A New Scheme for Fault Detection and Classification Applied to DC Motor
This study presents an approach for fault detection and classification in a DC drive system. The fault is detected by a classical Luenberger observer. After the fault detection, the fault classification is started. The fault classification, the main contribution of this paper, is based on a represen...
| Principais autores: | , , , , , |
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| Formato: | Artigo |
| Idioma: | English |
| Publicado em: |
Sociedade Brasileira de Matemática Aplicada e Computacional
2018-09-01
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| coleção: | Trends in Computational and Applied Mathematics |
| Acesso em linha: | https://tcam.sbmac.org.br/tema/article/view/1155 |
| Resumo: | This study presents an approach for fault detection and classification in a DC drive system. The fault is detected by a classical Luenberger observer. After the fault detection, the fault classification is started. The fault classification, the main contribution of this paper, is based on a representation which combines the Subctrative Clustering algorithm with an adaptation of Particle Swarm Clustering. |
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| ISSN: | 2676-0029 |