133 / 2023-10-19 11:24:49
Research on Digital Diagnosis of Switchgear Based on Integration of Virtuality and Reality
switchgear,thermoelectric coupling,model dimensionality reduction,fault diagnosis,visualization
终稿
Guoqiang Su / State Grid Shandong Electric Power Research Institute
Hejin Liu / State Grid Shandong Electric Power Research Institute
Xiangyu Wen / State Grid Shandong Electric Power Research Institute
Feng Wang / State Grid Shandong Electric Power Research Institute
Yang Liu / State Grid Shandong Electric Power Research Institute
Shidong Zhang / State Grid Shandong Electric Power Research Institute
Xinbin Zuo / State Grid Shandong Electric Power Company
Switchgear, as a crucial electrical equipment for control and protection, presents a range of safety issues during its operation, significantly impacting the reliability of power supply. Existing switchgear detection methods mostly focus on the analysis of two-dimensional charts, making it challenging to provide comprehensive feedback on multi-physics field states in a three-dimensional space. Therefore, this paper employs a multi-physics coupled finite element model to investigate the temperature and electric field distribution during the operational status of switchgear. It establishes a switchgear proxy model based on Radial Basis Function (RBF) neural networks by combining simulation with engineering practices. Furthermore, it investigates switchgear discharge faults and fault diagnosis algorithms based on parallel Adaptive Neuro-Fuzzy Inference Systems (ANFIS) neural networks, and subsequently achieves the visualization of switchgear status information through Unity. This research enhances the accuracy and real-time monitoring of switchgear data, realizes the data visualization of switchgear status, and offers insights for proactive switchgear maintenance.
重要日期
  • 会议日期

    12月08日

    2023

    12月10日

    2023

  • 11月01日 2023

    初稿截稿日期

  • 12月10日 2023

    注册截止日期

主办单位
IEEE IAS
承办单位
Southwest Jiaotong University (SWJTU)
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