摘要
传统装表接电电能计量故障检测方法存在检测精度低、故障类型检测能力不足的问题。对此,提出基于物联网和大数据分析的故障检测方法。利用物联网技术,安装传感器实时采集设备运行数据;基于大数据分析技术,处理采集到的海量数据,提取电能计量故障特征并建立故障检测模型,实现故障检测。实验结果表明,所提方法的故障检测精度较高,能够准确地检测出所有故障类型,检测出的故障点数量与实际数量完全一致。
The traditional methods for detecting faults in energy metering during meter installation and connection have problems such as low detection accuracy and insufficient ability to detect fault types.In this regard,a fault detection method based on the Internet of Things and big data analysis is proposed.By using Internet of Things technology,sensors are installed to collect real-time data on the operation of equipment.Based on big data analysis technology,the massive data collected is processed to extract the fault features of electric energy metering and establish a fault detection model,thereby achieving fault detection.The experimental results show that the proposed method has a high fault detection accuracy,can accurately detect all types of faults,and the number of detected fault points is completely consistent with the actual number.
作者
刘翔
LIU Xiang(Power Supply and Distribution Service Branch,Jinhua Power Transmission and Distribution Engineering Co.,Ltd.,Jinhua,Zhejiang 321000,China)
出处
《智能物联技术》
2025年第4期78-81,共4页
Technology of Io T& AI
关键词
物联网
大数据分析
装表接电
电能
计量
故障检测
Internet of Things
big data analysis
metering and connecting electricity
electric energy
measurement
fault detection
