Autor(es):
Foito, Daniel 
; Pires, V. Fernão ; Amaral, T. G. ; Martins, J. F.
Data: 2014
Origem: Repositório Comum
Assunto(s): Fault detection; Rectifier; Power factor correction; AC/DC conversion; Neuro-fuzzy
Detalhes do Documento
A Neuro-Fuzzy Based System for Fault Detection and Diagnosis of 3-Phase PFC Rec...
Descrição
Com o apoio RAADRI. Fault diagnosis in PFC rectifiers is becoming more and more important in many industrial applications. PFC rectifiers allow high power factor operation in AC/DC conversion. This power converter is normally the first interface between the ac power system network and the electronic equipment. In this way a good diagnosis system can avoid unplanned standstill. Under this context, this work presents a method to detect and identify the open transistor circuit fault. The developed method has two major steps. First, the input line currents are converted into a new pattern representation. Second, a neuro-fuzzy algorithm will be used to identify the fault. Several simulation and experimental results are presented to show the effectiveness of the proposed approach.
Com o apoio RAADRI. Fault diagnosis in PFC rectifiers is becoming more and more important in many industrial applications. PFC rectifiers allow high power factor operation in AC/DC conversion. This power converter is normally the first interface between the ac power system network and the electronic equipment. In this way a good diagnosis system can avoid unplanned standstill. Under this context, this work presents a method to detect and identify the open transistor circuit fault. The developed method has two major steps. First, the input line currents are converted into a new pattern representation. Second, a neuro-fuzzy algorithm will be used to identify the fault. Several simulation and experimental results are presented to show the effectiveness of the proposed approach.
Tipo de Documento
Documento de conferência
Idioma Inglês
Idioma Inglês
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