Fault diagnosis for power systems based on neural networks
Wang Sheng Fang · 2011
Neurocomputing is one of fastest growing areas of research in the fields of Artificial Intelligence and Pattern Recognition. Real time Fault Detection and Diagnosis (FDD) is an important area of research interest in Knowledge Based Expert Systems. This paper explores the suitability of pattern classification approach of neural networks for fault detection and diagnosis. Suitability of using neural network as pattern classifiers for power system fault diagnosis is described in detail. An Analysis of the learning, recall and generalization charecterstisc of the neural network diagnostic system is presented and discussed in detail. A neural network design and simulation environment for real-time FDD is presented.