Power signal disturbance classification using wavelet based neural network

Autor:	Suja S., Jerome Jovitha
Jazyk:	angličtina
Rok vydání:	2007
Předmět:	discrete wavelet transform power quality disturbances learning vector quantization multi resolution analysis (mra) Electrical engineering. Electronics. Nuclear engineering TK1-9971
Zdroj:	Serbian Journal of Electrical Engineering, Vol 4, Iss 1, Pp 71-83 (2007)
Druh dokumentu:	article
ISSN:	1451-4869 2217-7183
DOI:	10.2298/SJEE0701071S
Popis:	In this paper, the power signal disturbances are detected using discrete wavelet transform (DWT) and categorized using neural networks. This paper presents a prototype of power quality disturbance recognition system. The prototype contains three main components. First a simulator is used to generate power signal disturbances. The second component is a detector which uses the technique of DWT to detect the power signal disturbances. DWT is used to extract disturbance features in the power signal. These coefficients obtained from DWT are further subjected to statistical manipulations for increasing the detection accuracy. The third component is neural network architecture to classify the power signal disturbances with increased accuracy of detection.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/797f4fafdf3f4b8c8a9495fe499996fc Zobrazit plný text záznamu View record in DOAJ