98 / 2024-04-12 09:47:50
Intelligent Breakdown Diagnosis System for Vacuum Interrupter in Conditioning Based on Zynq SoC and Deep Learning
breakdown diagnosis, vacuum interrupter, Zynq, deep learning, conditioning
摘要录用
Xu Xunchen / Nanjing University of Aeronautics and Astronautics
Shimin LI / Nanjing University of Aeronautics and Astronautics
Chaohai Zhang / Nanjing University of Aeronautics and Astronautics
Breakdown diagnosis in conditioning had a great significance for vacuum interrupter (VI) insulation improvement. This paper proposed an intelligent breakdown diagnosis system in conditioning based on Zynq System-on-Chip (SoC) and deep learning to diagnose breakdown accurately and efficiently. The deep learning model was constructed and trained on PC to diagnose breakdown through pre-breakdown current waveforms, and the weights parameters of deep learning model for breakdown diagnosis were acquired. The intelligent breakdown diagnosis system was implemented on Zynq SoC with acquired weights parameters through software-hardware co-design. It integrated the image capture module and breakdown mechanism classification module, which could diagnose breakdown automatically without manual operation and extern PC devices. The results indicated that the real-time breakdown mechanism could be obtained accurately and efficiently with the intelligent breakdown diagnosis system, whose accuracy was higher than 85%. The intelligent breakdown diagnosis system could have a promising application in engineering for VI insulation improvement.

 
重要日期
  • 会议日期

    11月10日

    2024

    11月13日

    2024

  • 11月11日 2024

    初稿截稿日期

  • 11月19日 2024

    注册截止日期

主办单位
Xi’an Jiaotong Universit
历届会议
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询