Artículo
Fault Diagnosis of Metro Traction Power Systems Using A Modified Fuzzy Reasoning Spiking Neural P System
Autor/es | He, Yangyang
Wang, Tao Huang, Kang Zhang, Gexiang Pérez Jiménez, Mario de Jesús |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2015 |
Fecha de depósito | 2021-04-26 |
Publicado en |
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Resumen | 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 ... 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. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España |
Identificador del proyecto | TIN2012-37434 |
Cita | He, Y., Wang, T., Huang, K., Zhang, G. y Pérez Jiménez, M.d.J. (2015). Fault Diagnosis of Metro Traction Power Systems Using A Modified Fuzzy Reasoning Spiking Neural P System. Romanian Journal of Information Science and Technology (ROMJIST), 18 (3), 256-272. |
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