Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference (한국전기전자재료학회:학술대회논문집)
- 2000.07a
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- Pages.645-650
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- 2000
Diagnosis of Transform Aging using Discrete Wavelet Analysis and Neural Network
이산 웨이블렛 분석과 신경망을 이용한 변압기 열화의 전단
Abstract
The discrete wavelet transform is utilized as processing of neural network(NN) to identifying aging state of internal partial discharge in transformer. The discrete wavelet transform is used to produce wavelet coefficients which are used for classification. The mean values of the wavelet coefficients are input into an back-propagation neural network. The networks, after training, can decide if the test signals is aging early state or aging last state, or normal state.
Keywords
- Acoustic Emission Signals;
- Discrete Wavelet Transform;
- Feature Extraction;
- Multi- Decomposition;
- Neural-Network