Partial Discharge Pattern Recognition Using Fuzzy-Neural Networks (FNNs) Algorithm

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.