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 ›› 2025, Vol. 44 ›› Issue (10): 1579-1584.

• • 上一篇    

家庭用电负载下故障电弧断路器性能评价技术研究

陈斌1, 马楠2, 马俊铭3, 陈钦佩4   

  1. （1.深圳消防救援支队，广东 深圳 518000； 2.深圳供电局有限公司，广东 深圳 518000； 3.广东工业大学 环境科学与工程学院，广东 广州 510006； 4.应急管理部天津消防研究所，天津 300381）
  • 收稿日期:2024-08-09 修回日期:2025-01-02 出版日期:2025-10-15 发布日期:2025-10-15
  • 作者简介:陈 斌，深圳市消防救援支队高级工程师，中国科学技术大学在读博士研究生，主要从事建筑防火、电气火灾安全研究工作，广东省深圳市红荔路2009号，518000，chenbin3@mail.ustc.edu.cn。
  • 基金资助:
    深圳消防救援局科研项目（23HK0761）；国家自然科学基金面上项目（52276108）

Research on performance evaluation technology of arc fault detection devices under residential electrical characteristic loads

Chen Bin1, Ma Nan2, Ma Junming3, Chen Qinpei4   

  1. (1. Shenzhen Fire and Rescue Division, Shenzhen Guangdong 518000, China; 2. Shenzhen Power Supply Bureau Co., Ltd., Shenzhen Guangdong 518000, China; 3. School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou Guangdong 510006, China; 4. Tianjin Fire Science and Technology Research Institute of MEM, Tianjin 300381, China)
  • Received:2024-08-09 Revised:2025-01-02 Online:2025-10-15 Published:2025-10-15

摘要： 电弧故障引发的电气火灾事故时有发生。本文对比分析市面上电弧故障保护装置的检测算法，选取典型家庭用电特征负载，并建立故障电弧断路器性能量化评价体系，通过创新性地引入并量化分断时间变异系数、分断时间快慢和误脱扣次数3个关键性能指标，基于熵权法进行权重分配，提出了一种基于性能量化的评价方法。以基于傅里叶变换检测方法、小波变换检测方法以及结合人工神经网络检测算法的故障电弧断路器为实例验证，并依据国家标准GB/T 31143-2014及本文的性能量化评价方法进行测试。验证结果筛选出对特定家用特征负载发生失效的故障电弧断路器，表明本文提出的性能量化评价体系能够有效衡量故障电弧断路器在典型家庭用电特征负载下的性能，为家庭用户的实际用电场景提供指导。

关键词: 故障电弧断路器, 性能量化评价体系, 电气火灾

Abstract: Electrical fires caused by arc faults are a frequent occurrence. This paper presents a comparative analysis of detection algorithms of Arc Fault Detection Devices (AFDDs) available on the market. The typical household electrical characteristic loads are selected, and an evaluation system for AFDD performance is established. Three key performance indicators—coefficient of variation of breaking time, breaking time speed, and the number of false trippings—are introduced and quantified. The entropy method is applied for weight allocation to develop a performance-based quantitative assessment method. The evaluation is validated with AFDD based on Fourier transform detection method, wavelet transform detection method and artificial neural network detection algorithm. The testing and analysis are conducted in accordance with the national standard GB/T 31143-2014 as well as the performance quantification evaluation method proposed in this paper. The verification results have identified AFDDs that fail under specific residential characteristic loads, demonstrating that the performance quantification evaluation system proposed in this paper can effectively measure the performance of AFDDs under typical residential electrical characteristic loads, offering valuable insights for real-world electricity usage scenarios in households.

Key words: arc fault detection devices, performance quantification assessment system, electrical fire