Banca de QUALIFICAÇÃO: ANDERSON EGBERTO CAVALCANTE SALLES

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : ANDERSON EGBERTO CAVALCANTE SALLES
DATE: 22/01/2021
TIME: 13:30
LOCAL: meet.google.com/xwj-xmeq-cpq
TITLE:

Diagnosis of internal faults in SCIG using neural networks in FPGA.


KEY WORDS:

Internal faults, SCIG, Artificial Neural Networks, FPGA.


PAGES: 39
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Sistemas de Computação
SPECIALTY: Hardware
SUMMARY:

The objective of this work is to implement a model for detecting internal faults in wind turbines based on the cage rotor induction machine. For this purpose, it is proposed to implement a machine learning model, embedded in an FPGA, that learns from the data and captures the characteristics of the electrical signatures of the faults.
The main focus is on developing the learning model and using software aimed at high-level synthesis to embark the model on an FPGA.


BANKING MEMBERS:
Presidente - 1694485 - MARCIO EDUARDO KREUTZ
Interna - 1350250 - ANNE MAGALY DE PAULA CANUTO
Interna - 1882699 - MONICA MAGALHAES PEREIRA
Externo ao Programa - 2885532 - IVANOVITCH MEDEIROS DANTAS DA SILVA
Externo à Instituição - LUCIANO SALES BARROS - UFPB
Notícia cadastrada em: 14/01/2021 08:43
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