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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jeong-Tae Kim Won Choi Sung-Kwun Oh Keon-Jun Park Grzybowski, S. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Electr. Eng., Daejin Univ., Pocheon (Jeong-Tae Kim; Won Choi) || Dept. of Electr. Eng., Univ. of Suwon, Suwon (Sung-Kwun Oh; Keon-Jun Park; Grzybowski, S.) |
| Abstract | In order to develop reliable on-site partial discharge (PD) pattern recognition algorithm, the fuzzy set-based fuzzy neural network (FNN) was investigated and designed. Using PD data measured from laboratory defect models, this algorithm was designed and tested. Considering the on-site situation where it is not easy to obtain voltage phases in PRPDA (phase resolved partial discharge analysis), the measured PD data were artificially changed with shifted voltage phases for the test of the proposed algorithm. The result of the proposed FNN algorithm was compared with that of conventional BP-NN (back propagation neural networks) algorithm using same data. The FNN algorithm proposed in this study was appeared to have better performance than BP-NN algorithm. |
| Starting Page | 272 |
| Ending Page | 275 |
| File Size | 332133 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424415342 |
| DOI | 10.1109/IPMC.2008.4743634 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-27 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Partial discharges Algorithm design and analysis Phase measurement Laboratories PRPDA Pattern recognition dielectric degradation Partial discharge measurement Fuzzy sets Voltage Fuzzy neural networks fuzzy neural network algorithm Testing partial discharge pattern recognition |
| Content Type | Text |
| Resource Type | Article |
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