Fault Diagnosis of Metro Traction Power Systems Using A Modified Fuzzy Reasoning Spiking Neural P System
This paper presents the application of a modified fuzzy reasoning spiking neural P systems (MFRSN P system, for short) to fault diagnosis of metro traction power supply systems. In MFRSN P systems, three types of neurons are used to represent operation information of protection devices including pro...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/107804 |
| Acceso en línea: | https://hdl.handle.net/11441/107804 |
| Access Level: | acceso abierto |
| Palabra clave: | Membrane Computing Probabilistic fuzzy reasoning spiking neural P system Metro traction power supply system Fault diagnosis |
| Sumario: | This paper presents the application of a modified fuzzy reasoning spiking neural P systems (MFRSN P system, for short) to fault diagnosis of metro traction power supply systems. In MFRSN P systems, three types of neurons are used to represent operation information of protection devices including protective relays and circuit breakers; a reasoning algorithm associated with MFRSN P systems is introduced to fulfill fault reasoning; fault diagnosis rules for metro traction power supply systems and their MFRSN P systems are described. Case studies show the feasibility and effectiveness of the presented method. |
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