through wireless network.The remote monitoring system of electrical equipment status was simulated and tested.The results show that the system can make use of the advantages of wireless network to conduct high⁃precision remote monitoring of electrical equipment status,and shorten the time of remote monitoring of electrical equipment status.
作者
王岚
WANG Lan(Bearing Roller Factory,Luoyang LYC Bearing Co.,Ltd,Luoyang 471039,China)
出处
《现代电子技术》
2021年第18期22-26,共5页
Modern Electronics Technique
关键词
电气设备
远程监测
无线网络
信号采集
特征提取
监测模型
信号去噪
electrical equipment
remote monitoring
wireless network
acquisition
feature extraction
monitoring model
signal denoising
