主管：中华人民共和国应急管理部
主办：应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU
消防科学与技术

消防科学与技术 ›› 2026, Vol. 45 ›› Issue (2): 25-30.

• • 上一篇    下一篇

不同电气故障模式下智能电能表数据的研究分析

王玉领1,2,3, 央金拉姆4, 杜瑞5, 李树超1,2,3, 曹芮晗6   

  1. （1.应急管理部天津消防研究所，天津 300382； 2.工业与公共建筑火灾防控技术应急管理部重点实验室，天津 300381； 3.天津市消防安全技术重点实验室，天津 300381； 4.拉萨市消防救援支队，西藏 拉萨 850030； 5.长白山消防救援支队，吉林 长白山 134499； 6.中国农业大学 动物医学院，北京 100093）
  • 收稿日期:2024-12-04 修回日期:2025-04-09 出版日期:2026-02-11 发布日期:2026-02-15
  • 作者简介:王玉领，应急管理部天津消防研究所助理研究员，硕士，主要从事火灾调查和火灾视频分析等研究，天津市西青区富兴路2号，300382，wangyuling@tfri.com.cn。
  • 基金资助:
    国家重点研发计划项目（2022YFC3006303）；应急管理部天津消防研究所基科费项目（2025SJ22）

Research and analysis of intelligent energy meter data under different electrical fault modes

Wang Yuling1,2,3, Yangjin Lamu4, Du Rui5, Li Shuchao1,2,3, Cao Ruihan6   

  1. (1. Tianjin Fire Science and Technology Research Institute of MEM, Tianjin 300382, China; 2. Key laboratory of Fire Protection Technology for Industry and Public Building, Ministry of Emergency Management, Tianjin 300381, China; 3. Tianjin Key Laboratory of Fire Safety Technology, Tianjin 300381, China; 4. Lhasa Fire and Rescue Division, Lhasa Xizang 850030, China; 5. Changbai Mountain Fire and Rescue Division, Changbai Mountain Jilin 134499, China; 6. College of Veterinary Medicine, China Agricultural University, Beijing 100093, China)
  • Received:2024-12-04 Revised:2025-04-09 Online:2026-02-11 Published:2026-02-15

摘要： 为准确分析电气火灾的发生发展过程，深入调查火灾原因，设计并搭建了故障模拟试验平台，通过模拟6种电气故障模式，分析线路发生故障时智能电能表采集的负荷数据和事件记录的变化情况，研究电气参数变化与不同电气故障之间的相关规律。结果表明：通过提取分析智能电能表采集的负荷数据和事件记录，能够推断出火灾现场电气设备的使用情况、电气故障发生的时间轴、故障类型等，结合调查询问、现场痕迹、技术鉴定及模拟试验，可溯源电气火灾发生发展的完整过程，为电气火灾的原因调查提供有力的数据支撑。

关键词: 火灾调查, 电气故障, 智能电能表, 事件记录

Abstract: In order to accurately analyze the occurrence and development process of electrical fires, investigate the causes of fires in depth, design and build a fault simulation experimental platform, the load data and event record changes collected by intelligent energy meters during line faults were analyzed by simulating 6 electrical fault modes. The relevant laws between changes in electrical parameters and different electrical faults were studied. The results show that by extracting and analyzing the load data and event records collected by smart energy meters, it is possible to infer the type of electrical equipment usage, time axis and electrical faults at the fire scene. Combined with investigation and inquiry, on-site traces, technical identification, and simulation experiments, the complete process of the occurrence and development of electrical fires can be traced, providing strong data support for the investigation of the causes of electrical fires.

Key words: fire investigation, electrical malfunction, intelligent energy meters, event record