Scholarlink

In the test of Arc Fault Detection Device,, the characteristics of series fault arc are not obvious and there is noise interference. In this paper, the LIF model in spiking neural networks and Markov conversion field are used to detect the fault arc, process and analyze the current signal, improve the detection accuracy and reliability, and the identification accuracy rate is 98.13%, which provides a new idea for detection and is expected to be used in electrical safety.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Arc Fault Identification Technology Based on SNN and MTF Codes

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Chen Zukuai,
  • Li Jing,
  • Shen Yuwen,
  • Jiang Song

摘要

In the test of Arc Fault Detection Device,, the characteristics of series fault arc are not obvious and there is noise interference. In this paper, the LIF model in spiking neural networks and Markov conversion field are used to detect the fault arc, process and analyze the current signal, improve the detection accuracy and reliability, and the identification accuracy rate is 98.13%, which provides a new idea for detection and is expected to be used in electrical safety.