Fault location in transmission line using self-organizing neural network

R. Salat , Stanisław Osowski

Abstract

The paper presents the application of self-organizing neural network for the location of the fault in 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 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 fault and its parameter with the measured set of node voltages. The results of computer experiments are given in the paper and discussed
Author R. Salat
R. Salat,,
-
, Stanisław Osowski (FoEE / ITEEMIS)
Stanisław Osowski,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
Pages1585-1588 vol.3
Book 5th International Conference on Signal Processing Proceedings, 2000. WCCC-ICSP 2000, vol. 3, 2000
Keywords in EnglishCircuit faults, Distributed parameter circuits, Electrical resistance measurement, fault location, hybrid neural network, impedance, Intelligent networks, multilayer perceptron, multilayer perceptrons, neural networks, node voltage measurement, output postprocessing MLP structure, parameter estimation, pattern classification, power engineering computing, preprocessing, self-organising feature maps, self-organizing layer, self-organizing neural network, transmission line, Transmission line measurements, transmission lines, transmission line theory, Voltage
DOIDOI:10.1109/ICOSP.2000.893403
Score (nominal)0
Publication indicators WoS Citations = 2; GS Citations = 4.0
Citation count*4 (2013-01-30)
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