Determination of neural-network topology for partial discharge pulse pattern recognition

A time-series approach has been employed to devise neural-network topologies for time dependent partial discharge pulse pattern recognition applications. The cascaded output neural-network structure was found to provide the highest success rate in differentiating between two different partial discharge patterns. This was accomplished by utilizing the indexed feature of the first stage output as one of the inputs into the second stage of the cascaded neural network.

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