891 resultados para Tire inspection machine


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Pós-graduação em Microbiologia Agropecuária - FCAV

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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Ciência da Computação - IBILCE

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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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.

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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.

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Pós-graduação em Saúde Coletiva - FMB