Análises de falhas em eixo de laminadora

Pós-graduação em Engenharia Mecânica - FEG

Identificação de doenças em folhas vegetais da cultura de algodão

Pós-graduação em Ciência da Computação - IBILCE

Compactação de um cambissolo háplico com o tráfego de um trator skidder no arraste de pinus elliottii

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação do ruído e da vibração no posto de trabalho em dois tratores agrícolas

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Processamento de imagens digitais para detecção e quantificação de defeitos na madeira serrada de coníferas de reflorestamento de uso não estrutural

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Desenvolvimento e avaliação de equipamentos e metodologia para determinação de parâmetros físicos do solo relacionados a dias trabalháveis com máquinas agrícolas

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Energetic efficiency of an agricultural tractor in function of tire inflation pressure

The tire inflation pressure, among other factors, determines the efficiency in which a tractor can exert traction. It was studied the effect of using two tire inflation pressures, 110.4 kPa in the front and rear wheels, 124.2 kPa in the front wheel and 138 kPa in the rear wheels, the energetic efficiency of an agricultural tractor of 147 kW of engine power, in the displacement speed of 6.0 km.h-1, on track with firm surface, with the tractor engine speed of 2000 rpm. For each condition of the tire pressure, the tested tractor was subjected to constant forces in the drawbar of 45 kN and 50 kN, covering 30 meters. It was used a randomized complete block with a 2x2 factorial arrangement (tire pressure and drawbar power) with four replications, totaling 16 experimental units. Data were subjected to analysis of variance, using the Tukey test at 5% probability for comparison averages. The lowest hourly and specific fuel consumption, the lowest slippage of the wheelsets and the highest efficiency in the drawbar was obtained with the tire inflation pressure of 110.4 kPa in the front and rear tires of the tractor, highlighting that lower pressures improve energetic and operational performance of the tractor.

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Acidentes graves fatais no trabalho de corte mecanizado de cana-de-açucar: o olhar através do método mapa

Pós-graduação em Saúde Coletiva - FMB

Estudo comparativo da eficacia de dois adesivos dentinarios e um cimento de ionomero de vidro empregados na adesão do amalgama a dentina

Pós-graduação em Odontologia Restauradora - ICT

Influence of the surface treatment of tire rubber residues added in mortars

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

Hot turning of a difficult-to-machine steel (sae xev-f) aided by infrared radiation

A possible way for increasing the cutting tool life can be achieved by heating the workpiece in order to diminish the shear stress of material and thus decrease the machining forces. In this study, quartz electrical resistances were set around the workpiece for heating it during the turning. In the tests, heat-resistant austenitic alloy steel was used, hardenable by precipitation, mainly used in combustion engine exhaustion valves, among other special applications for industry. The results showed that in the hot machining the cutting tool life can be increased by 340% for the highest cutting speed tested and had a reduction of 205% on workpiece surface roughness, accompanied by a force decrease in relation to conventional turning. In addition, the chips formed in hot turning exhibited a stronger tendency to continuous chip formation indicating less energy spent in material removal process. Microhardness tests performed in the workpieces subsurface layers at 5 m depth revealed slightly higher values in the hot machining than in conventional, showing a tendency toward the formation of compressive residual stress into plastically deformed layer. The hot turning also showed better performance than machining using cutting fluid. Since it is possible to avoid the use of cutting fluid, this machining method can be considered better for the environment and for the human health.

STOCHASTIC ADDING MACHINE AND 2-DIMENSIONAL JULIA SETS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Integrated cutting machine programming and lot sizing in furniture industry

In this paper a mathematical model that combines lot-sizing and cutting-stock problems applied to the furniture industry is presented. The model considers the usual decisions of the lot sizing problems, as well as operational decisions related to the cutting machine programming. Two sets of a priori generated cutting patterns are used, industry cutting patterns and a class of n-group cutting patterns. A strategy to improve the utilization of the cutting machine is also tested. An optimization package was used to solve the model and the computational results, using real data from a furniture factory, show that a small subset of n-group cutting patterns provides good results and that the cutting machine utilization can be improved by the proposed strategy.