@inproceedings{56f652ef98a54878ba6d6291daf84537,
title = "A simulated power quality disturbance recognition system",
abstract = "The paper presents a prototype of power quality disturbance recognition system. The prototype contains two main components: a simulator to generate power quality disturbances and a classifier to identify these disturbances. Based on the results of site measurements, the disturbance generator is designed to simulate different power quality disturbances frequently encountered at power system sub-stations. The proposed classifier, based on the techniques of neural networks and fuzzy associative memory, is designed to evaluate the decision boundaries separating patterns to be classified. In addition, the sampled waveforms, before being fed to the classifier, are pre-processed by using digital wavelet transform so as to extract disturbance features in the concerned sub-bands.",
keywords = "Fuzzy associative memory, Learning vector quantization, Pattern recognition, Power quality disturbances, Wavelet transform",
author = "Jiansheng Huang",
year = "2003",
language = "English",
isbn = "1932415122",
series = "Proceedings of the International Conference on Artificial Intelligence IC-AI 2003",
publisher = "CSREA Press",
pages = "525--531",
editor = "H.R. Arabnia and R. Joshua and Y. Mun",
booktitle = "Proceedings of the International Conference on Artificial Intelligence IC-AI 2003",
note = "2003 International Conference on Artificial Intelligence, IC-AI 2003 ; Conference date: 23-06-2003 Through 26-06-2003",
}