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Doctoral Thesis
DOI
https://doi.org/10.11606/T.3.2008.tde-09022009-181024
Document
Author
Full name
Marcos Rogério Cândido
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2008
Supervisor
Committee
Zanetta Júnior, Luiz Cera (President)
Baccalá, Luiz Antonio
Coury, Denis Vinícius
Moreira, Fernando Augusto
Pereira, Carlos Eduardo de Morais
Title in Portuguese
Aplicação da transformada Wavelet na análise da qualidade de energia em fornos elétricos a arco.
Keywords in Portuguese
Análise de ondaletas-wavelets (análise de séries temporais)
Energia (qualidade)
Forno elétrico
Abstract in Portuguese
Neste trabalho, desenvolveu-se um novo método para a detecção e classificação dos distúrbios que afetam a qualidade de energia elétrica em sistemas elétricos industriais na presença de fornos elétricos a arco. Durante o processo de fusão dos fornos elétricos a arco, ocorrem diversos eventos que afetam o sistema elétrico ao qual estão inseridos, tendo como características: forma de onda do sinal de corrente altamente desequilibradas e com grande distorção devido aos harmônicos, efeitos de cintilação; bem como afundamento e elevação nos sinais de tensão. O método ora proposto foi aplicado a sinais reais, permitindo a detecção e classificação dos distúrbios múltiplos na forma de onda do sinal de tensão, proveniente da operação dos fornos elétricos a arco. Para tal, foi usada como base do algoritmo, uma técnica baseada na Transformada Wavelet, aplicada aos sinais não-estacionários de uma instalação industrial com três fornos elétricos a arco.
Title in English
Application of wavelet transform for power quality analysis in electric arc furnace.
Keywords in English
Electric arc furnace
Multiple disturbances
Power quality
Wavelet
Abstract in English
A new method for the detection and classification of the disturbances that affect the electric power quality in industrial electric systems with electric arc furnaces was developed in this work. During the fusion process of the electric arc furnaces, may occur several events that affect the electric system to which it is inserted may occur, having as characteristic: waveform of the signal of current highly unbalanced and with great distortion due to the harmonic, scintillation effects; as well as sag and swell in the voltage signals.The method proposed was applied to real signals, allowing the detection and classification of the multiple disturbances in the waveform of the voltage signal originating from the operation of the electric arc furnace. For this purpose, a technique based on Wavelet Transform will be used and applied to the not-stationary signals of an industrial installation with three electric arc furnaces.
 
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Publishing Date
2009-08-13
 
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