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Hybrid fault analysis system using neural networks and artificial intelligence

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2 Author(s)
Fukuyama, Y. ; Fuji Electric Corp. Res. & Dev. Ltd., Tokyo, Japan ; Ueki, Y.

The system detects the fault type and approximate fault points using information about operated relays, circuit breakers, and the fault voltage/current waveform. Faulted sections are estimated in the expert system (ES) part and fault voltage/current waveform recognition is performed in the NN part. Since power systems require high reliability, the system uses a verification procedure for the result of waveform recognition obtained by NNs, based on model-based reasoning (MBR). Four different types of NNs were examined and an appropriate NN was selected for waveform recognition. This system is a combination of NN, ES, and MBR technologies for analyzing faults, and it provides functions which cannot be obtained by conventional methods

Published in:

Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on  (Volume:4 )

Date of Conference:

3-6 May 1992

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