Identification of structural parameters for active vibration control

The study of algorithms for active vibration control in flexible structures became an area of enormous interest for some researchers due to the innumerable requirements for better performance in mechanical systems, as for instance, aircrafts and aerospace structures. Intelligent systems, constituted for a base structure with sensors and actuators connected, are capable to guarantee the demanded conditions, through the application of diverse types of controllers. For the project of active controllers it is necessary, in general, to know a mathematical model that enable the representation in the space of states, preferential in modal coordinates to permit the truncation of the system and reduction in the order of the controllers. For practical applications of engineering, some mathematical models based in discrete-time systems cannot represent the physical problem, therefore, techniques of identification of system parameters must be used. The techniques of identification of parameters determine the unknown values through the manipulation of the input (disturbance) and output (response) signals of the system. Recently, some methods have been proposed to solve identification problems although, none of them can be considered as being universally appropriate to all the situations. This paper is addressed to an application of linear quadratic regulator controller in a structure where the damping, stiffness and mass matrices were identified through Chebyshev's polynomial functions.

Um estudo sobre o osu do modelo de cor RGB no proceso de correspondência por correlação

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Background interference on the color of dental composite materials with different thickness by digital contrast

In this work the color dependence of resin composites with the background color was evaluated. The objective was to measure since what thickness the color of the sample stops being influenced by the color of the background over which the resin is placed and the methodology used in experiment was based in analyzing the contrast of digital images of the sample over a black background. The results shown that since 0.8 mm the images contrast becomes almost constant; it prove that since this thickness the color of resin composite depends on the optical resin properties only. The experiment was repeated under three conditions of luminosity to evaluate the influence of it on the image contrast and the results obtained were identical.

Pitch detection algorithms based on zero-cross rate and autocorrelation function for musical notes

This paper discusses two pitch detection algorithms (PDA) for simple audio signals which are based on zero-cross rate (ZCR) and autocorrelation function (ACF). As it is well known, pitch detection methods based on ZCR and ACF are widely used in signal processing. This work shows some features and problems in using these methods, as well as some improvements developed to increase their performance. © 2008 IEEE.

Accuracy of impression techniques for implants. Part 1 - Influence of transfer copings surface abrasion

Purpose: This study evaluated the influence of surface abrasion of transfer copings to obtain a precise master cast for a partially edentulous restoration with different inclinations. Materials and Methods: Replicas (N = 30) of a metal matrix (control group) containing two implants at 90° and 65° in relation to the benchtop were obtained using a polyether impression material and three impression techniques: square impression copings splint with dental floss and autopolymerizing acrylic resin (TRS), square impression copings abraded with aluminum oxide (TA), and square impression copings abraded with aluminum oxide and adhesive-coated (TAA). The replicas obtained in type V stone were digitalized, and the images were exported to AutoCAD software to perform the readings of possible degree alterations in implant inclinations. The results were submitted to analysis of variance (ANOVA) and Tukey test (α < 0.05). Results: Comparing the techniques with regard to the 90° implant inclination, no statistical difference was observed between the three techniques and the control group. Analyzing the three techniques with regard to the 65° implant inclination, no significant difference was seen between technique TA and the control group. Conclusions: Technique TA presented more accurate master casts than TRS and TAA techniques. The angulated implant (65°) tended to generate more imprecise master casts than implants perpendicular to the surface. © 2008 by The American College of Prosthodontists.

Edge detection in digital images using fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in grey shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the grey shades making up the image and, thus, calculate the appropriateness of the pixels in relation to a homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. Copyright © 2009, Inderscience Publishers.

A regularized nonlinear diffusion approach for texture image denoising

In this paper a new partial differential equation based method is presented with a view to denoising images having textures. The proposed model combines a nonlinear anisotropic diffusion filter with recent harmonic analysis techniques. A wave atom shrinkage allied to detection by gradient technique is used to guide the diffusion process so as to smooth and maintain essential image characteristics. Two forcing terms are used to maintain and improve edges, boundaries and oscillatory features of an image having irregular details and texture. Experimental results show the performance of our model for texture preserving denoising when compared to recent methods in literature. © 2009 IEEE.

Digital radiography for the inspection of weld seams of pipelines - better sensitivity

Conventional radiography, using industrial radiographic films, has its days numbered. Digital radiography, recently, has taken its place in various segments of products and services, such as medicine, aerospace, security, automotive, etc. As well as the technological trend, the digital technique has brought proven benefits in terms of productivity, sensitivity, the environment, tools for image treatment, cost reductions, etc. If the weld to be inspected is on a serried product, such as, for example, a pipe, the best option for the use of digital radiography is the plane detector, since its use can reduce the length of the inspection cycle due to its high degree of automation. This work tested welded joints produced with the submerged arc process, which were specially prepared in such a way that it shows small artificial cracks, which served as the basis forcomparing the sensitivity levels of the techniques involved. After carrying out the various experiments, the digital meth odshowed the highest sensitivity for the image quality indicator (IQI) of the wire and also in terms of detecting small discontinuities, indicating that the use of digital radiography using the plane detector had advantages over the conventional technique (Moreira et al. Digital radiography, the use of plane detectors for the inspection of welds in oil pipes and gas pipes.9th COTEQ and XXV National Testing Congress for Non Destructive Testing and Inspection; Salvador, Bahia, Brazil and Bavendiek et al. New digital radiography procedure exceeds film sensitivity considerably in aerospace applications. ECNDT; 2006; Berlin). The works were carried out on the basis of the specifications for oil and gas pipelines, API 5L 2004 edition (American Petroleum Institute. API 5L: specification for line pipe. 4th ed. p. 155; 2004) and ISO 3183 2007 edition (International Organization for Standardization, ISO 3183. Petroleum and gas industries - steel pipes for pi pelines transportation systems. p. 143; 2007). © 2010 Taylor & Francis.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

Improving image classification through descriptor combination

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

Geração automática de modelos digitais de superfícies utilizando múltiplas imagens

Pós-graduação em Ciências Cartográficas - FCT

Utilização de equações diferenciais parciais no tratamento de imagens orbitais

Pós-graduação em Ciências Cartográficas - FCT

Procedimento híbrido envolvendo os métodos primal-dual de pontos interiores e branch and bound em problemas multiobjetivo de aproveitamento de resíduos de cana-de-açúcar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção de Crateras de Impacto em Imagens Digitais. Estudo de caso: Superfície de Marte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)