Fault location in transmission line using hybrid neural network

被引:4
作者
Osowski, S [1 ]
Salat, R [1 ]
机构
[1] Warsaw Univ Technol, Warsaw, Poland
关键词
fault analysis; neural networks; transmission lines;
D O I
10.1108/03321640210410715
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The paper presents the application of self-organizing neural network for the location of the fault in the transmission line and estimation of the Parameter of the faulty element. The location of fault is done on the basis of the measurement of some node voltages of the line and appropriate Preprocessing it to enhance the differences between different faults. The hybrid neural network is used to solve the problem. The self-organizing layer of this network is used as the classifier. The output postprocessing MLP structure realizes the association of the place of the fault and its parameter with the measured set of node voltages. The results of computer experiments are given in the paper and discussed.
引用
收藏
页码:18 / 30
页数:13
相关论文
共 13 条
  • [1] [Anonymous], 1991, TESTING DIAGNOSIS AN
  • [2] [Anonymous], 1988, SELF ORG ASS MEMORY
  • [3] BANDLER JW, 1984, P IEEE INT S CAS MON
  • [4] On-line fault detection and diagnosis obtained by implementing neural algorithms on a digital signal processor
    Bernieri, A
    Betta, G
    Liguori, C
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 1996, 45 (05) : 894 - 899
  • [5] DUHAMEL P, 1979, IEEE T CAS, V26
  • [6] GHAUSI MS, 1968, INTRO DISTRIBUTED PA
  • [7] Haykin S., 1994, NEURAL NETWORKS COMP
  • [8] NEURAL-GAS NETWORK FOR VECTOR QUANTIZATION AND ITS APPLICATION TO TIME-SERIES PREDICTION
    MARTINETZ, TM
    BERKOVICH, SG
    SCHULTEN, KJ
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1993, 4 (04): : 558 - 569
  • [9] Fast second order learning algorithm for feedforward multilayer neural networks and its applications
    Osowski, S
    Bojarczak, P
    Stodolski, M
    [J]. NEURAL NETWORKS, 1996, 9 (09) : 1583 - 1596
  • [10] POETL A, 1999, IEEE T POWER DELIVER, V14, P1269