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Classification of power quality disturbance with neural pattern recognition technique [articol]

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dc.contributor.author Zamrooth, D.
dc.contributor.author Babulal, C.K.
dc.date.accessioned 2024-10-02T10:33:56Z
dc.date.available 2024-10-02T10:33:56Z
dc.date.issued 2019
dc.identifier.citation Zamrooth, D.; Babulal, C.K.: Classification of power quality disturbance with neural pattern recognition technique. Timişoara: Editura Politehnica, 2019. en_US
dc.identifier.issn 1582-4594
dc.identifier.uri https://dspace.upt.ro/xmlui/handle/123456789/6699
dc.description.abstract The proposed work presents a novel approach using Discrete Wavelet Transform (DWT) and Neural Pattern Recognition (NPR) technique for the detection and classification of the Power Quality (PD) disturbances. Various PQ related events were simulated including single and combined events and the generated signals were treated with DWT for feature extraction. For classification purpose the signal parameters were trained with Neural Pattern Recognition (NPR) tool. Eleven types of PQ disturbances were considered for classification. The simulation results depicted that the combined process of DWT and NPR can effectively detect and classify different PQ disturbances effectively. Compared to the conventional methods available on the literature this method needs less computations and works faster. en_US
dc.language.iso en en_US
dc.publisher Timișoara : Editura Politehnica en_US
dc.relation.ispartofseries Journal of Electrical Engineering;Vol 19 No 5
dc.subject Power Quality en_US
dc.subject Discrete Wavelet Transforms en_US
dc.subject Neural Pattern Recognition Technique en_US
dc.subject Confusion Matrix en_US
dc.title Classification of power quality disturbance with neural pattern recognition technique [articol] en_US
dc.type Article en_US


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