@article {10.3844/ajassp.2006.2049.2053,
article_type = {journal},
title = {A Novel Detection and Classification Algorithm for Power Quality Disturbances using Wavelets },
author = {Sharmeela, C. and Mohan, M. R. and Uma, G. and Baskaran, J.},
volume = {3},
year = {2006},
month = {Oct},
pages = {2049-2053},
doi = {10.3844/ajassp.2006.2049.2053},
url = {https://thescipub.com/abstract/ajassp.2006.2049.2053},
abstract = {This study presents a novel method to detect and classify power quality disturbances using wavelets. The proposed algorithm uses different wavelets each for a particular class of disturbance. The method uses wavelet filter banks in an effective way and does multiple filtering to detect the disturbances. A qualitative comparison of results shows the advantages and drawbacks of each wavelet when applied to the detection of the disturbances. This method is tested for a large class of test conditions simulated in MATLAB. Power quality monitoring together with the ability of the proposed algorithm to classify the disturbances will be a powerful tool for the power system engineers.},
journal = {American Journal of Applied Sciences},
publisher = {Science Publications}
}