作者:
KM Silva，Souza， B.A.，NSD Brito
关键词:
fault diagnosis ； neural nets ； power engineering computing ； power supply quality ； power transmission faults ； wavelet transforms ； ANN ； Brazilian utility company ； artificial neural network ； fault classification
摘要:
This paper proposes a novel method for transmission-line fault detection and classification using oscillographic data. The fault detection and its clearing time are determined based on a set of rules obtained from the current waveform analysis in time and wavelet domains. The method is able to single out faults from other power-quality disturbances, such as voltage sags and oscillatory transients, which are common in power systems operation. An artificial neural network classifies the fault from the voltage and current waveforms pattern recognition in the time domain. The method has been used for fault detection and classification from real oscillographic data of a Brazilian utility company with excellent results
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