Comparison of the performance of artificial neural networks and fuzzy logic for recognizing different partial discharge sources

@inproceedings{Masud2017ComparisonOT,
  title={Comparison of the performance of artificial neural networks and fuzzy logic for recognizing different partial discharge sources},
  author={Abdullahi Abubakar Mas’ud and Jorge Alfredo Ardila-Rey and Ricardo Albarrac{\'i}n and Firdaus Muhammad-Sukki and Nurul Aini Bani},
  year={2017}
}
This paper compared the capabilities of the artificial neural network (ANN) and the fuzzy logic (FL) approaches for recognizing and discriminating partial discharge (PD) fault classes. The training and testing parameters for the ANN and FL comprise statistical fingerprints from different phase-amplitude-number (φ-q-n) measurements. Two PD fault classes considered are internal discharges in voids and surface discharges. In the void class, there are single voids, serial voids and parallel voids… CONTINUE READING