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Through the above processing and settings, the entire network can be trained to a suitable state on the training set, and feature extraction and classification recognition can be realized. There are four types of partial discharge to recognize, oil gap defect, floating defect, tip defect and surface defect. For each type, 200 samples are sampled to form the training set, and 50 samples are sampled to form the test set. Therefore, the total training set has 800 samples and the test set has 200 samples. Network training is carried out through the training set, and the results are verified on the test set.
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IEEE/ICACT20220141 Slide.13
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