Classificação de distúrbios na rede elétrica usando redes neurais e wavelets
Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances - providi...
Na minha lista:
| Autor principal: | |
|---|---|
| Outros Autores: | |
| Formato: | doctoralThesis |
| Idioma: | por |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
|
| Assuntos: | |
| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/15119 |
| Tags: |
Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
|
| Resumo: | Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in systems, looking
for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances - providing an automatic assessment
- techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbance s occurrences in the network. This work presents a methodology based on the Discrete Wavelet Transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution
levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks |
|---|