METHOD FOR AUGMENTATION PARTIAL DISCHARGE DATA USING GENERATIVE ADVERSARIAL NETWORK

摘要

The method for augmenting power facility partial discharge data using a hostile generation network according to the present invention comprises the steps of: (a) determining whether a partial discharge exists while a determination network collects actual partial discharge data and continuously updates the model through learning; and (b) generating partial discharge image data arbitrarily by the generation network and requesting the determination network, and then utilizing partial discharge data having a similarity set with actual partial discharge data as enhanced partial discharge data; It has the effect of generating a large amount of augmented partial discharge data with high similarity by learning the discharge data through a Generative Adversarial Network (GAN).