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Master's Dissertation
DOI
10.11606/D.76.1998.tde-16092008-103645
Document
Author
Full name
Samuel Corrêa Bueno
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 1998
Supervisor
Committee
Roda, Valentin Obac (President)
Catalano, Fernando Martini
Tannus, Alberto
Title in Portuguese
Utilização de processamento de imagens em aplicações da aerodinâmica
Keywords in Portuguese
Aerodinâmica
Processamento de imagens
Redes neurais artificiais
Stall dinâmico
Abstract in Portuguese
Neste trabalho apresentamos o desenvolvimento e a realização de um experimento utilizando recursos modernos de processamento de imagens como câmeras CCD, placas de aquisição de imagens e linguagem de programação visual com interface multimídia para observação do fenômeno do Estol dinâmico que tem grande importância do estudo de estabilidade de aeronaves. O fenômeno de Estol ocorre nos aerofólios de aeronaves como nos rotores de helicópteros e asas de aeronaves acrobáticas. Nosso sistema e capaz de detectar dentro de um experimento de um aerofólio oscilando em baixas freqüências a Histerese de sustentação que ocorre neste. Utilizamos também na nossa abordagem redes neurais backpropagation para acomodação dos dados experimentais. Implementamos e descrevemos um hardware mecânico para obtenção de melhores imagens e as funções escritas em Visual Basic que foram utilizadas, com o objetivo de permitir a reprodução do experimento em outros centros de pesquisa.
Title in English
Utilization of images processing in aerodynamics application
Keywords in English
Aerodynamics
Artificial neural networks
Dynamics Stall
Images processing
Abstract in English
In this work we present an experiment using modern imaging processing techniques such as CCD cameras, video acquisition boards and visual programming using multimedia interfacing for the observation of the Stall phenomena which has great importance in the airplane stability. The Stall phenomena occurs in arplaine (airfoils) such as in helicopter blades and acrobatic airplane wings. We demonstrated that the developed system is able to detect the lift histeresis in a low frequency oscillating bidimensional airfoil. We also used in our approach backpropagation neural network for the experimental data accomodation. In order to allow replication of the experiment by other institutions, we present a detailed description of the mechanical setup used to obtain the best possible images and of the Visual Basic functions.
 
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SamuelBuenoM.pdf (21.10 Mbytes)
Publishing Date
2008-09-17
 
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