Discrimination of Tree Inception using Partial Discharge Pattern Recognitions with Neural Network

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  • ニューラルネットワークによる部分放電パターン認識を利用したトリー発生の判別
  • ニューラル ネットワーク ニ ヨル ブブン ホウデン パターン ニンシキ オ

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The Neural network algorithm was adopted to the discrimination of the partial discharge patterns before and after the tree initiation from a needle-shaped void. Phase (φ), discharge amount (q) and discharge frequency (n) were measured for all discharge pulses in the partial discharge measurement period. φ-qand φ-q-n patterns before and after the tree initiation were learmed by neural network, using the back-propagation method. The network which learned φ-q-n patterns showed a good discrimination performance than that leaned φ-q patterns. The discrimination performance decreased when the input pattern was taken from the non-experienced sample. Stable discrimination was possible when the tree length exceeded the void length.

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