DONG Li. Fault Recognition of Single-phase Reclosing Based on Fuzzy Neural Network[J]. Industry and Mine Automation, 2009, 35(8): 49-51.
Citation: DONG Li. Fault Recognition of Single-phase Reclosing Based on Fuzzy Neural Network[J]. Industry and Mine Automation, 2009, 35(8): 49-51.

Fault Recognition of Single-phase Reclosing Based on Fuzzy Neural Network

  • Publish Date: 2009-08-10
  • Auto-reclosing is a very important equipment that can improve reliability of power supply system and guarantee security operation of power line,so the auto-reclosing is widely applied in transmission line.In allussion to the misjudgment of voltage criterion of auto-reclosing,the paper put forward a method of fault recognition which applied fuzzy neural network(FNN) to recognize the faults of single phase auto-reclosing.It built up a model of fuzzy neural network with two-input and one-output,which was used to recognize transient faults and permanent faults.Using the method of gaining fuzzy rules from samples and Matlab software,it simulated the method.The simulation result verified the feasibility and accuracy of the proposed method.

     

  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (22) PDF downloads(3) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return