DocumentCode :
3535095
Title :
Classification of power quality disturbances using S-transform and Artificial Neural Networks
Author :
Rodriguez, A. ; Ruiz, J.E. ; Aguado, J. ; Lopez, J.J. ; Martin, F.I. ; Muñoz, F.
Author_Institution :
Electr. Eng. Dept., Univ. of Malaga, Malaga, Spain
fYear :
2011
fDate :
11-13 May 2011
Firstpage :
1
Lastpage :
6
Abstract :
An automated classification based on S-transform as feature extraction tool and Artificial Neural Network as algorithm classifier is presented. The signals generated according to mathematical models have been used to obtain experimental results in two stages, first, with a data set with only simple disturbances and, later, including complex disturbances, more usual in real electrical systems. In both cases noise is added to the signals from 40dB to 20dB. At last, a data set with several disturbances, simple and complex, has been generated by simulation software based on electrical models, to test the implemented system. Evaluation results verifying the accuracy of the proposed method are presented.
Keywords :
feature extraction; neural nets; power engineering computing; power supply quality; transforms; S-transform; artificial neural networks; electrical systems; feature extraction tool; mathematical models; power quality disturbances; simulation software; Artificial neural networks; Feature extraction; Harmonic analysis; Power quality; Time frequency analysis; Transient analysis; Voltage fluctuations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering, Energy and Electrical Drives (POWERENG), 2011 International Conference on
Conference_Location :
Malaga
ISSN :
2155-5516
Print_ISBN :
978-1-4244-9845-1
Electronic_ISBN :
2155-5516
Type :
conf
DOI :
10.1109/PowerEng.2011.6036517
Filename :
6036517
Link To Document :
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