Esse trabalho compara análises modais, obtidas por dois métodos distintos, de propriedades de imagens de chamas de um forno industrial. Visto que a combustão de gases e líquidos é caracterizada pelo tipo de injeção de combustível, pela formação aleatória de vórtices e pela distribuição de reagentes, o exato sinal de excitação do sistema é, na prática, muito pouco conhecido, cabendo aos métodos de análise a identificação dos parâmetros modais sem essa informação. Para vencer este obstáculo, na presente dissertação foram utilizados o método de Ibrahim no Domínio do Tempo (ITDM) e o método Eigensystem Realization Algorithm (ERA) associados à técnica do decremento aleatório (Random Decrement - RandomDec). A técnica RandomDec permite a obtenção de um sinal proporcional ao decaimento livre do sistema, a partir de uma excitação aleatória. Essa proporcionalidade permite que os métodos no domínio do tempo citados anteriormente sejam empregados na obtenção das características de vibração do sistema. O estudo da dinâmica de chamas com base em propriedades de suas imagens é tema muito pouco abordado na literatura; por esse motivo, inicialmente foi realizado, por meio de simulações numéricas em um sistema hipotético, um completo teste de sensibilidade de todos os métodos e da técnica a serem implementados no problema real do forno industrial. Posteriormente, os dados de chamas foram utilizados para obtenção dos modos de vibrar das propriedades de imagens. Os resultados mostram que a modelagem realizada pelo ERA para sistema SIMO (single input and multiple output) fornece modos de vibrar com amortecimentos mais condizentes com a dinâmica da chama e, assim, sugerem que, em princípio, está técnica poderia ser utilizada prontamente na identificação desse tipo de sistema, sem a necessidade da realização de qualquer outra análise modal para corroborar os resultados. Além disso, a identificação de um sistema complexo como o analisado, utilizando métodos de análise modal operacional, enseja a possibilidade de pesquisas visando obter sistemas de controle baseado em imagens para plantas com características semelhantes. / In this present study, two different modal analysis methods are applied to obtain and compare models for properties of flame images captured in an industrial furnace. Since combustion of gases and liquids is characterized by the type of fuel injection, random formation of vortices and distribution of reagents, the system excitation signal isn\'t precisely known in the reality, thus the analysis methods must identify the modal parameters without this information. To overcome this obstacle, Ibrahim Time Domain Method (ITDM) and Eigensystem Realization Algorithm (ERA) associated with the Random Decrement (RandomDec) technique were implemented in this thesis. The RandomDec technique give the means to obtain a signal which is proportional to the free decay of the system when it is randomly forced. This proportional signal allows the previously mentioned analysis methods to be used to identify vibration characteristics of the system. The study of flame dynamics based on its image characteristics is barely approached in the literature; for this reason, a complete sensitivity test of all the methods and techniques to be implemented in the real problem of industrial furnaces was initially performed through numerical simulations of a hypothetical system. Afterwards, flame data was used to obtain the vibration modes of image properties. The results lead to conclude that the SIMO (single input and multiple output) model obtained by ERA has vibration modes with more consistent damping regarding flame dynamics and suggest also that this technique could be readily used in the identification of this kind of system, without the need of any other modal analysis for results corroboration. Furthermore, the utilization of operational modal analysis methods to identify a complex system such as the analyzed one may instigate researches on image-based control systems of industrial plants with suchlike characteristics.

Esse trabalho compara análises modais, obtidas por dois métodos distintos, de propriedades de imagens de chamas de um forno industrial. Visto que a combustão de gases e líquidos é caracterizada pelo tipo de injeção de combustível, pela formação aleatória de vórtices e pela distribuição de reagentes, o exato sinal de excitação do sistema é, na prática, muito pouco conhecido, cabendo aos métodos de análise a identificação dos parâmetros modais sem essa informação. Para vencer este obstáculo, na presente dissertação foram utilizados o método de Ibrahim no Domínio do Tempo (ITDM) e o método Eigensystem Realization Algorithm (ERA) associados à técnica do decremento aleatório (Random Decrement - RandomDec). A técnica RandomDec permite a obtenção de um sinal proporcional ao decaimento livre do sistema, a partir de uma excitação aleatória. Essa proporcionalidade permite que os métodos no domínio do tempo citados anteriormente sejam empregados na obtenção das características de vibração do sistema. O estudo da dinâmica de chamas com base em propriedades de suas imagens é tema muito pouco abordado na literatura; por esse motivo, inicialmente foi realizado, por meio de simulações numéricas em um sistema hipotético, um completo teste de sensibilidade de todos os métodos e da técnica a serem implementados no problema real do forno industrial. Posteriormente, os dados de chamas foram utilizados para obtenção dos modos de vibrar das propriedades de imagens. Os resultados mostram que a modelagem realizada pelo ERA para sistema SIMO (single input and multiple output) fornece modos de vibrar com amortecimentos mais condizentes com a dinâmica da chama e, assim, sugerem que, em princípio, está técnica poderia ser utilizada prontamente na identificação desse tipo de sistema, sem a necessidade da realização de qualquer outra análise modal para corroborar os resultados. Além disso, a identificação de um sistema complexo como o analisado, utilizando métodos de análise modal operacional, enseja a possibilidade de pesquisas visando obter sistemas de controle baseado em imagens para plantas com características semelhantes. / In this present study, two different modal analysis methods are applied to obtain and compare models for properties of flame images captured in an industrial furnace. Since combustion of gases and liquids is characterized by the type of fuel injection, random formation of vortices and distribution of reagents, the system excitation signal isn\'t precisely known in the reality, thus the analysis methods must identify the modal parameters without this information. To overcome this obstacle, Ibrahim Time Domain Method (ITDM) and Eigensystem Realization Algorithm (ERA) associated with the Random Decrement (RandomDec) technique were implemented in this thesis. The RandomDec technique give the means to obtain a signal which is proportional to the free decay of the system when it is randomly forced. This proportional signal allows the previously mentioned analysis methods to be used to identify vibration characteristics of the system. The study of flame dynamics based on its image characteristics is barely approached in the literature; for this reason, a complete sensitivity test of all the methods and techniques to be implemented in the real problem of industrial furnaces was initially performed through numerical simulations of a hypothetical system. Afterwards, flame data was used to obtain the vibration modes of image properties. The results lead to conclude that the SIMO (single input and multiple output) model obtained by ERA has vibration modes with more consistent damping regarding flame dynamics and suggest also that this technique could be readily used in the identification of this kind of system, without the need of any other modal analysis for results corroboration. Furthermore, the utilization of operational modal analysis methods to identify a complex system such as the analyzed one may instigate researches on image-based control systems of industrial plants with suchlike characteristics.

The visual sense has outstanding importance for humans’ interaction with the environment and visual attention is the key mechanism that bundles our limited cognitive resources in order to enhance the perceptual processing of the most relevant environmental features at a certain point in time. Eye-Tracking technology enables us to accurately observe peoples’ eye movement behavior i.e. overt attention. In the last decade, overt attention on real-world scenes gained increasing popularity in vision research. The higher ecological validity of such scenes in combination with a free-viewing task allows us to investigate human viewing behavior under natural conditions. In this context, the majority of previous studies focused on the impact of basal image properties, such as color and luminance differences, to quantify the extent to which our fixation behavior is guided by these so-called low-level image properties. However, in most experimental studies complex images are observed only one time, whereas we are continually confronted with repeated visual impressions in everyday life. Therefore, I introduce a repeated-presentation-design that allows scrutinizing the impact of low-level image properties and the power of scene types over time. Besides these low-level factors, I also address inter-individual differences in motivation as well as emotional components as so-called high-level factors in overt attention. Previous research on visual attention has widely neglected these factors, especially in the context of real-world images. On the basis of novel study designs and by means of various analysis techniques, I show how several low- and high-level factors influence overt attention on complex scenes, how they interact, and how eye movement parameters are interrelated. In addition to that, I provide a comprehensive review of the previous literature on emotions’ and personality traits’ impacts on visual attention. On the basis of the inconsistent understanding of core concepts in the literature, I describe how behaviorally oriented studies investigate these high-level factors in visual attention, how the interplay between emotion and attention is conceptualized from a neuroscientific perspective, and I derive several conceptual and practical recommendations for future research. Finally, I outline some new ideas and venues for future research in the general discussion of the present work, for example how eye-tracking might overcome some fundamental problems of classical testing in psychological diagnostics, or how the view of embodied cognition can help us to get a better understanding of high- and low-level factors in visual attention.